Seeing that we couldn’t have done otherwise in a situation as it played out draws attention to why we behave as we do, giving us more control in future situations, for instance over when and what we eat. The behavior technology involved in weight loss can apply in just about any domain where we seek control, personal or collective. But accessing all the resources of behavior tech requires that we finally grow up as a species, accepting our place in, not above, nature.

Article Index

• Opening gambit
• High level advisories
• Commitment devices
• Managing food situations
• Portion control
• Healthy food
• Exercise
• Monitoring
• What to expect
• Well beyond weight loss

Opening gambit: could you have done otherwise?

Many folks struggling with their weight suppose that in consuming chocolate cake on a particular occasion – substitute your favorite fattening food – they could have resisted eating it, but failed to do so.

Source: http://www.flickr.com/photos/bigbaddie/4907862472/

To see that this is mistaken is perhaps what’s unique about weight loss naturalism. On the naturalistic, science-based view of human beings, there is no you-the-decider independent of your brain, body and situation which rules over them. There’s no immaterial you in charge of the material you that determines what you eat. You – your brain and body – could not have done otherwise in that actual situation given the circumstances, and to understand and accept this can help you gain control over your weight. For you to have resisted the cake, something would have had to been different about that situation, either inside you or outside you or both. This is because, on a scientific understanding, your behavior is a fully caused result of all the factors in play – there isn’t a freely willing, causally exempt decision-maker inside you that could have done otherwise, such as a soul or non-physical mental agent.¹

Making future situations different such that you are caused to choose the sherbet (with occasional, intentional and well-deserved exceptions!) is our objective here. Seeing that you couldn’t have done otherwise in the actual situation will help you do otherwise in future situations, since those will be different (we hope) in respects that make it more likely you’ll resist temptation.

Supposing you could have resisted the cake no matter what the conditions were subverts the naturalistic, causal basis for self-control. Why? Because you’ll tend to downplay or ignore the actual determinants of your behavior. Want to gain control over your weight? Then give up the myth of the radically autonomous decider that trumps causality with its contra-causal free will, what philosophers often call libertarian free will. You’ll pay more attention to setting things up so that in the future you’ll more likely be determined to lose weight (both meanings apply).

Compassion and control. Seeing you don’t have contra-causal free will – that you are fully caused – has the effect of highlighting the conditions that actually influence your beliefs, desires and decisions. You can’t suppose you can just will your way to weight loss independent of conditions. Instead, you’ll concentrate on changing those conditions such that you’ll make better choices about eating and exercise. You become smarter and more intentional about behavior change. In short, seeing through the myth of contra-causal free will, should you be in thrall to it, gives you greater control over yourself and your situation. It also makes you more tolerant of any set-backs you encounter: you can’t suppose that, given the conditions in play, you could have done otherwise. Compassion, as well as control, follows from seeing our full causal connection to the world, past and present. Hence the tagline for the Center for Naturalism: “connection, compassion, control.”

Cause and effect. Losing weight is completely a matter of cause and effect, in this case caloric intake vs. caloric expenditure, and that balance depends almost entirely on what you do. What you do in turn depends on who and what you are, plus your situation. And part of who you are includes what you believe about yourself, including what you believe about how you make choices. Getting real about all this – applying science to yourself as a chooser and decider – is to become more reality-based in your self-image and therefore more effective in realizing your goals. Admitting your behavior is fully caused, and understanding how it is caused, is an important higher-level cognitive tool you can wield in service to self-control.

Chance and control. A quick reminder about chance in all this: if there should be a random element which plays a role in your behavior, for instance something at the quantum level that percolates up in how your brain makes a choice, that obviously doesn’t give you more control or power in a situation. True, it means that something different might have happened given the exact situation, but it doesn’t allow you to understand and predict your behavior in future situations. So there’s no good reason to want there to be exceptions to causal laws, for instance the laws that connect your actions to your desires, or your desires to circumstances. Chance doesn’t give us control, nor does it give us a kind of freedom worth wanting.²

Passivity and excuses. And a quick reminder about passivity and excuse-making: realizing that you’re fully caused doesn’t in the least diminish the value of the goals you’ve set for yourself, in this case weight loss. Losing weight is just as desirable as it was before. Plus, your behavior is just as effective as it ever was in bringing about what you want. So there’s no invitation to passivity here: don’t confuse determinism with fatalism, a mistake people often make. And just because your behavior is fully caused doesn’t mean that you’re let off the hook for not doing the right thing. Don’t confuse explanations with excuses. You can and should hold yourself accountable (and ask others to hold you accountable) for following through on your expressed commitment to lose weight, once you make that commitment. Such accountability, along with other factors, helps to cause you to lose weight, because you as an agent are responsive to it (hence responsible). Since you as an identifiable person are just as real as all the other factors in the weight loss situation, accepting your active role as a responsible agent is simply to be reality-based and effective in the quest for self-control.

From metaphysics to the real world. Regrettably, a sudden flash of metaphysical insight about contra-causal free will (for those who supposed they had it) isn’t entirely enough to slim down. We have to get into the specifics of behavior change as outlined below. These are gleaned from various sources, including some personal experience in a Weight Watchers program (see endnote 4). Some suggestions will be comparatively easy to adopt, others less so, but none require any superhuman or supernatural will power, which means you can likely succeed in gaining control over your weight. Having put aside the idea that some part of you is exempt from causation, you’ll be more likely to pay attention to, and change, what causes you to be overweight. This has ramifications beyond weight loss, since effective techniques of self-management can be applied in pursuit of more momentous goals, both personal and collective (see the Behavior Tech page and the last section of this article).

But, you might ask yourself, will I actually take steps to lose weight? Well, we don’t know what the future holds, although it holds something (see here). But if you follow the suggestions below, then it’s likely you’ll lose weight, and keep it off. Believing this reasonable proposition is itself an inducement to actually follow the suggestions. On the assumption you’re at least beginning to believe it, you’re already being caused to lose weight, congratulations!³

Higher level advisories on behavior change

Having stirred the pot a bit with the challenge to contra-causal free will, let’s list some higher level observations and generalizations that set the stage for the more specific strategies to come.

Be scientific and empirical. In deciding how to lose weight, look for evidence-based practices coming from reputable sources that reflect what we know about human physiology, psychology and behavior. In weight loss, as in every other aspect of our lives, we must play by nature’s rules, and knowing the rules often helps us avoid false starts and unsuccessful strategies. I don’t know about you, but I always obey the laws of physics, chemistry, biology, psychology and other sciences as they are discovered to apply to human beings. Don’t trust your own untutored intuitions; don’t trust hearsay; don’t let what you want to be the case distort your view of what is the case. This advisory of course applies to the advice given here: don’t take it on faith. A modicum of skepticism is always in order. Or as they say in Missouri, “Show me.”

Analyze this. Conduct an analysis of your situation to see what’s causing the behavior you want to change, in this case eating too much, too often, and maybe not exercising enough. The causes are both internal to you and external, in who and what you are and in your situation. They can be pretty concrete, such as your proximity to food and the company you keep, or pretty abstract, such as your beliefs about human agency discussed above. You’re very likely not an expert in behavioral analysis, but you needn’t be to get a useful handle on your situation; plus you can always ask for help in understanding why you do what you do. Any increase in understanding will give you that much more control.

Everything presents an opportunity for intervention. All the determinants of your behavior are possible targets for change. True, there is no outside vantage point independent of you and your situation from which you can exert control. This might seem problematic given the traditional notion that we need to be uncaused causers to have “real” control, to have leverage over events. But if you think about it (have you thought about it?), being an uncaused causer doesn’t help give you control or power; see “The flaw of fatalism.” Also note that the weight loss project is engaging desires that were already present in you. So it isn’t as if you’re starting from scratch – your feet are already firmly pushing against the starting blocks.

The virtuous circle. We can perhaps roughly divide the opportunities for intervention into domains of belief, desire, situation and behavior: BDSB. Any of these can be worked on in order to bring about improvements, and at least some of them must be changed. Since they are interlinked, changing an element in one domain will likely change elements in the others to some extent. You can work on your beliefs, desires, situation and behavior in any combination. The opening section above, for instance, was keyed to changing your beliefs about behavior, about who you really are as an effective agent. If that belief changes in a more realistic direction, it can help bring about helpful changes in behavior, which in turn will change your situation to your advantage, which will feed back into more effective behavior, likely reinforcing your desires to lose weight and gain control that got the whole process started. The virtuous circle awaits you.

Be Skinnerian. Behavior is controlled (or shaped, as behaviorist B.F. Skinner liked to say) by its consequences, the rewards and punishments that follow it. We therefore have to engage in incentive management – incentivizing behavior to produce behavior change. Since humanistic naturalists like me want to stay on the positive side of the ledger, we’ll try to use rewards more than punishments in losing weight. We want to make the process of achieving self-control as painless as possible, and of course a primary strategy in this is to reinforce behavior positively, for instance by achieving goals. There’s nothing like success to consolidate a behavioral repertoire; indeed, Skinner himself was always trying to invent reward-based, non-punitive behavior change strategies (he was voted Humanist of the Year back in 1972). However, at least a few rude awakenings (stepping on the scale after a week’s travel) are unavoidable, and they too function to shape behavior. To err is human, and to discover you’ve erred is no fun – it’s a mild bit of punishment that makes you want to do better next time. Keep in mind that in accepting the bits of pain that come our way in losing weight, we’re trying to avoid the much more painful, restrictive consequences of being overweight and out of shape, and we want to access all the energy and self-efficacy of being physically fit. So a little pain now, whether it’s from resisting temptation or being given a little grief for having failed to resist it, is well worth it.

Find other rewards in life. Food is a basic reinforcer, so people tend to resort to it if other reinforcers – that is, pleasurable activities and other intrinsic and extrinsic rewards – aren’t there. This highlights the importance of making one’s life situation to be rewarding in many respects besides eating (which is not at all to dismiss the pleasures of food). The more other activities you enjoy that can compete with eating, the less eating will control you and your behavior. Being physically active – using your body to increase lean muscle and burn calories – is one such type of activity.

Get real. Behavior change isn’t a piece of cake (sorry!). Don’t suppose you can change your beliefs, desires, behavior and situation overnight. Be realistic so you don’t set yourself up for disappointment. Knowing you will sometimes fail (oh no!) goes with the territory. But being realistic is, very importantly, also to believe that progress is entirely possible. With knowledge of cause and effect on your side, you will very likely prevail.

Fully endorse and protect your goal. This advisory is about your desires and motivations. Don’t beat around the bush: do you really want to lose weight, get in better shape, gain in energy, establish a domain of self-control that you can extend to other areas of your life, and get rewarded by achieving your goals? Of course you do! Can you seriously not fully endorse all of the above? But of course you are not a single-minded creature (more reality here, sorry). You are subject to countervailing influences: appetites, peer pressure, fatigue, distractions, lack of time, pressing obligations, fear of failure, etc., all of which need to be managed to keep on track. Protecting and nurturing the motivation and opportunity to lose weight against the predations of opposing influences is the name of the game, and it’s entirely possible to win at it.

Incrementalism. Start small and work up: the Big Idea of this article is that you can gradually establish a pattern of control, starting with controlling your weight. Any step you succeed in making toward your goal, however small, is evidence of control, and that evidence will reward you for taking that step. Choose achievable, incremental (bite size?) goals such that you get to experience success. Each bit (bite) of success, such as not having seconds, or using smaller plates, helps to reinforce the behavior that led to it, and, just as important, rewards and reinforces your determination to stick with the entire project of losing weight. This will get you going on the virtuous circle.

Generalization. Success in one area has the further effect of establishing a more general pattern of self-control. For instance, success in establishing portion control (consistently using smaller plates for meals, not going back for seconds) will give you confidence that you can succeed in setting up an exercise routine to build and maintain lean muscle (which in turn helps keep weight off, see below). On a larger scale, success in controlling your weight will serve as a model for self-control in other domains; it proves it’s possible for you to manage your beliefs, desires, situation and behavior to achieve your goals. What’s not to like?

Now that we’ve set forth some pretty abstract principles and guidelines, let’s move to more specific strategies and techniques for weight loss. Remember, if you actually practice what’s preached below, then you will very likely lose weight, and keep it off.

Commitment devices and support networks

These are steps you can take to shore up your determination to stick with a weight loss program. Commitment devices are techniques to help you follow through in pursuit of a goal. Having a support network means that you’re not doing it on your own. It’s perfectly possible to do it on your own, but a tougher proposition for most of us. This of course applies to achieving other goals besides weight loss.

Put some money up front. A financial commitment is a good way to maintain motivation. Having paid for participation in a weight loss program, you’ll naturally want to get your money’s worth. This makes it more likely that you’ll stick with the program, for instance in going to meetings and following behavioral advice. But of course it’s perfectly possible to lose weight for free too, so don’t think you have to join a paid program.

Join, or form, a weight loss group.⁴ Being part of a group has many advantages, one of which is making your commitment public to other members. You won’t want to disappoint your peers; you want to look good, show people that you can follow through, get their approval for doing so, and be held at least somewhat accountable. Making a public commitment to lose weight puts your reputation on the line. And of course a group provides psychological and motivational support, learning opportunities, and a chance to widen your social network. Plus, helping others achieve their goals by sharing your own insights and successes (and setbacks) is very satisfying. In all this you’re putting basic human psychology to work to your advantage. Last but not least, the group will most likely have a leader who is familiar with what works to produce behavior change leading to weight loss.

Recruit your spouse, friends, co-workers and family. The same commitment device/support network logic applies here: you already have a network, so put it to work for you. Let people in your life know you’re working on losing weight, and ask for their help in keeping your vow to do so. As you’ll discover, there are many ways they can help with changing your environment (removing candy bowls at work), with giving you support (praise for meeting a goal) and commiseration (sympathy when you don’t). It might turn out that for you to meet your goals, they’ll have to change their behavior in some respects as well, and it will likely be for the better. You could end up leading the charge in your family or social network for healthier behavior – who knew you had it in you?

Science flash update: See this Economist article about a new evidence-based model of weight loss, and try out the Body Weight Simulator it mentions. The article provides more realism about the difficulties of losing weight, saying “in principle, the heavier person could make the necessary cuts in stages—reducing his daily intake again and again as he lost weight. In practice, that would take a will of iron, and the few people who have such willpower rarely get fat in the first place. The lesson, then, is to stay, rather than become, slim.” Ok, point taken, but weight loss naturalism and other applications of behavior tech show how willpower itself – in this case your determination to lose weight – is a function of conditions. It can be fortified by means of all the strategies mentioned above and below; it isn’t a fixed quantity you either have or don’t. So stay reality-based; don’t let this new model get you down!

Managing food-related beliefs, behavior and situations

Now the rubber hits the road, Jack. The basic goal is to reduce the frequency and amount of food intake, while eating healthy foods that meet your caloric and gustatory needs. Remember: take these steps incrementally, track your progress in taking them, and make sure to notice that your successes are evidence that you’re establishing a pattern of self-control. We want you to get caught up in the virtuous circle of BDSB change: changes in belief, desire, situation and behavior that reduce caloric intake.

Guard your appetite! You can use hunger to your advantage, strangely enough. Several strategies apply here:

Reinterpret being hungry. Change your beliefs and attitudes about hunger. Instead of thinking of hunger as a state to be avoided at all costs, reframe it as a sign of success. Guard your appetite! Being hungry indicates that you’re on the deficit side of the caloric transaction – you’re using calories faster than you’re imbibing them. That’s a good thing, right? Right: being hungry means you’re making progress in your project. And just because you’re hungry doesn’t mean you need to eat right away; you can learn to wait. Having made the switch in how you think about hunger (a change in belief), you can even enjoy the fact of being moderately hungry, strange as that may sound. For instance…

Being hungry makes food tastier. Enjoy being hungry as a preview of pleasure to come. Once you’ve experienced on a number of occasions that food really does taste better if you’re sharp set, then it will be easier not to eat right away – it will change your behavior. Likewise, remember the…

Law of diminishing gustatory returns. It’s the initial bites and portions that taste best, and the more you eat, the less rewarding it gets. Knowing this helps to limit your intake. Relatedly…

Don’t eat if you’re not hungry. Before eating anything, check to see if you are hungry or not, and just how hungry you are. Can you please wait till you are quite, or reasonably, hungry? Thank you. This will also prepare you for times, Force forbid, when food isn’t immediately available.

Use food as a reward. You can “be Skinnerian” by finishing a task before your meal or snack, in particular tasks that aren’t that rewarding or that you’ve procrastinated on. You reward yourself with food for having gritted through a necessary but perhaps tedious bit of work. Do the dishes piled up in the sink before you have dinner. Then you can enjoy the meal and not face the pile afterwards. That enjoyment will reinforce doing the dishes first. There are all sorts of ways and opportunities to be Skinnerian, that is, to manage incentives to get better control of your behavior and your situation. About which, please read this on how to train your significant other, roommate, or child to behave better; and remember, the same lessons apply to you.

Displacement and distraction. If hunger is starting to get the better of you, but it isn’t time to eat yet, substitute other activities for eating. Activities involving movement (e.g., walking, exercise, stretching, doing laundry, cleaning house, watering the garden, minor maintenance) work better than those requiring sustained concentration or sitting still (e.g., reading, writing, watching TV). Why? Hunger is less noticeable if you’re moving and actively doing things, at least for me. Activities that get you out of range of food are of course the best. Experiment to see what works for you.

Manage your food environment. Buy only healthy and balanced food for your household and for work. See below for what that is. Your immediate food environment, over which you have control, is a very important determinant of your food behavior, so be smart about what foods are available to you. Don’t buy the naughty stuff unless you’ve already established the self-control not to binge on it. Relatedly…

Keep temptation out of sight. Both and home and at work, avoid keeping snacks ready to hand since that will subvert self-control. Instead, arrange your situation to minimize temptation. Again: “Arrange your situation to minimize temptation.” Very good!

Plan your food behavior ahead. This will help you minimize the frequency of eating. For your regular workdays (or simply days, if you don’t work), make a schedule of meals and snacks – e.g., breakfast/snack/lunch/snack/dinner – with fairly specific times and stick to it; wait to eat until the appointed time. If you find yourself getting hungry in advance of the time you’ve scheduled, that’s how it’s supposed to work. Wait! Being hungry is a good thing, or at least not a bad thing (see above). Map out your food day, set your goals for portion control (see below), and prepare what’s needed in advance as necessary, such as making a lunch. As you make and stick to your plan, you’re being successful in gaining a pattern of control, and such success is very rewarding.

Portion control

Perhaps the biggest challenge in weight loss is simply eating less than you’re used to. You need to reduce the size of portions as well as the frequency of eating. Exercise is important (see below), but definitely will not substitute for portion control in losing weight (sorry!). What will cause you to reduce your portions? Changing your food behavior and situation will do the trick. Here are some tips on how to take and eat less food at each meal.

Serve yourself at home. Don’t let anyone else decide how much to put on your plate, since if they put too much you might feel obligated to eat it and use that, wrongly, as an excuse to have more than you should (the excuse doesn’t fly since no one was holding a gun to your head, forcing you to eat it). If they give you too little, you’ll have to go back for seconds, possibly subverting the general rule of not having seconds (see below). Here are some other deceptively simple admonitions, or at least not simply deceptive:

Use smaller plates. This works to make portions appear larger, and there’s less room on the plate to pile on more food. For our main meals, we switched from regular 11 inch dinner plates to 7 inch shallow soup bowls with a wide flat rim. Less food looks like more, and it looks less lonely than when sitting on a big plate, surrounded by emptiness, wanting company from more food, poor thing.

Don’t have seconds. By abjuring seconds, thus reducing your caloric intake, you’re taking a very strong step to weight loss. Take a reasonably sized first helping, eat it slowly, savor it, and that’s all folks. And keep in mind: because you’re hungry at the start of a meal, the first helping is always the best, so seconds of anything aren’t as rewarding – they will let you down, gustatorily. To satisfy a desire smartly, not indiscriminately, is both to enjoy its satisfaction more and gain some control over it.

Don’t rush, practice mindfulness. Remember, it takes a while for your stomach to register the fact that it’s had a sufficiency, which is why it’s important not to rush eating, or rush to have more. If you eat deliberately, you’ll be less likely to eat more than you should. Be mindful of, that is, pay close attention to, how your hunger diminishes in response to eating, and try to notice when it ends before the feeling of being stuffed arrives. Stop eating before you feel stuffed.

Do not finish up leftovers. Don’t eat food that’s left in the pan, bag, or plate just to get rid of it, even if it’s a very small amount! Do not do it! You don’t have to finish the sandwich just because some of it’s still there on your plate. Put it away for later consumption, feed to cat, or otherwise remove from easy accessibility. Every bit of caloric intake matters and even little bits add up, inevitably. Since you now believe this to be true, you’re more likely to behave in a way that takes this truth into account: belief change translates into behavior change.

Fruit and salad first. Start lunch with that apple, nicely sliced and cored, and you’ll savor every bite because you’re hungry and it will fill you up a bit in advance of more caloric foods. A little cinnamon perhaps, or fresh ground nutmeg (keep some in your desk drawer at work, along with a grater). Or have those carrots first. At dinner, same idea: start with your salad.

Vary your diet. Novelty can be rewarding, thus helping to compensate for smaller portions and having to wait until your scheduled mealtimes.

Eat filling foods. Weight Watchers has lots of advice about what these are that I won’t repeat here (see endnote 4), except to say that it can help to have…

Fiber first. If you use a fiber supplement (e.g., psyllium husk), have that in advance of eating, or while you’re eating, since it helps fill you up. Some of these supplements help ensure you’re getting sufficient fiber for digestive health, and some say they’re good for heart health as well. (Caution: don’t take my word for it; look for reliable scientific evidence to validate these claims). The orange flavored fiber supplements are a reasonable facsimile of an orange drink, especially when mixed with sparkling water, not bad with a sandwich (see endnote 4).

Micro desserts. If you like desserts, have just a bite or three of very good chocolate, candied ginger, or other intensely flavored sweet, keeping in mind that additional bites won’t be as rewarding as the first. Become a connoisseur of maximally rewarding dessert moments that don’t subvert your weight loss goals.

The problem with restaurants. Not eating too much at restaurants can be very difficult, especially if you’re with peers who aren’t with the program, but it’s possible if you have some strategies thought out in advance. Choose or ask for smaller portions on small plates and avoid those dishes you know perfectly well are unhealthy or super-caloric. Nicely ask your waitron to remove or pack up what seems to be an excess quantity right away, before you’re tempted to dispose of it right there at the table.

Occasional exceptions. Even in the weight-losing phase of your program, as opposed to the maintenance phase, it’s ok to now and then indulge in what seems (and is!) caloric excess or otherwise questionable food choices. Being too rigid in a weight loss regimen can set you up for a fall, so cutting yourself some slack as part of the program (as does Weight Watchers) is perfectly ok, so long as the overall caloric trajectory and healthiness of your choices are maintained. This goes for most, perhaps all, the rules above and below: occasional exceptions to rules help to make rules more effective. But here’s a question: does the rule just stated apply to itself? I think so, since some rules are more effective if you don’t ever break them.

Healthy food

A consensus of evidence-based belief seems to be emerging about what constitutes a healthy diet, with an emphasis on minimizing processed carbohydrates and fats found in red meat and other bad fats (there are good ones). Get adequate protein, fiber and nutrients; eat your fresh fruits, veggies and legumes; and nuts on a daily basis are good in small quantities. If you’re a vegetarian or vegan, make sure you’re getting enough protein, maybe via a protein supplement if necessary. For a recent science-based analysis of what foods seem to be associated with weight reduction, please read Still counting calories? Your weight-loss plan may be outdated. It isn’t just how many calories you consume that matters, but the type of food that’s carrying the calories.

Fiber and protein. According to Weight Watchers, which touts the scientific basis for its program (see endnote 4), digesting fiber and protein uses more energy than digesting simple and/or refined carbohydrates. This is one reason their weight loss plan allocates food points to steer you towards the former and away from the latter. Fiber and protein supplements can help to ensure you’re getting your needs met in this regard, but you can’t rely on them as substitutes for real food.

Exercise, muscle and eating: the virtuous circle

One aid to losing weight and keeping it off, according to many sources, including Weight Watchers, is to increase and maintain your amount of lean muscle. Lean muscle burns calories more than fatty tissue, even at rest, so the more muscular you are, the easier it is to burn calories without even trying. This means, once you’re down to your target weight, if you’re muscular you can eat more than you could otherwise and maintain the same weight. This in turn means you can have more food enjoyment and be stronger, more physically capable, and more energetic. What’s not to like?

Exercise, of course, is the route to building lean muscle, and it has many other benefits, physical and psychological. Unless you’re a professional athlete or trainer, or your trade involves regular and intense use of all major muscle groups, you need to engage in an intentional program of exercise that builds and maintains muscle. This is possible at any stage of life, so being old (however you choose to define it!) is no excuse not to exercise. One has to be careful, of course, to not overdo it, so be smart and incremental as you take up exercise. For instance, in order to get stronger you don’t need to lift the maximum weight you’re capable of, putting your joints and tendons at risk. Taking an exercise class is helpful for the reasons mentioned above about joining a weight loss group. You’re more likely to exercise harder, and enjoy it more, if you do it with others than on your own.

My exercise routine (fwiw). After taking an 8 week small group training in intensive exercise (they called it “boot camp” and it was), my workout 3 days a week is to do about 30-45 minutes of minute-long sets of free weight lifting, machines and core exercises (e.g., planks, crunches) with 30-45 second breaks in between, stopping every 10 minutes or so for a 3 minute water break. This routine gets my heart rate and breathing up pretty high for most of the workout while working all the muscle groups hard, thus maintaining muscle strength and cardio conditioning simultaneously. I vary the exercises from one day to the next, which helps to keep it fun (or, more realistically, less onerous). As you lose weight, some exercises, such as pull ups, become easier since you’re lifting fewer pounds of yourself. It’s very rewarding to be able to do double or more the pull ups than what you could before. Remember too that the endorphin release after strenuous exercise will elevate your mood very reliably.

Monitoring your weight and behavior

Regular weigh-ins. Make sure to weigh yourself often (e.g., every day at the same time), so that you get continuous feedback on how you’re doing. Once you see your weight start to drop, bit by bit, the very act of weighing yourself becomes rewarding, hence part of your routine. If you see it creeping up, that’s an early warning to resume what you were doing right.

Record your weight. Keep a weekly diary of your weight to track your progress and to see how it correlates with your food-related behavior. Such correlations are evidence for what does and doesn’t work in weight loss. Relatedly…

Record significant changes in your behavior and situation. Keep a simple diary of what changes you make in your food-related behavior and situation, including exercise, so that you remember what you did and when. This record will show that you did make changes, that you were able to establish a pattern of control, which is rewarding in and of itself. And as noted above, you’ll also be able to see what changes in behavior and situation are associated with changes in your weight. Knowing what works – being empirical about the process of losing weight – helps you keep doing the right thing.

What to expect

Weight loss. If you reduce the frequency of eating and portion sizes as described above, it’s very likely you will begin to lose weight. Indeed, it’s inevitable you’ll lose weight if your caloric intake drops below your caloric expenditure in maintaining your bodily functions and in carrying out daily activities. In a 16 week Weight Watchers program, I lost 16.6 pounds (averaging about 1 pound lost per week) to reach my target weight, which I’ve maintained since then.

Hunger. You can expect to feel hungry more often, especially when you’re in the weight loss phase of the project (as opposed to the maintenance phase, when you can increase food consumption somewhat). But as explained above, this is not a bad thing. Since you’ve reinterpreted hunger as a sign of success, and since hunger now precedes more enjoyable food experiences, hunger isn’t something to fear or avoid like the plague. You can accept it as part of a successful process of losing weight and gaining control.

Food satisfaction. You can expect to enjoy food more, since you’re eating less often and less of it. Food tastes better when you’re hungry, which you’ll be more often. You’ve become a connoisseur of fewer, but more intense food moments, which you can enjoy in anticipation as well. Seeing this adds to the total picture of having gained control: you’ve actually gained in net pleasure too. You’ve managed to manage a desire to optimize its satisfaction.

Satiation. Once you’ve reduced portion size for a while, you’ll find that you’ll feel uncomfortably stuffed if you eat the amount you used to, for instance when you had seconds and maybe thirds. Instead of feeling comfortably satiated, you’ll feel as if you overdid it – and you have! That feeling will help get you back on track. Put another way (as Skinner would put it), feeling stuffed becomes aversive, not pleasurable, so you’ll avoid the behavior that leads to feeling that way, namely eating too much. As you eat, remember to stop before you start feeling stuffed.

Well beyond weight loss: behavior tech and collective self-control

All the practical recommendations above, and the more abstract advisories that preceded them, can prove useful in losing weight even if you declined the opening gambit: that your behavior is fully caused. Even if you insist that you could have done otherwise in an actual situation as it played out, for instance the cake-choosing situation, these advisories will still work for you. However, if you suppose you’re exempt from causation in some respect, you’ll be less likely to pay attention to the full set of conditions that, from a scientific standpoint, actually determine your motivations and actions. This reduces the amount of potential control you have over them, which disempowers you. You’ll also be more likely to blame yourself in emotionally toxic ways, since you’ll imagine that you could have done otherwise, but simply failed to do so as a matter of contra-causal choice. Chronic self-blame is unproductive and demoralizing. So there are two good pragmatic reasons to disbelieve in contra-causal free will: the gain in self-control and the gain in self-compassion. But of course the primary reason to disbelieve in it is on empirical grounds: there’s no science-based evidence you have it, and science is by far the most reliable grounds for factual beliefs about the world.

Wherever you end up in your beliefs about free will, the techniques of behavior change and incentive management that work in weight loss can be applied in any domain where you want to gain control. Having won the battle to manage your weight, or at least having made progress in it, you’re now in a position to generalize your weight loss strategy. Analyze your situation to see what’s causing the behavior you want to change. These causes lie in your beliefs, desires, concrete environment, social networks, and wider culture. All of these are potential targets for intervention. Proceed scientifically, incrementally and realistically, taking note of your progress as evidence that yes, you can establish domains of self-control.

Our desires for self-mastery and self-actualization are perfectly legitimate concerns for each of us individually, but not the end of the story when it comes to the quest for control. Inhabiting a technologically advanced culture, we’ve gotten very good at designing gadgets to make life easier and more entertaining, and in arranging environments to be pleasing and convenient. In comparison, we’ve spent very little time thinking about and designing ways to manage ourselves for our own good and the good of other species and the environment. Even to raise the question of collective self-control using behavioral technology (behavior tech) is controversial, since it immediately raises the specter of authoritarian states trampling on human rights and individual initiative. But there’s no necessary contradiction between intentional collective self-management and having an open, democratic society; indeed, the latter might well depend on attaining the former (see here and here). We can, and must, take on the question of control explicitly, asking how we can balance our legitimate desires for liberty and autonomy against the pressing needs for constraints on behavior, for instance on reproduction and consumption in an age of diminishing resources. We are the inheritors of a culture premised on the supreme value of personal freedom, but understanding its practical limits may be the best, and only, way to preserve it.

We either take control intentionally, in light of an open conversation about what sort of world we want and what sorts of democratically self-imposed constraints are necessary to achieve it, or we will likely face a rather uncomfortable future dominated by the consequences of not taking control. Believing this, we are more likely to embark on the momentous project of applying behavioral technology to ourselves in the pursuit of long-term happiness. This will be progress toward achieving maturity as a species, one fully cognizant and accepting of its own nature, and thus capable of exerting skillful self-control on its own behalf and on behalf of its unthinking, vulnerable parent: planet Earth.

Endnotes

Related posts:

1. Guns Or Butter: Reflections On How Science And Technology Impact Us
2. A Rational Approach to Understanding the Irrational Behavior of Indians
3. Naturalism: Scientific, Philosophical and Socio-Political.
4. Worldview Naturalism
5. Are You A Freethinker? Naturalism, Life and Meaning in a Causal Universe
6. Naturalism Logo Contest: $500 1st Prize

“The neuron pattern in a child’s brain is regulated by the electromagnetic radiation arising from the conjunction of the Sun and the specific constellation during the birth.”

That is what an educated young engineer, an astrology enthusiast from Bangalore, thinks about how stars determine human destiny. A retired gentleman supported the assertion saying, ‘science is great but it cannot explain everything. You should wait and see how many things will be proved right in future’. This was rather an amusing argument that caught my attention during a recent public sky-watch programme organized in Bangalore. Such beliefs are not uncommon. As one can witness, many people in the Silicon Valley are completely ill informed about the solar eclipse. They prefer to stay indoors during these rare but spectacular events. Take the case of the Indian Space and Research Organization(ISRO) officials. Evidently, special prayers are offered before launching any important payload into space. Following the streak, many insiders would not even hesitate to attribute the astounding success of the latest moon-mission, Chandrayaan-1, to the divine vindication of human entreaties. Apparently, invoking divine blessings and performing deity pooja is a routine practice not just at ISRO, but in many public establishments in India. An oft-repeated, self-gratifying explanation goes like this:

‘Great scientists including Newton and others were deeply religious. . . there are things that we don’t know . . . life is full of uncertainties… and so on’.

Of course, there are things that we do not know, just as there are places in the universe that we can never hope to visit. Given the limitations of human intellect, it is likely that many things will remain beyond the realm of our knowledge. In his celebrated book, The History of Western Philosophy, Bertrand Russell has rightly observed, ‘Uncertainty in the presence of vivid hopes and fears, is painful, but must be endured if we wish to live without the support of comforting fairy tales’. No one disputes the abounding uncertainties and the lurking fear of the unknown in everyday life. But surrendering at the altar of ignorance does not enlighten us either. Neither has it eased the burden of the unknown – an unsavory parcel of our evolutionary history. On the contrary, giving sanctity to superstitions only appends the layers of ignorance. It does so by compromising the core principle of rationality and critical thinking that has thus far driven the progress of modern science.

Unfortunately, those who know better are sometimes directly complicit in perpetuating menacing falsehoods of every kind. Instead of challenging dogmatic beliefs on rational grounds, educated people (including scientists and technocrats) become prone to mindless justifications for the prevailing superstitions. This is a great disservice to a society that is so precariously gripped by an unrelenting past on the one hand and burgeoning modernity on the other. The appalling reliance on technology and society’s collective descent into the abyss of supernatural beliefs is a poignant outcome of the tainted compromises of the scientific community. Apart from serving media goodies loaded with ‘irrational exuberance’, should not our scientific and technological achievements also be showcased as a means to gradually dispel the dogmatic beliefs and superstitious practices from society?

The whole purpose of critical inquiry and skepticism is not to abandon our beliefs but to question our reasons for holding on to them, no matter how enchanting or reassuring they may appear. The lack of critical and independent thinking, for example, makes people extremely vulnerable, compelling them to seek guidance and personal cure from sources that are not always benign and authentic. At another level, irrational faith can become a breeding ground for collective indoctrination, forcing absolute compliance to supremacist authority of one kind or another. The renewed upsurge in public craze for high-profile godmen and the increasing prominence of soothsayers and cult-like figures in the public sphere is, therefore, not too surprising. What is more lamentable is the fact that the obligation to spread scientific outlook and critical thinking has not found its rightful place in our public outreach and educational programmes.

On the question of scientific awareness and rationality, it seems, a majority of Indian scientists do not have a unified and unambiguous stand. Isaac Newton, arguably the most outstanding scientist of all time, spent over three-fourths of his time thinking about religious matters and scriptural writings. Despite devoting so much energy to these studies, he did not accomplish anything worthwhile that could even remotely match his scientific brilliance. It is not to suggest that Newton disregarded science in favour of his religious beliefs. Newton, no doubt, was smarter than many ordinarily accomplished, but he misled himself into belief that the laws of nature are the manifestations of a ‘divine plan’ and it is necessary to satisfy the ‘divine creator’ in order to discover them. His occult studies comprising chronology of ancient kingdoms, astrology and interpretation of Biblical apocalyptic, by today’s standard are plainly unscientific. In retrospect, one can only imagine how much farther Newton would have seen had he not been distracted from his scientific pursuit, though it is important to remember that Newton lived in times when the Church was still strong and science was just in its infancy. There were no clear and established standards demarcating the practice of science from pseudoscience. Most importantly, Newton today is known for the impact of his scientific work on our lives and certainly not for his religious musings and metaphysical digressions. Trajectories of the modern space flights are not revealed in prayers or in some private communication with an individual’s benevolent god, but meticulously computed from the orbital mechanics derived from Newton’s laws of motion and gravitation. No amount of worship, wishful thinking or animal sacrifice can fix the glitch in a combustion chamber or repair faulty coolant lines serving the radiator. In fact attributing success to higher powers and seeking divine interventions grossly undermine the capabilities and achievements of human ingenuity. The proven success of the moon mission was due to the efforts of dedicated individuals and the state-of-the-art engineering design based solely on the known laws of physics. Newton’s scientific work was an immense contribution to humanity. It would be a befitting tribute to the man, if posterity does not fall trap to the obscurantist and weird notions that had also beguiled Newton.

RAVINDER KUMAR BANYAL

Indian Institute of Astrophysics

Bangalore 560 034

Related posts:

1. Yukti 2011, a Workshop to Promote Scientific Temper
2. A Defense of Non-Profit Activism in the Rationalism Movement.
3. Naturalism: Scientific, Philosophical and Socio-Political.
4. A Scientific View of the God Delusion and it’s Implications
5. Annual “Best Scientific Outlook Award” Ceremony And Rationalist Program

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This is part-II of the Philosophy With Selvi series. Part-I is here. This series is written for children of ages 10 – 14 years.

When Saturday arrived, mother and daughter took Puli to the park and tossed around a stick for him to fetch. Selvi loved the weekends because she got to spend more time playing with Puli and talking to Sandanam. Today, Selvi was her usual inquisitive self and the fresh air provoked deep thoughts.

“Ma”, she said as she watched Puli dash after the stick. “You told me the other day about justification of knowledge. Tell me more about how that works. “

Sandanam, was not entirely unprepared since she had spent the past few nights thinking about how she should deal with her daughter’s intense curiosity. But there was no simple formula. Perhaps Selvi needed formal training… someone who could teach her properly what she wanted to understand…

“OK, let’s start at the beginning” Sandanam began. “Justification of knowledge involves making arguments and dismissing or accepting them. The formal study of this process is called Logic”.

“Is common-sense the same thing as logic?”

“Depending on the definition, common-sense can be described during conversation as a type of logic. But it is not a formal system of logic. It is not comprised of a formal set of rules for evaluating arguments.”

Puli was racing back with the stick in his mouth. On reaching the two women he spun around them and circled back with Selvi laughing wildly, chasing after him.

Sandanam resumed her mental monologue. She’s just a little girl, she thought. Shouldn’t Selvi be worrying about things girls her age are concerned about?… But then again, why should she?.. Indeed, why should any girl only care about clothes, or movies …

Puli let Selvi catch up with him and grab hold of one end of the stick around which he still had his jaws clamped firmly shut. He dug in and would not let Selvi pry it from his mouth. An impromptu game of tug-o-war ensued. Selvi yelled at Puli to let go, which he did promptly, sending her somersaulting backwards on the grass. Puli came over immediately and licked Selvi’s face as she sat up. The look of surprise on her face turned to amusement. When Puli saw Selvi smile he jumped back, tail wagging, concern for Selvi abated and his undivided attention directed once again at the inexplicably fascinating object Selvi was holding in front of him. Selvi stood up on her feet, wound back, and threw the stick as far as she could. Then she turned back to her mother with an expression that said “Go on, then!”

Sandanam had made up her mind. She was going to present Selvi with a historical account of logic. She began to talk.

“There are three classical philosophical traditions of formal logic- the Greek, the Chinese and the Indian traditions. The Greek tradition influenced the thinkers of the enlightenment, which led to the development of the modern scientific tradition.”

She paused. Selvi was looking at the ground, standing with her weight almost all on her left foot. Sandanam knew a question was on its way, but she pressed on.

The study of logic in India began at about the same time as the Greeks in Europe. Broadly speaking, there were 5 schools of Indian logical thinking, each influencing the others over the centuries. (1) The oldest school of Indian logic dealt with Grammar, which influenced all of Indian philosophy because of the predominance of the Sanskrit language in philosophical discussion in ancient India. One of the earliest influential Sanskrit grammarians was Panini who lived in the 4th century BCE. (2) Vaisesika was a form of natural philosophy that viewed the world as composed of atoms. It is considered one of the six orthodox schools in the Astika tradition of Indian philosophy. Its proponents built a system of categories, and devised syllogism and methods of inference, to inform their epistemology. These syllogisms and methods of inference were developed further within the subsequent schools of Indian logic. The logical categories created by the proponents of the Vaisesika school of thought formed the foundations of the old Nyaya school of logic. (3) Formally recognized as the orthodox logical tradition in Astika philosophy, old Nyaya is often simply referred to as Vedic logic. Proponents of the old Nyaya school of logic assimilated elements of Vaisesika logic and further developed formal systematic analyses of perception and inference. However, old Nyaya and Vaisesika were doomed from the start because of their deference to Vedic authority as infallible truth. Many proponents of the old Nyaya school wasted their efforts developing complicated but flawed arguments for the existence of god. (4) Buddhist logic was partly a reaction against the old Nyaya school. In Buddhist logic we begin to see a formal logic that is distinct from epistemological and ontological concerns, and almost completely dependent on syllogism and inference. Buddhist logic strongly influenced Chinese logic. (5) Navya-Nyaya (New Nyaya) was the final phase of classical Indian logic. It began in the 13th century fueled by the work of Gangesopadhyàya. It further refined concepts from the old Nyaya tradition. The Navya-Nyaya school has produced many thinkers over the last few centuries and their influence is felt to the present day.

The Chinese tradition of logic was started by a contemporary of Confucius (6th century BCE) called Mozi. The Mohist school, as it was called, approached inference with a preference for analogy rather than deduction or induction. A separate school known as the Logicians were the intellectual descendants of the Mohists during the oppressive Warring States Period in Chinese history. After the Mohist school fell out of favor following the Qin dynasty, Buddhist philosophy introduced from India became highly influential. Buddhist philosophy was responsible for reviving the logical tradition in China.

In the Greek tradition, although there was little formal logic before Aristotle in the 3rd century BCE, there existed a great many philosophers who were involved in logical study of the world. The Greeks were the first to use geometry, starting with Pythagoras in the 6th century BCE. Later philosophers like Zeno of Elea and Euclid started what is known as the dialectic tradition in philosophy, which involved resolving arguments through discussion governed by rules of reasoning. These philosophers, many of whom were contemporaries of Plato, established what is known as the Stoic tradition in Greek logic, which contributed many important ideas to the development of the Western tradition of logic. Plato laid the ground-work for Aristotle, who established the most comprehensive system of formal logic in the Greek tradition. In fact, Aristotle is known as the founder of formal logic in the Western tradition. His work on categories and syllogism had a major impact on Western philosophy, and continued to be critiqued and further developed throughout the Roman, Christian and Islamic periods. The influence of Aristotelian ideas in Europe and the Middle East contributed to the development of modern science, as 15th and 16th century enlightenment philosophers, from Francis Bacon to Descartes and Kant, developed the foundations of scientific philosophy through the debate between, and subsequent synthesis of, the schools of rationalist and empiricist logic.

“There are many commonalities between the Eastern and Western schools of logic, such as when dealing with the sources of knowledge, known as ‘Pramanas’ in Indian logic.”

Selvi was at bursting point. But she tempered her eagerness and simply asked “OK, so what are these sources of knowledge?”

Sandanam smiled. She sensed her daughter was filing away her questions for later.

“Most logic traditions agree on two very general sources of knowledge (or pramanas)- perception and inference. Do you know what perception is?”

“Yes. Seeing or hearing something..right?”

“Right. It’s the process of collecting information about the world using our sense organs”.

“OK. What is inference?”

“Inference is the process of following logical arguments and drawing logical conclusions. We all make inferences all the time. As an example consider these statements:

• When there is smoke, there is fire.
• There is smoke now.
• There is fire now.

Using premises and observations we infer logical conclusions. The above statements follow from each other and together form what is known as a ‘syllogism’.”

Selvi was beginning to understand what logic really meant, but there were more questions now than before. She looked at Puli who had made friends with a toddler playing over by the trees. At that moment Puli turned his head to look at her. He stopped prancing around when their eyes met.

Puli stood there, head turned to the side looking at Selvi in the distance. He saw her turn back to her mom, deep in conversation. The toddler let out a squeal and charged him, causing Puli to break pose and jump away, playfully daring the kid to come chasing after him.

“So, inference is important in all schools of logic” Selvi asked.

“Yes. Inference is an essential aspect of all logic systems. In the Indian tradition it was known as ‘anumāna’.”

“Are the different types of inferences also found in different schools of logic?”

Sandanam paused for a bit. There was no avoiding it now.

“Different schools of logic approached inference differently, although they had many core ideas in common. In the Greek tradition, induction and deduction were historically the most debated modes of inference. In India, Nyaya and later schools incorporated a mixed induction-deduction approach, along with other modes of inference such as analogy. The Chinese Logicians were more keen on using analogy than induction-deduction. Today we recognize many types of inferential logic.

“What type of inference is the example of fire and smoke that you used?”

“Deduction. In this method of inference you take general principles as your premises and infer specific conclusions. That is, you go from the general to the specific. Give me an example of a general statement that you believe is true in principle.”

Selvi thought for a moment and said “Crows are black”.

“Good. Now if I told you that there are three crows on that tree, what can you tell me about them?”

“Those three crows are black?”

“That, Selvi, is deductive logic! All logic in pure mathematics is deductive logic. Another important type of logic, inductive logic, is the opposite of deductive logic. In inductive logic, you go from specific observations to general principles.

Consider this syllogism:

• A dog is chasing a rabbit.
• All dogs chase rabbits.

Here we go from a specific observation to a general principle. This is the general form of induction. Both induction and deduction are essential inferential techniques in science. Philosophers often discuss each type separately because each needs to be internally consistent, but in practice both types of logical inference are used by us to form coherent ideas about the world.”

Fun Fact: In formal logic an inference might be considered valid or invalid. What constitutes a valid inference is determined by the rules of logic. An invalid inference is called a fallacy.

Selvi seemed to be deep in thought. Puli was back at her side now, and she was stroking his back with a far-away look in her eyes.

Sandanam knew exactly how to lead Selvi around the road-block.

“Imagine you’re a police officer and you’re trying to solve a crime, say, a murder. What type of logical inference would you use?” she asked.

There was a moment of silence followed by a quick intake of breath.

“Both inductive and deductive logical inferences” said Selvi looking up triumphantly.

“Exactly”, said Sandanam. She grabber Puli’s collar and slipped the leash back on. The dog looked down at the ground and his tail went limp. But when Selvi said “We’re going home, boy!”, her enthusiasm prompted him to look up at her with his heavy eyes and give his tail a little wag.

Sandanam picked up where she had left off. “There are also many newer forms of logic, some of which derive from mathematical logic and computational logic. These include interdependence-friendly logic, multimodal logic, game-theoretic semantics and linear logic. Besides, modern science has transcended and re-defined many aspects of traditional logic, and helped create new logically coherent systems.”

“Is science also a philosophy?”

Sandanam looked at her daughter and smiled.

“Science is a methodical practice born out of philosophy. Indeed, some of Aristotle’s ideas from over two millennia ago still inform the scientific method! But science in turn also informs philosophy.

“The foundational ideas behind science have evolved over the years. A good method for studying the history of the philosophy of science is to study the debates between the proponents of two general types of justifications: Rational justifications and Empirical justifications. So can you guess which of these two types of justifications are involved in the justification of science?”

Selvi looked up at mother quizzically, then her face lit up. They were both smiling as they said in unison,

“Both, rational and empirical justifications!”.

Sandanam and her daughter held eye contact for a moment longer and then simultaneously burst out laughing, with Puli joining in braking excitedly.

On the walk back from the park Sandanam made a mental note to design some special experiments for Selvi. Also, she needed a book….an instruction manual on how to raise an extremely inquisitive teenager. This conversation had brought them to science’s doorstep, and her little girl was ready to walk right in.

The sun was going down now and Selvi’s attention seemed to have moved on to other things. It stayed on those other things all the way home.

The phone was ringing as they walked in the door. Selvi ran and grabbed it, saw the number on the caller ID, exclaimed “its for me!”, ran up into her room, and shut the door as her father yelled after her from the living room warning her not to stay on the line for hours.

“Well, at least this is normal”, Sandanam reflected as she sat down at the computer and began her search.

Join us on the Forums for a game of Spot the Logical Fallacy.

Related posts:

1. Philosophy With Selvi – What Is Knowledge? (Epistemology For Beginners)
2. A Rational Approach to Understanding the Irrational Behavior of Indians
3. Is Western Philosophy Witnessing A Resurgence In Christianity?

This is Part – II of Dr. Kamath’s series on Heretics, Rebels and Revolutionaries. Read Part – I here.

Around 600 B. C., when numerous heretical philosophies were budding in the turbulent post-Vedic period of India, someone by the name of Brihaspati wrote a classic atheistic philosophical treatise known as Barhaspatya Sutras. Later on his philosophy came to be labeled as Lokayata (“pertaining to the world”) or Charvaka (“Sweet-tongued”) philosophy. Westerners labeled this philosophy as “Materialism.” Because vested interests of theistic philosophies perceived this atheistic philosophy as too dangerous, they mercilessly ridiculed it, deliberately misinterpreted it, and freely caricatured it. In his classic treatise on ancient philosophies of India titled Sarva-Darshana-Samgraha, Madhavacharya (1268 -?) sarcastically referred to this philosophy as, “Crest-gem of Nastik schools.”

The most authoritative modern textbook on Carvaka philosophy, written by Debiprasad Chattopadhyaya

There is no philosophy in the world today about which there are so few original documents, and yet on which so many eminent people have commented so much. Thanks to the marvel of the Internet, if you just Google “Charvaka” numerous excellent articles on Charvaka philosophy will pop up, which give you a lot of factual information and divergent opinions on it. Therefore, there is absolutely no point in my writing another article summing up the materials from those articles. Instead, I decided to put some flesh and blood into the skeletal information available from the semi-original sources, and humanize this philosophy, and to give it a historical context. Thus, I have invented a conversation with a Charvaka philosopher of medieval times, say 14^th century A. D., who has suddenly materialized in the twenty-first century. By means of this conversation, I hope to convey the true spirit of Charvaka philosophy to the reader.

Mr. Charvaka, what is the essence of your philosophy in life?

I have but one life to live; and therefore, if there is an object of the senses I can enjoy, or a pleasurable sensation I can experience, let me go for it today and not defer it till tomorrow, for I shall not pass this way again.

What is the basis of your Atheistic temperament?

We believe that all valid knowledge (Pramana) must be gained only by means of perception of our five senses (Pratyaksha). We do not accept knowledge gained by inference (Anumana), intuition or testimony. All these three are hotbeds of false knowledge. Therefore, we do not believe in supra-sensory stuffs such as Atman, Brahman, god, Karma, Dharma, heaven, hell, Papam (sin), Punyam (merit), Moksha, Nirvana and all other supra-sensory stuff Indian religions are made up of. Nor do we believe in various mindless rituals and practices such as Yajna, Pooja, Yoga, astrology, miracles, and the like, which were invented to gain or lose these non-existent supra-sensory entities.

How is it that your philosophy was so much hated and caricatured by theistic systems?

Opposition to the Vedas and Veda-based rituals is as old as Vedas themselves. You know that the post-Vedic period of 800-200 B. C. was one of great turmoil due to steady decadence of Brahmanism, which became obsessed with sacrificial rituals, superstitions, class system and other nonsensical stuff. We Charvakas were the only people who challenged them, “Prove your claims or just shut up.” Unlike other rebels, we did not mince words when we did so. Whenever someone challenges Brahmanic shenanigans, their response is to indulge in personal attacks against him. They portrayed us as some type of demons who were born to destroy the world. So they attacked us, distorted our philosophy and caricatured us as some freaks of nature, and even destroyed our literature.

What aspects of Brahmanism do you agree with?

Well, first of all Brahmanism of ancient India was somewhat different from Brahmanism of today. Its goals were Kama (desire), Artha (wealth), Dharma (Law) and Samsara (transmigration of soul). Today’s Brahmanism is the result of incorporation of Upanishadism and Bhagavatism, both of which were clearly designed to overthrow Brahmanism. As a result, somewhat incongruously neo-Brahmanism claims that its newfangled goals are: Kama, Artha, Dharma and Moksha (liberation from Samsara and union with godhead). Therefore, neo-Brahmanism is a bundle of contradictory ideas and doctrines, for as we will discuss later, Kama and Artha will guarantee that one will not attain Moksha.

In principle, we are in agreement with Brahmanism as far as Kama and Artha are concerned. Like Brahmins and Kshatriyas of Vedic times, we believe in ceaseless pursuit of happiness. Life is for us to enjoy it to the fullest extent. The problem was that Brahmins claimed then, and they claim even today, that one could obtain wealth (Artha) and pleasure here on earth and heaven hereafter by means of Kama-driven Yajnas and rituals (BG: 2:43; 4:12; 9:20). There is absolutely no valid proof whatsoever to this claim. To us, this was a straightforward case of scam. When we accused them of fraud, they began to hate us.

Why are you opposed to Dharma?

We are not opposed to Dharma when it stands for pure Righteousness. However, we have problem with the idea of Dharma as defined by Brahmanism. What Brahmanism loyalist call Dharma is nothing but Adharma, pure and simple. The hallmarks of Brahmanism are Varna Dharma and Jati Dharma. How can a Dharma consider some people as inherently inferior to others and condemn them to a life of servitude? The doctrine of the Gunas of Prakriti and Law of Karma, the very foundation of Brahmanism and Varna Dharma, were evil inventions of Brahmins to maintain their class superiority over everyone else, and to rule them for personal profit and security. By brainwashing people about these dogmas (BG: 3:5, 27, 33; 18: 40-45; 59-60), they practically enslaved them psychologically. Over three thousand years, millions upon millions of people suffered untold misery due to class and caste discriminations officially sponsored by Brahmanic Adharma.

A Dharma, which does not treat all people as equals; mistreats people on the basis of their skin color, race, occupation or some other feature; and which does not strive for the welfare of all people in the society, is not Dharma at all. It is Adharma. Even Upanishadists declared Brahmanism as Adharma (BG: 4:7-8) and proceeded to replace their doctrines with Upanishadic doctrines (BG: 2:39-40) of Brahman and Yoga. Even they condemned Varna Dharma by saying that Brahman was the same in all and therefore all people are equal (BG: 5: 18-19). Brahmanism pretended to embrace Upanishadism and yet kept on promoting Varna and Jati Adharmas.

So you do not believe in the Gunas of Prakriti?

We Charvakas believe in the Theory of Naturalism -Svabhava- Vada. We believe that each object in nature has its own inherent quality. For example, fire is hot; water flows; air blows, etc. This is distinct from Brahmanism’s theory of the Gunas. Now, where is the proof that three Gunas of Prakriti exist in reality? This is nothing but a figment of imagination. There is no proof to the fact that certain groups of people share a specific Guna. If the doctrine of the Gunas were true, how come so many “lower class people” allegedly of Tamasic Guna are more “Sattvic” than many “high class” Brahmins of Sattvic Guna? If the Gunas determine the quality of all actions, how come so many “lower class” people perform such great and honorable deeds? To be candid about it, Brahmins even stole our Svabhava-vada idea to justify Guna-based class distinction (BG: 18: 41-44, 47). After declaring that the classes were divided as per unequal distribution of the Gunas and Karma (BG: 4:13), they declared that their deeds were based on their respective Svabhava!

Why do you reject Law of Karma?

Old Brahmanism claimed that one is born again in another body after one dies. They called this cycle of birth, death and rebirth Samsara. They claimed that one’s enjoyment or suffering in this life was determined by their deeds in their previous lives. Where is the proof for all this nonsense? We believe that the body is made up of four base elements: earth, fire, water and air, and consciousness arises from these elements no different than alcohol arising from a mixture of grain, hops and yeast. When we die consciousness also dies with it, and these elements go back to their original forms.

To profit from this concept of Samsara, Brahmins conceived a place out there in the sky, which they called heaven. They brainwashed people into believing that if they followed Brahmanic dictates faithfully and performed expensive and elaborate sacrifices to please gods, they would go to heaven after death. If they did not follow Brahmanic dictates, they would suffer dishonor here on earth and go to hell hereafter. This was a classic reward-punishment tactic to control people and profit from it. So the hoax of Law of Karma not only served the purpose of keeping the “lower classes” subjugated, but also was a source of income to Brahmins. Brahmanism primarily operated from inside this Samsara box.

Why do you reject Moksha?

The brief answer is this: Since there is no valid evidence (Pramana) to either Samsara or Moksha, we rejected them both. Now let me explain. Moksha was a Bhagavata concept, specifically conceived to overthrow Brahmanism. This is an example of creating one fraud to tackle another. Moksha (liberation) has basically two meanings. The first meaning is liberation from Samsara followed by one’s Atman merging with Parameshwara, residing in the Abode of Parameshwara (Supreme God) located somewhere out there in the sky. No one knows where this Abode is. This Abode was offered to replace heaven, the Abode of various Vedic gods. The difference between these two abodes is that, the ticket to heaven is two-way and the ticket to Abode of Parameshwara is one way (BG: 9:20-28).

The second meaning of Moksha is liberation from the evil of Brahmanism. Bhagavatas declared that Krishna was the Dharma himself (BG: 14:27); and by taking refuge in him, one could transcend the force of the Gunas (BG: 7:14); and by offering fruits of one’s deeds to him one could overcome the Law of Karma (BG: 9:28). Thus, by overcoming these two Brahmanic doctrines, one would conquer the three evils emanating from these doctrines: Shokam (grief), Dwandwam (mental agony) and Karmaphalam (Samsara). In fact, Bhagavatas repeatedly claimed that one could never attain Moksha by means of the Vedas, Yajnas, Tapas or Brahmanic rituals (BG: 11:48, 53). Yet, Brahmins fraudulently claimed that Vedic sacrifices led to Moksha (BG: 17: 25). Such is the duplicity of neo-Brahmanism.

What is your opinion of Yajna?

If one truly believed that he could send meat to gods in heaven by sacrificing animals in the fire, why can’t one jump into the fire so he could reach heaven immediately? Where is the proof that heaven exists? The truth is, it is by deluding people with the idea of appeasing supernatural beings with sacrificial rites and other senseless rituals that Brahmins make their living. They like to make their living by easy means. They know that they are hoodwinking naive people with their ever-scheming minds. They claim that the Vedas are sacred. What makes them so sacred? Ancient priests churned out these Vedas for purposes that are little understood and long gone. These priests hang on to every word in them not knowing their real intent or meaning. They have absolutely no relevance to current times, and they serve no useful purpose except to fill the stomach of Brahmins.

Why do Upanishadists condemn you?

Upanishadists’ main goal was to dismantle Brahmanism by developing a new set of doctrines. They came up with the doctrine of Brahman/Atman to replace the Brahmanic doctrine of the Gunas of Prakriti. They put forth the practice of Yoga to replace the ritual of Yajna (BG: 4: 33). The problem is that they too tackled one fraud by creating another. As you know, they created the “all-pervading” Brahman, which was beyond the perception of the senses (“not this, not this”) without realizing the long-term consequences of their creation. Then they said that a small portion of Brahman resides in one’s heart as Atman. If you cleave open the heart of man, you can’t find this Atman there. How can an entity exist and not be perceived by the senses? When questioned by doubters, their patent answer was, “Have Faith!”

It might surprise you to know that just as we agreed with Brahmanism’s goal of Kama and Artha, we agreed with Upanishadists’ goal to dismantle Brahmanism. However, that is where we parted ways with them. We do not believe in Atman as the “life force” which is the source of our consciousness or knowledge. We believe that consciousness arises from the chemical interaction between the four components that make up the body: earth, fire, wind and water. When the body dies consciousness also dies. Even the great Upanishadic sage Yajnavalkya admitted this in one of his moments of befuddlement (Brih. Up: 2:4:12):

“Thus verily, O Maitreyi, does this Being, endless, unlimited, consisting of nothing but knowledge, rise from out of these elements, and vanish again in them. When he has departed, there is no more knowledge, I say, O Maitreyi!”

Besides, we reject Upanishadists’ claim that since enjoying sense objects is the womb of pain (BG: 5:22) one should quit enjoying sense objects. Just because one risks getting hurt does not mean he should refrain from enjoying life. Every action of ours comes with a pain-pleasure warning label. Just because you risk getting into an accident, you do not give up driving a car. Just because all medicines are potentially poisonous, you do not refrain from using them. Just because a chainsaw is potentially dangerous, you do not avoid using it. While pursuing pleasure one should be smart enough to avoid pain, or deal with it, if and when it appears. That is no reason to avoid enjoying life. Besides, pain is essential to stimulate growth of intellect.

Upanishadists are a bunch of hypocrites. I tell you why. When king Janaka tempted Yajnavalkya (Brih. Up: 4:1:1), “For what object did you come, wishing for cattle, or for subtle questions?” the greedy sage replied, “For both, Your Majesty!” This was the same man who told his wife Maitreyi (Brih. Up: 2:4:2), “But there is no hope of immortality by wealth.”

Because of our rejection of Atman/Brahman, they have condemned our philosophy as false knowledge created by Brihaspati to delude demons: Maitrayani Up: 7: 9:

“Brihaspati, having become Sukra, brought forth that false knowledge for the safety of Indra and for the destruction of the Asuras. By it they show that good is evil and evil is good. They say that we ought to ponder on the new law, which upsets the Veda and other sacred books. Therefore, let no one ponder on that false knowledge. It is wrong. It is, as it were, barren. Its reward lasts only as long as the pleasure lasts, as with one who has fallen from his caste. Let that false science not be attempted.”

Now you tell me, which of the two is false knowledge? Upanishadists claim that Brahman/Atman, which is “not this, not this” because it is beyond the senses, is Real, and all material things we perceive by means of the five senses is Unreal, or just Maya (illusion). We say exactly the opposite. To the skeptics like us who question their claims they say, “You should have Faith in the testimony of great sages that they have intuitively attained Atman through Yoga; and one could infer validity of this claim by looking at their glowing faces.” Forgetting that the original purpose of creating Brahman/Atman and Yoga were simply to overthrow Brahmanic doctrines of the Gunas and Karma, these ignorant “sages” have made these doctrines an end in themselves. Now Yoga is a multibillion-rupee/dollar business in the world.

What beef do Bhagavatas have with you?

When Brihaspati in his Sutras spelled out Charvaka philosophy around 600 B. C., the word Nastik meant, “One who does not believe in the Vedic Dharma.” It did not mean, “One who does not believe in god.” The concept of god, as we know it today or even in the Bhagavata sect, was born much later. There was no great god for us not to believe in when Brihaspati wrote his Sutras. However, since we did not believe in the concept of supernatural, Bhagavatas branded us as Atheists, meaning those who do not believe in god. As you know, Bhagavatas came much later than the Upanishadists. Their only goal was to dismantle Brahmanism from top to bottom. However, being rabidly theistic, they demonized us atheists and condemned us to no end! Look what they had to say about us:

BG: 16: 7-11: The demoniac know not what to do and what to refrain from; neither purity nor right conduct nor truth is found in them. They say, “the universe is unreal, without a moral basis, without a God, born of mutual union, brought about by lust; what else?” Holding this view, these ruined souls of small intellect, of fierce deeds, rise as the enemies of the world for its destruction. Filled with insatiable desires (Kama), full of hypocrisy, pride and arrogance, holding evil ideas through delusion, they work with impure resolve. Beset with immense cares ending only with death, regarding gratification of lust as the highest, and feeling sure that that is all (there is to life).

As you know, Barhaspatya Sutras disappeared from circulation altogether. Either Charvakas were too busy in their pursuit of pleasure to save and promote their own treatise, or Brahmins destroyed them as too dangerous for the society. That is why all original information we have about Charvaka philosophy comes to us from condemning articles written by our sworn enemies. You can imagine how reliable they might be as evidenced by the above shlokas!

What is your view about means (Pramana) of gaining valid knowledge?

Well, we believe that knowledge gained only by direct perception (Pratyaksha) by means of five senses is true knowledge. You can say that we were probably one of the earliest scientists in India. We do not ordinarily believe in inference (Anumana), intuition or testimony. As we discussed before, this is exactly opposite of what Upanishadists believe in. We are not entirely opposed to inference. For example, if my bedroom were filled with smoke while I was asleep, I would immediately run for a safe exit to save my life inferring that my house was on fire. I would not be foolish enough to verify if there was actually a fire in the house. What we object to is inferring that there is a supernatural power or an object based on such claims as, “We performed a Yajna and it rained the next day. So god of rain obliged us.” Or, “Baba produced ashes by the wave of his hand.” In our view, people who fall for this kind of fraud are plain stupid.

How do you address the accusation that Charvakas are devoid of moral principles?

To the uninformed, the idea of enjoying life appears to be narcissistic and devoid of morals. This is not true. Just because there is no literature available of our philosophy does not mean we did not have morals in our philosophy. We do not believe in hurting anyone else in the pursuit of our happiness. However, we do not make a ‘great production’ of our morals, and use morality as a method of declaring our superiority over others. We do not believe in pronouncing Satyamaeva Jayate, Naanritham (Only Truth Will Prevail, Not Untruth), and indulge in deceptive practices with a straight face. With us, what you see is what you get. One does not need a religion or gods to be a good, moral and decent person.

We believe that enjoying life to the fullest extent does not necessitate one to be greedy or dishonest. In fact, when one is liberated from the shackles of fear of evil, and dependence on gods and rituals for fulfillment of one’s desires, one is free to enjoy life to the fullest extent. We believe that a man must work hard and honestly to earn his money and enjoy his life. Now let me ask you: How moral are holier-than-thou Brahmins who fleece innocent people of their life-savings by making false promises to them about gaining wealth here on earth and heaven hereafter? How moral are Brahmins who extort money from people in distress promising to ward off unknown evil by means of mindless rituals? We disapprove of the ways by which priests delude people to make their living. When we question this fundamental modus operandi of Brahmanism, they get bent out of shape because their very livelihood is threatened. No matter how you slice it, the ultimate purpose of religion and gods is just this: To fill one’s stomach.

Mr. Charvaka, you have given us core values of your philosophy. Thank you very much. Is there anything I can do for you?

Well, I am hungry! Is there a good steakhouse around here where I can have a couple of drinks and good steak dinner? By the way, may I borrow a couple of bucks from you?

I knew then that this was, indeed, a genuine Charvaka!

Continue the discussion on Dr. Kamath’s ‘A Manifesto For New Charvaka Movement’ posted on our forums here. Read Dr. Kamath’s series on The Truth About The Bhagavad Gita here.

Dr. Prabhakar Kamath, is a psychiatrist currently practicing in the U.S. He is the author of Servants, Not Masters: A Guide for Consumer Activists in India (1987) and Is Your Balloon About Pop?: Owner’s Manual for the Stressed Mind.

Related posts:

1. The Rebels Who Challenged The Law Of Karma
2. Heretics, Rebels, Reformers And Revolutionaries – Introduction
3. ‘Freedom Of Speech’ in India- Case Studies: Islamist Zakir Naik, Maoist Rebels, Film Actress Kushboo, Artist M.F. Hussain

NOTE: The comic strip below scrolls from right to left when you click on the right end of the strip. If you cannot see it, please try refreshing your browser.

This is the first part in a series of introductory level articles on Philosophy for Freethinkers. The second one can be found here. This series is written for children of ages 14 and below.

The question caught Sandanam by surprise. Without giving it much thought, she pointed at the trees through the window of the living room they were sitting in and said “It’s how the universe talks to us. We have to listen hard to make sense of it”.

The house was situated on the grounds of a small park. Sandanam has just finished her evening ritual of watching the sun set over the trees, before settling down in front of the television.

Now she was looking at her daughter who was standing in front of her. Selvi had questions for her mother- questions that were not very clear to her, and yet seemed somehow profound and central to her purpose. These questions came to her at every turn. This time she was struck when she was doing her math homework. Her little head was filled with a deep desire to understand how the rules of mathematics related to reality. After talking about it to her dog, Puli, for an hour, she had worked her way down to some really fundamental questions. She tried to give form to her ideas, but the words fell short. Now, standing in front of her mother, she cleared her throat and began again.

“Ma, how do we know these things… I mean, how do we know that anything is true at all?… I mean—”

“OK, let’s look at this.”, her mother interrupted. She was starting to realize that metaphors would not be sufficient to satisfy Selvi this time. The girl was thinking.

“What do you mean when you say the word ‘know’?”, Sandanam asked her daughter.

The girl frowned.

Sandanam continued, “It is good to first make sure that we both understand what we mean by ‘knowledge’ before we go any further. Knowledge has three parts. The first part is belief. The second part is truth. The third part is the way in which we connect belief with the truth. This part is called justification.” She paused for a few seconds and said,

“Do you believe that horses exist?”

“Yes” said Selvi stoutly.

“Is it true that horses exist?”

“Yes”

“Do you know that horses exist?”

“Yes”

How do you know that horses exist?

Selvi’s lips curved mischievously as she looked at her mother and she giggled. She quickly composed herself when she realized her mother was being serious.

“Because … I have seen them…I just told you its true that horses exist and you didn’t object to that”, she smiled.

Sandanam smiled back at her daughter. “Okay, then let’s try to understand how you think about ‘truth’”, she said. “Is ‘truth’ the same thing as ‘knowledge’?”

“No. Something can be true without me knowing about it”. Selvi smiled, realizing how her mother had led her to the answer.

Puli, the dog, stretched his legs lazily on the floor and turned his head at Selvi. She look at him, then cocked her head until it was at the same angle as Puli’s head.

Sandanam urged Selvi on, saying “So, ‘knowledge’ is not related to ‘truth’?”

Epistemology: Image from http://relationary.wordpress.com

Selvi thought about this as she stared into Puli’s face, then turned to look back at her mother. She crossed her feet and swung her hands to and fro. Then she said, “Knowledge needs truth and it needs me to be the knower”.

“Very good!”, said Sandanam. “Knowledge requires both the truth as well as a person to know that truth. This person can be called an ‘observer‘. For something to be true, it must exist even when there is no observer. Then the thing can be said to be true “objectively”.” She pointed at the TV and said, “Do you see that TV screen?”.

“Yes”, said Selvi.

“Okay. Imagine you are the only person who can see it. Everyone else sees a vase where you see the TV. In a situation like that, it would be difficult to say that you ‘know’ that the TV exists ‘objectively’. Fortunately for us, the universe acts in certain predictable ways that we can use to construct and justify informed beliefs. In reality, we both see the TV. The TV exists ‘objectively’, because we can confirm that it would continue to exist in this living room if you and I walk into the kitchen.”

“Is that justification?”, asked Selvi.

“One kind of justification, yes.” Sandanam paused. She took a deep breath, then said:

“In regular conversation we often justify actions rather than beliefs. This is a different type of justification from the one we are interested in. For example, I can justify picking oranges over apples at the market by simply stating that I don’t want apples; by pointing out that I am not obligated to pick apples. However, this form of justification cannot apply when we are dealing with true belief and knowledge. I cannot say that I know something because I am not obligated to believe that it is wrong. To overcome this, philosophers have come up with various rules that can be applied to make the idea of justification more accurate when we are talking about knowledge.

When you want to confirm that something is true, you must first look for the evidence (more here). Also, you must ask how reliable is the source of the evidence obtained (more here). Based on the type of justification, knowledge can be internalist or externalist. To put it in a simple form, internalist justifications consider that complete knowledge is possible from within an internally consistent framework, often by studying observations born out of sensory experience. This form of justification includes some schools of thought such as Rationalism.  Externalist justifications take into account the relationship of an event with objects and events outside the sphere of the event (often outside subjective reality). This form of justification accommodates the notion of causality, which we spoke about earlier.”

A few seconds passed with neither of them saying anything. Puli was resting his head on his paws, taking a nap. On the TV, a famous charlatan was talking about quantum mysticism. Outside, the crickets chirped loudly, their mating calls echoing off the buildings on the street across from the park. Selvi decided that the steady chirping made more sense than the man on the TV.

Another thought came to Selvi.

“The evidence… isn’t evidence also a belief?”, she asked her mother.

“Yes”, said Sandanam. “Each and every observation that is claimed as evidence requires justification and belief. This brings us to another aspect of justification, called the structure of justification. How do all the beliefs that we hold relate to each other? And how do those relationships between beliefs create knowledge? These are just some of the questions that are asked and answered within the discipline of philosophy called ‘Epistemology’“

Puli was snoring softly. On the TV, a man was talking about the earthquake in California. He was announcing a special guest on the show; the man named Deepak Chopra, the one who distorts quantum physics to suit his own mystical interpretation of reality, all the while seeking the legitimacy of the scientific enterprise. This time, Chopra claimed to have caused the recent earthquake by the power of his meditation. On the show he was going to talk about how the energy flow from his chakras was consciously guiding the universe to do his will, but the skeptics with their negative energy were inducing power fluctuations in his meditation field, causing unfortunate accidents like the recent earthquake.

Selvi began placing playing cards face down on the floor. She announced to her mother that she had invented a game. For every unjustified knowledge claim that Chopra made, she would turn over one card after first trying to guess what it was by counting the open cards and calculating the odds. Sandanam tried hard to keep a straight face as she turned up the volume. The chirping of crickets faded into the background as the calm, soothing voice of blissful unreason filled the room.

Related posts:

1. Philosophy With Selvi #2 – Understanding Logic
2. Is Western Philosophy Witnessing A Resurgence In Christianity?

The complete series, Complexity Explained by Dr. Vinod Wadhawan, can be accessed here.

In this concluding part of the series on complexity I recapitulate the basic ideas about complexity, and then revisit the questions about the origin of the universe we live in, the origin of life, and the origin of consciousness. The bottom line is that the word ‘origin’ should be replaced by ‘evolution.’ And what evolves with time is complexity, resulting in the emergence of new properties or phenomena which could not have been anticipated.

17.1 Recapitulation of the Main Ideas in Complexity Science

With reductionism comes the conviction that a court proceeding to try a man for murder is “really” nothing but the movement of atoms, electrons, and other particles in space, quantum and classical events, and ultimately to be explained by, say, string theory.

Stuart Kauffman (2006)

1. Classical microscopic laws of physics are characterized by determinism and time-reversal symmetry. Determinism means that if the position and the momentum of a particle are known at any instant of time, then the laws of classical mechanics determine the position and momentum at all instants of time, both future and past. The success of space missions is an example of the applicability of the deterministic equations of motion to simple (or simplifiable) systems (in contrast to complex systems). Simple systems have the linearity feature: The inevitable imprecision in our knowledge of the physical parameters of such a system does not lead to disastrous or runaway consequences in our predictions about the mechanics of the system.
2. By contrast, chaotic systems, though deterministic, are governed by nonlinear equations of motion, and consequently we cannot predict their behaviour far into the future. Chaos is an example of the fact that determinism does not necessarily imply predictability.
3. The familiar second law of thermodynamics is a striking example of emergence in complex systems. The laws of mechanics (classical or quantum) applicable to any microscopic particle comprising a macroscopic system are time-symmetric; but the macroscopic system has the emergent property of time-asymmetry, embodied in the fact that the entropy of the system cannot decease with the passage of time.
4. In the macroscopic world, we associate the direction of increasing entropy with the direction of increasing time. Entropy is a measure of disorder, and negative entropy or negentropy is a measure of information.
5. The emergence feature of complex systems makes the reductionistic approach to understanding complex natural phenomena quite inapplicable. But that does not mean that we should swing to the other extreme and adopt only a holistic approach. It is important to understand the distinction between chaotic, random, and complex systems. In a chaotic system there is determinism without predictability. Order and disorder coexist in a complex system. And randomness means a complete lack of structure or order (‘algorithmic irreducibility’). I shall be addressing these issues in a forthcoming book.
6. Complex systems have a hierarchical structure of complexity. The structure at one level leads to the next level of complexity, and each level of complexity often results in the emergence of new laws.
7. The new laws do not violate any of the laws operating at the lower levels of complexity. There is no question of ‘downward causality’ because, deep down under, everything interacts with everything else and we only have interactions, rather than actions and reactions (or causes and effects).
8. Physical laws, though always valid, are not always convenient or relevant for explaining, say, the chemical behaviour of a system. Similarly, biology is not always conveniently understood in terms of the laws of chemistry or physics alone. Nevertheless, if we consider only neighbouring or contiguous levels of hierarchical complexity, a reductionistic or constructionistic approach can often be useful.
9. Flow of energy through an open thermodynamic system can take the system so far away from equilibrium that there is a bifurcation in phase space, resulting in self-organization. Such bifurcations can occur repeatedly in a complex system, and there is no way to predict as to which branch of a bifurcation will be chosen, because the choice depends on random fluctuations at the moment of the bifurcation. This fact lies at the heart of (unpredictable) emergence of novel features during the time-evolution of a complex system.
10. Simple local rules can lead to the emergence of complex overall patterns, behaviour, or properties. This is how swarm intelligence emerges.
11. The flow of energy through a complex system results in a build up of the information content of the system. A state of complete order, as also a state of complete randomness, has low information content and a low degree of complexity. The more interesting complex systems usually fall in-between these two extremes.
12. Complexity thrives best at the ‘edge’ between order and disorder. Complex adaptive systems tend to self-organize so as to inch towards this so-called ‘edge of chaos.’
13. Per Bak’s notion of self-organized criticality provided important insights into how and why complex systems move to a state at or near the edge of chaos.
14. Positive feedback is an important mechanism of how self-organization can occur. However, it is not the only possible mechanism for this. Often, chain reactions achieve something similar. And negative feedback provides the necessary antidote for maintaining a state of optimal balance and perpetual novelty.

17.2 How did the Universe Emerge out of ‘Nothing’?

Everything existing in the universe is the fruit of chance and necessity.

Diogenes Laertius IX

This is the toughest of the three questions I revisit in this article. I wrote about cosmic evolution in Part 7 of this series, but want to make up here for some important omissions.

What happened immediately before the Big Bang? The answer to this question is important for understanding some observations in astronomy. How can energy be created out of nothing, and how is it continuing to increase as the universe expands? I quoted Seth Lloyd (2006) in Part 7: ‘Quantum mechanics describes energy in terms of quantum fields, a kind of underlying fabric of the universe, whose weave makes up the elementary particles – photons, electrons, quarks. The energy we see around us, then – in the form of Earth, stars, light, heat – was drawn out of the underlying quantum fields by the expansion of our universe. Gravity is an attractive force that pulls things together. . . As the universe expands (which it continues to do), gravity sucks energy out of the quantum fields. The energy in the quantum fields is almost always positive, and this positive energy is exactly balanced by the negative energy of gravitational attraction. As the expansion proceeds, more and more positive energy becomes available, in the form of matter and light – compensated for by the negative energy in the attractive force of the gravitational field.’

Apart from quantum-mechanical effects and the gravitational interaction, other dominant factors in the early stages were the immensely high temperatures and pressures. In the beginning it was all radiation, and no matter. And the energy content and the information content were very small. The energy content and the information content built up as the universe expanded and extracted more and more energy out of the underlying quantum fabric of space and time.

According to the current theories, the energy grew very rapidly in the beginning (by a process called inflation), and the amount of information grew less rapidly. Immediately after the Big Bang there was a hot plasma of elementary particles, which expanded and cooled very quickly. In fact, the first structures got formed within a fraction of a second after the explosion. Protons and neutrons were formed from quarks.

One minute after the Big Bang, helium nuclei were formed. Soon, a full 24% of all matter was in the form of helium nuclei. Radiation interacts primarily with ions (rather than atoms).A few tens of thousand of years after the Big Bang, the first electrically neutral matter was formed, when protons and electrons combined to form atoms of hydrogen. This marked the separation of electrically neutral matter from radiation. On further cooling, gravitational effects became more and more important, as electrically neutral atoms could now clump together because of gravitational attraction. This clumping went on to produce galaxies ultimately.

There are gaps in our understanding of how structure arose out of what was a structureless field of radiation in the beginning. In particular, we do not yet know whether there are forms of matter other than what we already know. Even as early as in the 1930s, it was known that gravitational effects in large galactic clusters are much higher than what can be expected from the known amount of matter there. Apparently, there is another, unknown, form of matter that is a full 90% of all matter, as indicated indirectly by the gravitational effects. It is called dark matter because we are unable to observe it; we infer its existence only through its gravitational effects.

Perhaps neutrinos have something to do with this dark matter. Or perhaps some still undiscovered elementary particles, including some very heavy (but unobserved) ones, may be involved. These particles might have got formed in the very hot conditions soon after the Big Bang.

The reasons for the occurrence of the Big Bang are still a puzzle. Another puzzle in modern cosmology is the fact that matter and the cosmic background radiation are distributed quite homogeneously throughout the observable universe. Consider a galaxy that is 5000 million light years away today from our galaxy, namely the Milky Way. When the universe was, say, just one million years old, it (the universe) was only a thousandth of its present size. Therefore at that time the two galaxies must have been 5 million years apart. But since the age of the universe at that time was only one million years, not enough time was available for the two galaxies to have exchanged signals of any kind (assuming that nothing travels faster than the speed of light). There could not have been any kind of communication between the contents of one galaxy and the other. So how did the homogenization of the shock waves associated with the Big Bang occur?

There is general agreement that the emergence of matter from the early radiation field was a kind of symmetry-breaking phase transition. This can be likened to the phase transition from liquid water (which is homogeneous, or translation-invariant) to ice (which is not translation-invariant). The radiation field was translation-invariant, and the appearance of matter broke this translational symmetry. A hypothetical field called the Higgs field has been introduced in cosmology to understand these phenomena. This field breaks the symmetries of the interactions among the elementary particles, and gives the particles their mass.

The Higgs-field theory predicts the existence of a cosmological constant. Such a constant was indeed introduced much earlier by Einstein, and then withdrawn because it amounted to introducing into his theory of gravitation a parameter ‘by hand,’ with no theoretical justification. Einstein’s cosmological constant was intended to provide the repulsive force needed to compensate for the attractive force of long-distance gravity. In other words, if gravity could be switched off, Einstein’s cosmological constant would result in a rapid inflation of the universe. But once it was known that the universe is expanding, it became unnecessary to try to counterbalance the attractive gravitational force.

The Higgs field results in the existence of a new cosmological constant, which turns ‘empty’ space into a space that has an energy content. The problem at present is that the predicted cosmological constant has too large a value for a correct understanding of the observed cosmic evolution. It is believed that perhaps the Higgs cosmological constant had a large value right after the Big Bang, resulting in a violent and very rapid expansion (or inflation) of the universe. At a certain stage of this inflation, a cosmic phase transition occurred, which freed enormous amounts of energy (rather like the release of latent heat when steam condenses to liquid water). In a way, this energy flash or Big Bang marked the actual birth of our cosmos. After this prelude of inflation and cosmic phase transition, the normal (much slower) expansion of the universe set in, and has continued ever since.

During the inflation prelude, the universe grew extremely rapidly from a volume smaller than that of the nucleus of an atom to the size of a tennis ball. If we associate the Big Bang with the moment at the end of the (very quick) inflation episode, certain cosmological mysteries get resolved. When the universe was just the size of a tennis ball, regions that are far apart today could have been in contact then, thus resulting in the observed homogenization of the universe.

This new model of the Big Bang (i.e. a phase transition after the inflation prelude) answers a few additional perplexing questions as well. The model implies that the observable cosmos is a part of a much bigger system. Our Big Bang occurred in a certain region of the cosmos, leaving other regions untouched. More Big Bangs can keep occurring in other regions of the cosmos, opening up the possibility of parallel universes. There is thus a multiverse, rather than a universe.

In a multiverse, Big Bangs occur repeatedly, and each resulting universe has values of fundamental constants that just happen to be what they are. The universe we live in happens to have values of fundamental constants that make our emergence and existence possible. Otherwise we would not have emerged and evolved. This brings us to the much-maligned anthropic principle. The principle states that: The parameters and the laws of physics in our universe can be taken as fixed; it is simply that we humans have appeared in the universe to ask such questions at a time when the conditions were just right for our life. I have not included a discussion of this principle in the present series because it is covered in another article (on biocentrism) on this website, which I coauthored with Ajita Kamal.

Although there is no law saying that the degree of complexity of the universe must always increase, an empirical observation is that it is increasing, and increasing at an exponential rate. There can be some local decreases in complexity (there is even an anthropocentric angle to this issue), but the overall complexity of our universe is increasing. This has been explained in terms of the fact that our universe is expanding, and thus getting a continuous supply of free energy or negentropy (cf. Part 7).

But how long will the universe continue to expand? Did time begin? Will time end? Here are three likely answers given by the noted cosmologist Paul Frampton in a recent (2010) book:

Most likely: The present expansion will end after a finite amount of time, the universe will contract, bounce and repeat the cycle. In this cyclic universe, time had no beginning, and will have no end.

Next most likely: The present expansion will end after a finite time in a Big Rip. Time began in the Big Bang some 13.7 billion years ago, and will end some trillion years in the future.

Least likely: The present expansion will continue for an infinite time. Time began 13.7 billion years ago, and will never end. In his book Prof. Frampton challenges this prevailing ‘conventional wisdom.’

17.3 How did Life Emerge out of No-Life?

It was discovered that RNA molecules can not only carry genetic information, but act as enzymes, speeding chemical reactions. Work is underway to create an RNA enzyme, or ribozyme, that can copy any RNA molecule including itself. The probability that an RNA molecule can catalyze a given reaction is roughly 10 divided by 10 raised to the 15th power. It is conceivable that such a molecule can arise by chance, but it faces the difficulty that were it to copy itself and make errors, those error copies would be more error prone than the initial copy, and a run away error catastrophe might ensue.

Stuart Kauffman (2006)

As discussed in Part 10, it is not easy to define life. One consequence of this situation is that life must have emerged very very gradually. Thus it is meaningless to try to identify a point of time which marked the ‘origin’ of life on Earth. As discussed in Parts 8, 9, and 12, a whole lot of chemical evolution of complexity preceded the emergence of what we intuitively understand as life.

I discussed only two models of the likely origins of life in Part 12. For a more comprehensive description, please see the 2006 online article by Stuart Kauffman.

I described Kauffman’s work on autocatalytic sets of molecules in Part 9, and his RBNs (random Boolean networks) in Part 12. He has been emphasizing the importance of the self-organization feature of complex systems in the evolution of biological complexity. He uses the phrase ‘order for free‘ for this non-Darwinian evolution of complexity:

“While it may sound as if ‘order for free’ is a serious challenge to Darwinian evolution, it’s not so much that I want to challenge Darwinism and say that Darwin was wrong. I don’t think he was wrong at all. I have no doubt that natural selection is an overriding, brilliant idea and a major force in evolution, but there are parts of it that Darwin couldn’t have gotten right. One is that if there is order for free – if you have complex systems with powerfully ordered properties – you have to ask a question that evolutionary theories have never asked: Granting that selection is operating all the time, how do we build a theory that combines self-organization of complex systems – that is, this order for free – and natural selection? There’s no body of theory in science that does this. There’s nothing in physics that does this, because there’s no natural selection in physics – there’s self organization. Biology hasn’t done it, because although we have a theory of selection, we’ve never married it to ideas of self-organization. One thing we have to do is broaden evolutionary theory to describe what happens when selection acts on systems that already have robust self-organizing properties. This body of theory simply does not exist.” (Chapter 20, “Order for Free”, The Third Culture, 1995).

Kauffman’s work brings out the inevitability of the emergence of life. The prevailing conditions were such that life just had to appear because of the relentless evolution of complexity. A knowledgeable alien would be very surprised if life had not emerged here. Thus, the ‘origin’ of life is the easiest of the three questions I am revisiting in this article. There is nothing miraculous or supernatural about the origin of life.

17.4 How does Consciousness Arise?

Meanwhile, my approximate theory is that mind is acausal, quantum mechanics is acausal on the familiar Born interpretation of the Schrödinger equation, (to the grief of Einstein), that consciousness is due to a special state where a system is persistently poised between quantum and classical behaviour, that the emergence of classical behaviour in the mind-brain system, perhaps by decoherence, is the “mind making something actual” happen in the physical world, and – big jump – that consciousness itself consists in this quantum coherent state as lived by the organism. This is a long jump, but not impossible. I don’t even think it is stupider than other theories of consciousness, and may be true. Whatever the case, consciousness is ontologically emergent in this universe.

Stuart Kauffman (2006)

The problem with the word ‘consciousness’ is that it is what Marvin Minsky calls a ‘suitcase word.’ It stands for a whole set of processes. Naturally, it is difficult to discuss it in a scientific manner. From the complexity perspective, consciousness arises from swarm intelligence, the swarm here being that of neurons. In a large swarm, local rules can lead to astonishingly complex behaviour and novel phenomena and sensations.

The self-referential nature of consciousness is what makes it look so puzzling. But the fact is that, long ago (in 1931), Kurt Gödel shook the foundations of mathematics by proving that even such an innocuous thing as the formal system of positive integers can have self-referential properties. Self-reference and formal rules can make systems acquire meaning, despite the fact that each constituent of the system in without meaning.

Nevertheless, there are difficulties galore:

‘All the limitative theorems of metamathematics and the theory of computation suggest that once the ability to represent your own structure has reached a certain critical point, that is the kiss of death: it guarantees that you can never represent yourself totally. Gödel’s Incompleteness Theorem, Church’s Undecidability Theorem, Turing’s Halting Theorem, Tarski’s Truth Theorem — all have the flavour of some ancient fairy tale which warns you that “To seek self-knowledge is to embark on a journey which … will always be incomplete, cannot be charted on any map, will never halt, cannot be described.”‘ (Douglas Hofstadter 1979)

The debate on consciousness is not likely to end anytime soon.

17.5 Acknowledgements

The idea of writing this series of articles was suggested by Mr. Ajita Kamal, Editor of Nirmukta. Ajita has been of great help throughout, and made several useful suggestions.

My Ph. D. student Indranil Bhaumik was immensely helpful by sending me several important books in pdf format.

Ms. Malgorzata Koraszewska took the trouble of translating these articles into Polish and publishing them at www.racjonalista.pl. She has done a thorough job indeed, consulting experts when in doubt about the exact Polish equivalent of a technical word in English. The Polish versions of these articles were discussed in a much more lively way than the originals in English. Unfortunately I could not take part there because of the language barrier, but was happy to answer some questions forwarded to me by Malgorzata.

I not only enjoyed writing these articles, it was also a great learning experience for me because of the comments and questions posted on nirmukta.com, as also on richarddawkins.net and some other websites which picked up some of these articles. I also received a lot of feedback from scientists-friends through private emails.

I shall feel amply rewarded for the time and effort I have put into the writing of these articles if I have succeeded in inducing even a few of the readers to shun all kinds of irrational belief systems.

Science is rational. Science is fun. Science has both a humbling and a liberating influence on those who have imbibed the spirit of the scientific method. The skepticism inherent in the scientific method, and its emphasis on making only falsifiable statements, are essential tools for acquiring knowledge we can trust with a high degree of confidence.

Nature is highly creative, and this creativity comes from the relentless evolution of complexity. A flower is a piece of art, and complexity science tells us how this ‘natural art’ can arise (emerge) without the need for the existence of the artist or the creator.

Dr. Vinod Kumar Wadhawan is a Raja Ramanna Fellow at the Bhabha Atomic Research Centre, Mumbai and an Associate Editor of the journal PHASE TRANSITIONS. All parts of Dr. Wadhawan’s series on Complexity Explained can be found here.

Related posts:

1. COMPLEXITY EXPLAINED: 3. Thermodynamic Explanation for the Increasing Complexity of our Ecosphere
2. COMPLEXITY EXPLAINED: 6. Emergence of Complexity in Far-from-Equilibrium Systems
3. COMPLEXITY EXPLAINED: 14. Biological Complexity at the Edge of Chaos
4. COMPLEXITY EXPLAINED: 7. Cosmic Evolution of Complexity
5. COMPLEXITY EXPLAINED: 5. Defining Different Types of Complexity
6. COMPLEXITY EXPLAINED: 15. Evolution of Cultural Complexity

The human brain is a physical organ, governed by the laws of physics. The mind is ‘brain power,’ or the capacity of the brain to feel, think, and reason. The brain carries the mind, as well as what we often call consciousness (although we cannot tell where exactly in the brain is the so-called consciousness located). Our intelligence may be no different from ‘swarm intelligence,’ the swarm here being that of neurons. There is a belief that the transition from intelligence to consciousness needs the acquisition of a human language. The ‘society of mind’ (comprising of ‘communities’ of large numbers of interacting neurons) emerged as a hierarchical structure, so typical of any complex adaptive system. Consciousness is an emergent phenomenon.

16.1 Evolution of the Mammalian Brain

Any living entity exploits the existing structure and order of its surroundings to ensure its survival and reproduction. Consider a single-celled organism in a pond. On its surface are molecules which can ‘detect’ (are influenced by) the presence of nutrients. There is usually a gradient of the nutrient concentration, so that it is higher on one side of the organism than on the other. The single-celled organism has chemical sensors which can detect this gradient. Biological evolution has programmed it to propel itself in the direction of increasing concentration of nutrient. An attribute of intelligence is the problem-solving capacity of the system; other important attributes are prediction and memory capabilities. As Hawkins (2004) points out, both prediction and memory are involved here. The prediction is that, by moving in the direction of increasing concentration of nutrient, more nutrient will be found. This is not something the organism has ‘learnt’ and ‘remembered’ in its lifetime. The memory, evolved over many generations of evolution, is in its DNA.

To cut a long evolutionary story short, let us jump from bacteria to plants. Plants also exploit the existing order and structure (constancy or sameness over reasonably long time scales) by employing memory and prediction. The memory in the genes of a tree tells it that it will find greater sunshine by sending its branches and leaves towards the sky. And that it will find water and minerals by sending its roots down into the soil. These actions are automatic, and there is no ‘thinking’ involved, just as there is no thinking involved in the actions of a bacterium.

At a certain stage in the evolutionary history of plants, more complex behaviour emerged in the form of communication systems among the various parts of a plant, based mainly on chemical signals. Suppose an insect damaged some part of a tree, and this led to the slow transmittal of a chemical through the vascular system to its other parts. This triggered a defence mechanism; e.g. the making of a toxin for the insect.

It is conceivable that neurons evolved in due course, as a faster way of communicating information to different parts of an organism. The electrochemical spikes in a neuron travel much faster than the diffusion of chemicals. In due course, the ‘synaptic’ connections between neurons became modifiable. A neuron may or may not send a signal, depending on what happened in the past. This rudimentary nervous system had elements of both memory and learning.

The evolutionary advantage of this to the animal was qualitatively different. Instead of depending on just ‘genetic memory’ and instinct coded in DNA, the animal could now learn from experience during its own lifetime, and modify its behaviour for achieving better survival and propagation rates. In particular, if the environmental structure and order changed rather suddenly, the animal could still make a generally adequate response, instead of having to depend only on the somewhat outdated (and therefore inadequate) genetic memory and instinct. Such plastic nervous systems entailed a huge evolutionary advantage, and there was a burst of new species from fish to snails to mammals, including humans.

Why is it that intelligence evolved mainly in the animal kingdom, but not in the plant kingdom? As explained by the noted robotist Hans Moravec, the difference has arisen because animals are mobile and plants are generally not. The mobility of animals presents to them an ever-changing environment, and therefore intelligence is an important prerequisite for survival and propagation: An animal can survive only if it has a large repertoire of solutions to the continuous stream of problems it faces in a changing environment.

The human brain, like the brain of any other mammal, has something distinctly additional compared to the brain of reptiles from which it evolved, namely the neocortex. Thus the human brain has two main parts: the ‘old brain’ or the reptilian brain or the R-brain or the ‘primitive’ brain, and the neocortex.

Practically everything we associate with conscious memory and intelligence occurs in the neocortex, although the thalamus and the hippocampus also play important roles. In the evolutionary history of life on Earth, sophisticated sensory and actuation organs had evolved in reptiles, and their behaviour was controlled by the old brain, with no cortex. The evolution of the cortex in one of the offshoots of the reptiles, along with the availability of a stream of sensory inputs into it which it could remember and analyse much better than reptiles could, gave the mammals an evolutionary advantage: When they found themselves in situations they remembered to have faced earlier, their much-improved memory and analysis power told them what to expect next, and how to respond effectively.

16.2 The Human Brain

The human brain, along with the spinal chord, comprises the central nervous system. The top outer portion of the brain, just under the scalp, is the neocortex (or cortex for short). It covers most of the R-brain, and has a crumpled appearance, with many ridges and valleys. The R-brain is rather similar in reptiles and mammals, and has a number of parts, including the thalamus and the hippocampus.

Humans are special compared to other mammals because of their very prominent prefrontal cortex (or frontal lobe).The prefrontal cortex (particularly the upper two-thirds of it, including the dorsolateral prefrontal cortex) can be regarded as the rational centre of the brain; or the rational brain. The rest of the human brain is the emotional brain.

The human cortex, if stretched flat, is the size of a large napkin, and about 2 mm thick. It has six layers, each roughly the thickness of a playing card. There is a branching hierarchy among the layers. Layer 6 is at the bottom of the hierarchy, and Layer1 is at the top. The inputs from the various sensory organs are received in Layer 6, and then interpreted and correlated. Then more and more abstract and generalized versions of the information are sent up the hierarchical layers. There is a very high degree of feedback and feedforward among the layers, as also cross-correlations.

Image credit: K. Svoboda, as reproduced in the book Biological Physics: Energy, Information, Life, by Philip Nelson (2008). The image shows the dendritic tree of a neuron which receives more than 100,000 synaptic inputs, which are integrated by the neuron to create a single output signal.

There are ~10¹¹ nerve cells or neurons in the human cortex. Most of them have a pyramidal shaped central body or nucleus, as well as an axon, and a number of branching structures called dendrites. We can think of the axon as a signal emitter, and the dendrites as signal receivers. When a strand of an axon of one neuron (the presynaptic neuron) ‘touches’ a dendrite of another neuron (the postsynaptic neuron), a connection called a synapse is established. A typical axon is involved in several thousand synapses.

Portions of the cortex can be identified as different functional areas or regions. For example, a portion of the frontal lobe (see illustration) is the motor cortex. It controls movement and other actuator functions of the body.

The cortical tissue can be functionally divided into vertical units or columns. Neurons within a column respond in a similar manner to external signals with a particular attribute.

When a sensory or other pulse (‘spike’) involving a particular synapse arrives at the axon, it causes the synaptic vesicles in the presynaptic neuron to release chemicals called neurotransmitters into the gap or synaptic cleft between the axon of the first neuron and the dendrite of the second. These chemicals bind to the receptors on the dendrite, triggering a brief local depolarization of the membrane of the postsynaptic cell. This is described as a firing of the synapse by the presynaptic neuron.

If a synapse is made to fire repeatedly at high frequency, it becomes more sensitive; i.e. subsequent signals make it undergo greater voltage swings or spikes. Building up of memories amounts to formation and strengthening of synapses.

The firing of neurons follows two general rules: (1) Neurons which fire together wire together. Connections between neurons firing together in response to the same signal get strengthened. (2) Winner-takes-all inhibition. When several neighbouring neurons respond to the same input signal, the strongest or the ‘winner’ neuron will inhibit the neighbours from responding to the same signal in future. This makes these neighbouring neurons free to respond to other types of input signals.

The functionality of the cortex is arranged in a branching hierarchy. The primary sensory regions constitute the lowest rung of the hierarchy (Layer 6). The sensory region for, say, vision (called V1) is different from that for hearing etc. V1 feeds information to higher layers called V2, V4 and IT, and to some other regions. The higher they are in the hierarchy, the more abstract they become. V2, V4 etc. are concerned with more specialized or abstract aspects of vision. The higher echelons of the functional region responsible for vision have the visual memories of all sorts of objects. Similarly for other sensory perceptions.

In the higher echelons are areas called association areas. They receive inputs from several functional regions. For example, signals from both vision and audition reach one such association area.

Although the primary sensor mechanism for, for example, vision is not the same as for hearing, what reaches the brain at higher levels of the hierarchy is qualitatively the same. The axons carry neural signals or spikes which are partly chemical and partly electrical, but their nature is independent of whether the primary input signal was visual or auditory or tactile. Finally, they are just patterns.

16.3 Creation of Short-Term and Long-Term Memories

Creation of short-term memory in the brain amounts to a stimulation of the relevant synapses, which is enough to temporarily strengthen or sensitize them to subsequent signals.

This strengthening of the synapses becomes permanent in the case of long-term memory. This involves the activation of genes in the nuclei of postsynaptic neurons, initiating the production of proteins in them. Thus learning requires the synthesis of proteins in the brain within minutes of the training. Otherwise the memory is lost.

Information meant to become the higher-level or generalized memory, called declarative memory, passes through the hippocampus, before reaching the cortex. The hippocampus is like the principal server on a computer network. It plays a crucial role in consolidating long-term memories and emotions by integrating information coming from sensory inputs with information already stored in the brain.

16.4 The Prefrontal Cortex and its ‘Working Memory’

What sorts of ‘rules’ could possibly capture all of what we think of as intelligent behaviour however? Certainly there must be rules on all sorts of different levels. There must be many ‘just plain’ rules. There must be ‘metarules’ to modify the ‘just plain’ rules; then ‘metametarules’ to modify the metarules, and so on. The flexibility of intelligence comes from the enormous number of different rules, and levels of rules. The reason that so many rules on so many different levels must exist is that in life, a creature is faced with millions of situations of completely different types. In some situations, there are stereotyped responses which require ‘just plain’ rules. Some situations are mixtures of stereotyped situations – thus they require rules for deciding which of the ‘just plain’ rules to apply. Some situations cannot be classified – thus there must exist rules for inventing new rules … and on and on. Without doubt, Strange Loops involving rules that change themselves, directly or indirectly, are at the core of intelligence. Sometimes the complexity of our minds seems so overwhelming that one feels that there can be no solution to the problem of understanding intelligence – that it is wrong to think that rules of any sort govern a creature’s behaviour, even if one takes ‘rule’ in the multilevel sense described above.

Douglas Hofstadter, Gödel, Escher, Bach

We cannot make decisions without involving emotions. This conclusion of modern psychology goes against the grain of what was believed to be the case about the nature of rational behaviour for most of the 20^th century. The conventional picture has been that at the bottom of the hierarchical complexity of the human brain is the brain stem, which controls bodily functions like heartbeat, breathing, and body temperature. At the next higher level is the diencephalon, which regulates hunger pangs and sleep cycles etc. Then comes the limbic region, which generates and controls emotions (violence, lust, impulsive behaviour, etc.). These three levels of brain complexity are common to all mammals, including humans. Lastly there is the prefrontal cortex, predominantly responsible for our reasoning power and intelligence etc. Although it enables us to suppress emotions to a small or large extent, it is wrong to think that this ‘rationality’ portion of our brain can completely overpower or overrule what the three hierarchically lower parts of the brain tend to do. In other words, it is impossible for us to make decisions which are completely dispassionate or ‘reasoned.’

It is also true that a substantial portion of the prefrontal cortex is involved in our emotional behaviour. How do we ‘manage’ our emotions? We do so by thinking about them, and the thinking is done mainly by the prefrontal cortex. The term metacognition is used for the capacity of our prefrontal cortex to contemplate about our own mind. The frontal cortex knows when we are, say, angry. In fact, every emotional state comes with self-awareness attached to it. This enables us to figure out or ‘think’ why we are feeling the way we are feeling. Thus we humans are able to exercise a certain degree of control over our emotions by what is commonly called ‘rational thinking.’ This is also how we make decisions. The emotional brain is constantly sending out signals about its likes and dislikes. The prefrontal cortex monitors these emotional outputs and tries to decide which signals to take seriously and which ones to overrule. Although the rational brain cannot silence emotions, it can help figure out which ones should be followed. A highly readable account of the role of intuition and emotions in our decision-making process has been given in a recent (2009) book How We Decide by Jonah Lehrer.

Unlike other regions (columns) of the cortex, which specialize in processing specific types of stimuli, the cells of the prefrontal cortex can process whatever kind of data they need to process. This enables our brain to look at a given problem from a variety of vantage points, and even come out with creative solutions. How does the prefrontal cortex accomplish this? The answer has to do with its special kind of memory called the working memory. It is a short-term memory, but it has a persistence feature. It is a meeting ground, and also a melting pot, of information from various sources. Neurons in this part of the brain fire in response to a stimulus, and then keep on firing for several seconds after the stimulus has disappeared. This allows the brain to make creative associations. This is the so-called restructuring phase of problem-solving: Here information is mixed together in new ways and overlapping of ideas occurs, leading to new insights. The resultant novel neural wiring enables you to identify the answers you were looking for. This is an important feature of human intelligence.

The emotional brain is very important too

Excessively rational thinking can backfire, because it often amounts to suppressing what the primitive brain is trying to tell us. This problem arises because the rational brain is not an infinitely powerful supercomputer, meaning that rational analysis cannot always provide the best solution to a complicated problem. The cumulative wisdom buried in the (much larger) primitive brain must also be used.

The psychologist George Miller demonstrated in his essay ‘The Magical Number Seven, Plus or Minus Two’ that the conscious brain can only handle about seven pieces of data at any one moment. The computational circuitry of the rational part of our brain is only a tiny fraction of the total capacity of the brain, ‘just a few microchips within the vast mainframe of the mind.’ As a result, too many choices, or too much data, can overwhelm the prefrontal cortex, leading to bad decisions. The trick lies in learning when to trust your intuitions more than your reasoning power. ‘Because working memory and rationality share a common cortical source — the prefrontal cortex — a mind trying to remember lots of information is less able to exert control over its impulses. The substrate of reason is so limited that a few extra digits can become an extreme handicap’ (Lehrer 2009). The fact of life is that the rational part of our brain (which is really a very recent novelty on the evolutionary time scale) has a rather slow and small, even erratic, CPU. Too much information can interfere with understanding. When the prefrontal cortex is overwhelmed, correlation is confused with causation, and people tend to make theories out of coincidences.

Excessive dependence on the emotional brain can be risky too. The ideal situation is that exemplified by, say, a champion chess player. Through an unhurried analysis of the games he won or lost, he builds up experience (turning mistakes into educational events) which gets ‘internalised’ into his emotional brain. In due course, it becomes ‘second nature’ for him to make the right moves, not having to consciously analyse the consequences of too large a number of prospective moves. The emotional brain is a huge supercomputer, with massive parallel-processing capabilities.

16.5 Marvin Minsky’s ‘Society of Mind’

Our minds did not evolve to serve as instruments for observing themselves, but for solving such practical problems as nutrition, defence, and reproduction

Marvin Minsky (2006)

Marvin Minsky is a pioneer of the field of machine intelligence. Efforts at developing machine intelligence have resulted in deep insights into how the human brain functions.

In 1986 Minsky published his book The Society of Mind, in which he formulated his ideas about human cognition. His next book, The Emotion Machine, published in 2006, reflects the progress made in gaining insights into the workings of the human mind via the machine-intelligence approach.

Minsky’s ‘society’ of mind comprises of ‘agents’ or ‘resources,’ which are the simplest individuals that populate the brain. Each agent or resource can be visualized as a typical component of a computer program, like a simple subroutine or data structure. The agents can get connected and composed into larger systems called agencies or societies of agents. The agencies self-organize into still larger conglomerates that can perform still more complex functions, and so on into still higher and higher levels of self-organization and complexity, ultimately leading to the emergence of abilities we attribute to minds. There is a hierarchical structure and organization, like in any complex adaptive system.

The idea of hierarchical levels of organization was well documented in an earlier publication of Minsky (1980): One could say but little about “mental states” if one imagined the Mind to be a single, unitary thing. But if we envision a mind (or brain) as composed of many partially autonomous “agents”-a “Society” of smaller minds-then we can interpret “mental state” and “partial mental state” in terms of subsets of the states of the parts of the mind. To develop this idea, we will imagine first that this Mental Society works much like any human administrative organization. On the largest scale are gross “Divisions” that specialize in such areas as sensory processing, language, long-range planning, and so forth. Within each Division are multitudes of subspecialists-call them “agents”-that embody smaller elements of an individual’s knowledge, skills, and methods. No single one of these little agents knows very much by itself, but each recognizes certain configurations of a few associates and responds by altering its state.

As is the case with any complex adaptive system, we cannot predict with certainty the properties of the mind-system in terms of the laws of physics applied to the constituent agents, nor can we start from the observed complexity of the brain and work our way downwards all the way to understand why the increasing complexity took a particular route in phase space. To quote Minsky (1990): ‘The functions performed by the brain are the products of the work of thousands of different, specialized sub-systems, the intricate product of hundreds of millions of years of biological evolution. We cannot hope to understand such an organization by emulating the techniques of those particle physicists who search for the simplest possible unifying conceptions. Constructing a mind is simply a different kind of problem-of how to synthesize organizational systems that can support a large enough diversity of different schemes, yet enable them to work together to exploit one another’s abilities.’

Here is Minsky’s (1986) take on consciousness: ‘In this book, the word (consciousness) is used mainly for the myth that human minds are “self aware” in the sense of perceiving what happens inside themselves. I maintain that human consciousness can never represent what is occurring at the present moment, but only a little of the recent past – partly because each agency has a limited capacity to represent what happened recently and partly because it takes time for agencies to communicate with one another. Consciousness is peculiarly hard to describe because each attempt to examine temporary memories distorts the very records it is trying to inspect.’

Minsky describes ‘free will’ as a myth, the myth that human volition is based upon some third alternative to either causality or chance.

The ‘Single-Self’ concept

Some of us subscribe to the concept that there is creature (or a set of creatures) inside us that does all the feeling or thinking for us, and makes all the important decisions for us. It is our ‘identity’ or ‘self.’ Even our legal system distinguishes between deliberate wilful murder, and murder that was not pre-planned. This Single-Self concept may be useful, but has no scientific basis.

Why do humans entertain such fiction? It may be partly because it makes life look pleasant, ‘by hiding from us how much we’re controlled by all sorts of conflicting, unconscious goals.’ According to Minsky, ‘That image makes us efficient, whereas better ideas might slow us down. It would take too long for our hardworking minds to understand everything all the time. However, although the Single-Self concept has practical uses, it does not help us to understand ourselves-because it does not provide us with smaller parts we could use to build theories of what we are. When you think of yourself as a single thing, this gives you no clues about issues like these: What determines the subjects I think about? How do I choose what next to do? How can I solve this difficult problem? Instead, the Single-Self concept offers only useless answers like these: My Self selects what to think about. My Self decides what I should do next. I should try to make my Self get to work.’ He goes on to say that: ‘Whenever you think about your “Self” you are switching among a huge network of models, each of which tries to represent some particular aspects of your mind-to answer some questions about yourself.’

16.6 Daniel Dennett’s Model of Consciousness

Dennett’s 1994 book Consciousness Explained has been hailed as a major milestone in understanding the nature of consciousness. Both he and Minsky give due respect to what people say about their feelings and emotions and other internal subjective experiences, but only as evidence of how things appear to them to be, rather than as direct evidence of ‘things as they actually are.’ Dennett calls this the heterophenomenological approach.

Dennett has formulated his so-called multiple drafts model of consciousness. A point emphasized by both Dennett and Minsky is that mental processes are spread over both space and time. Consider the analogy of the preparation and publication of a book. The manuscript undergoes a number of draftings and distributions among the author, the referees, and the editor, and is thus spread over both space and time before it is ultimately finalized. The multiple drafts of the book are also a reality. Ditto with what we perceive as consciousness: There are multiple drafts, and only one may get chosen in a given situation.

Dennett emphasizes that it is only an illusion that a person is conscious of what is perceived as ‘now.’ Processes in the brain occur at millisecond (and not infinite) speeds, and many of them occur simultaneously. Therefore it is impossible to carry out a sequential timing or ordering of events in the brain at and below the millisecond time scale. There is no objective ‘now’ for a person’s brain; there can be only a subjective ‘now’ which depends on the choice made by the brain from among the recent events and processes occurring in it.

In other words, there is no central or single place in the brain (the so-called Cartesian Theatre) where everything is presented together (to Minsky’s ‘single agent’), and decisions are made. Dennett presents evidence for this model from a vast range of experiments in cognitive psychology and neuroscience, as well as from ideas from evolutionary biology.

He not only rejects the notion of a Cartesian Theatre in the brain, but also those of qualia and homunculus. The term ‘qualia’ refers to the mistaken notion that feelings associated with sensation are somehow independent of sensory input. And homunculus is the name used for the now-discredited unproductive and paradoxical idea of a small agent or intelligent thing or experiencing subject, located deep inside a person’s head, determining or controlling his behaviour.

Dennett also rejects the philosophy of Cartesian Dualism, according to which consciousness (a subjective experience) belongs to a different plane of reality than the one on which the material universe is constructed. Consciousness arises from the processes of information exchange in the brain. Multiple sets of sensory information, memories and emotional cues are competing with each other at all times in the brain, but at any particular instant only one set of these factors dominates the brain. At the next instant, another set of slightly different factors are dominant. At all instants, multiple sets of information are competing with each other for dominance. This creates the illusion of a continuous stream of thoughts, leading to the impression that consciousness is the entirety of the mental functions of the individual.

Dennett (2006) believes that acquisition of a human language is a necessary prerequisite for consciousness to emerge:

I believe, but cannot yet prove, that acquiring human language (an oral or sign language) is a necessary precondition for consciousness – in the strong sense of there being a subject, an I, a ‘something it is like something to be.’ It would follow that nonhuman animals and prelinguistic children – although they can be sensitive, alert, responsive to pain and suffering, and cognitively competent in many remarkable ways (including ways that exceed normal adult human competence) – are not really conscious, in a strong sense: There is no organized subject (yet) to be the enjoyer or sufferer, no owner of the experience as contrasted with a mere cerebral locus of effects.

16.7 Hawkins’ Model for Intelligence and Consciousness

Jeff Hawkins, in his 2004 book On Intelligence, proposed the so-called memory and prediction theory of how human intelligence arises. The basic idea of Hawkins’ theory of intelligence, in his own words, is as follows: The brain uses vast amounts of memory to create a model of the world. Everything we know and have learnt is stored in this model. The brain uses this memory-based model to make continuous predictions of future events. It is the ability to make predictions about the future that is the crux of intelligence.

Hawkins points out that the neocortical memory differs from that of a conventional computer in four ways:

1. The cortex stores sequences of patterns. For example, our memory of the alphabet is a sequence of patterns. It is not something stored or recalled in an instant, or all together. That is why we have difficulty saying it backwards. Similarly our memory of songs is an example of temporal sequences in memory.
2. The cortex recalls patterns auto-associatively. The patterns are associated with themselves. One can recall complete patterns when given only partial or distorted inputs. During each waking moment, each functional region is essentially waiting for familiar patterns or pattern-fragments to come in. Inputs to the brain link to themselves auto-associatively, filling in the present, and auto-associatively linking to what normally flows next. We call this chain of memories, thought.
3. The cortex stores patterns in an invariant form. Our brain does not remember exactly what it sees, hears, or feels; the brain remembers the important relationships in the world, independent of details.
4. The cortex stores patterns in a hierarchy.

Storing sequences, auto-associative recall, and invariant representation are the necessary ingredients for predicting the future based on memories of the past. How this happens is the subject matter of Hawkins’ book. According to him, making such predictions is the essence of intelligence.

Hawkins takes the view that perhaps consciousness is simply what it feels like to have a neocortex. He suggests that the self-awareness aspect of consciousness is synonymous with the formation of declarative memories. These are memories we can recall and talk about.

Hawkins, while formulating his theory of intelligence, was enamoured of the so-called Mountcastle’s hypothesis. Since the same types of layers, cell types and connections exist in the entire cortex, Mountcastle (1978) put forward the following hypothesis: There is a common function, a common algorithm, that is performed by all the cortical regions. What makes the various functional areas different is the way they are connected. He went further to suggest that the reason why the different functional regions look different when imaged is because of these different connections only. Hawkins suggests that, although hearing, touch, vision etc. are processed by the same algorithm in the neocortex, they are handled differently in the R-brain: ‘Hearing relies on a set of audition-specific subcortical structures that process auditory patterns before they reach the cortex. Somatosensory patterns also travel through a set of subcortical areas that are unique to somatic senses. Perhaps qualia, like emotions, are not mediated purely by the neocortex. If they are somehow bound up with subcortical parts of the brain that have unique wiring, perhaps tied to emotion centres, this might explain why we perceive them differently, even if it doesn’t explain why there is any sort of qualia sensation in the first place.’

The structure of the inputs (i.e. the spatio-temporal information pattern) is qualitatively different for, say, the auditory nerve and the optic nerve. The optic nerve has a million fibres, and the auditory nerve has only thirty thousand. The optic nerve caries information that is more spatial than temporal, and the auditory nerve carries information that is more temporal than spatial. This may have bearing on why is red red and green green. No matter how consciousness is defined, memory and prediction play crucial roles in creating it.

Here is how Hawkins answers why our thoughts appear to be independent of our bodies: ‘To the cortex our bodies are just part of the external world. Remember, the brain is in a quiet and dark box. It knows about the world only via the patterns on the sensory nerve fibres. From the brain’s perspective as a pattern device, it doesn’t know about your body any differently than it knows about the rest of the world. There isn’t a special distinction between where the body ends and the rest of the world begins. But the cortex has no ability to model the brain itself because there are no senses in the brain. Thus we can see why our thoughts appear independent of our bodies, . .’

16.8 Concluding Remarks

Consciousness is subjective and internal; perhaps a ‘virtual reality.’ In this article I have briefly discussed a few models of consciousness. The clear message is that there is nothing mystical or supernatural about consciousness. In fact, conscious superintelligent machines (robots) are likely to be a reality in the present century itself.

How did consciousness arise out of no-consciousness? It did so via the complexity-evolution route as an emergent property. Through self-organization and through cumulative natural selection, neurons emerged as a means of more efficient communication among the various parts of the brain. Interactions among neurons led to a further increase in complexity in the form of memory and prediction, and thence intelligence. From intelligence to consciousness is a difficult conceptual step because in science we have place only for testable or falsifiable statements, made in terms of symbols or words with a preassigned unambiguous meaning. But there is no agreement on what exactly we mean by the word ‘consciousness.’ There is a whole spectrum of definitions of this word.

Richard Dawkins takes the stand that, if you take a set of statements made about consciousness, and replace this word by some meaningless word like hkzisrkjd everywhere, you would have lost or gained nothing in understanding the meaning of that set of statements!

The philosopher Daniel Dennett takes consciousness very seriously. And he ends up saying that nonhuman animals and prelinguistic children are not really conscious (in the ‘strong’ sense of the word). He admits that this assertion will shock many people, but also says that ‘. . . of course, the truth of the empirical hypothesis is in any case strictly independent of its ethical implications, whatever they are.’

Marvin Minsky uses the word ‘myth’ for describing consciousness. Like any complex adaptive system, the human brain functions in a way that cannot always be understood in terms of a few simple fundamental rules or laws. To quote Marvin Minsky (2006): ‘… every brain has hundreds of parts, each of which evolved to do certain particular kinds of jobs; some of them recognize situations, others tell muscles to execute actions, others formulate goals and plans, and yet others accumulate and use enormous bodies of knowledge. And though we don’t yet know enough about how each of those brain-centres works, we do know their construction is based on information that is contained in tens of thousands of inherited genes, so that each brain-part works in a way that depends on a somewhat different set of laws.’ According to him, none of the popular psychology words like ‘feelings,’ ‘emotions,’ and ‘consciousness’ is about any single and definite process. Each such ‘suitcase word‘ vaguely refers to the effects of a large network of processes in the brain. Minsky argues that feelings are not basic at all, but are processes made of many parts. Similarly he demonstrates that ‘consciousness’ refers to more than 20 different processes (e.g. the process of reasoning and making decisions; the process of how the brain represents ‘our’ intentions; the process of how the brain knows what it has done recently; and so on).

Jeff Hawkins takes the view that ‘reality’ is largely a matter of how accurately our cortical model of the world reflects the true nature of the world.

As Douglas Hofstadter has explained in detail, consciousness emerges in a system that is powerful enough to have a sort of self-referential, self-modelling capability (‘strange loops’ is the term he uses in this context). The stage for this conclusion of his was set by Kurt Gödel’s discovery in 1931 that even things as simple as integers are powerful enough to be used for representing (at a different level) statements about themselves. Hofstadter builds on this fact to argue how conscious beings can think about and represent themselves.

. . . our intelligence is not disembodied, but is instantiated in physical objects: our brains. Their structure is due to the long process of evolution, and their operations are governed by the laws of physics. Since they are physical entities, our brains run without being told how to run.

Douglas Hofstadter, Gödel, Escher, Bach

Dr. Vinod Kumar Wadhawan is a Raja Ramanna Fellow at the Bhabha Atomic Research Centre, Mumbai and an Associate Editor of the journal PHASE TRANSITIONS

Related posts:

1. COMPLEXITY EXPLAINED: 2. Swarm Intelligence
2. COMPLEXITY EXPLAINED: 15. Evolution of Cultural Complexity
3. COMPLEXITY EXPLAINED: 7. Cosmic Evolution of Complexity
4. COMPLEXITY EXPLAINED: 8. Evolution of Chemical Complexity
5. COMPLEXITY EXPLAINED: 13. Evolution of Biological Complexity
6. COMPLEXITY EXPLAINED: 6. Emergence of Complexity in Far-from-Equilibrium Systems

Many of those of us who call ourselves freethinkers are aware that there is some fundamental difference between the way we view reality and the way the superstitious folks do. We believe in a naturalistic reality and the others subscribe to the supernatural. But what exactly is this difference? What does it mean to believe in a naturalistic reality? What is ‘natural’, and how is it different from ‘supernatural’?

Note: I will avoid discussion of the nature of evidence in this article since it will distract us from our objective here.

The key to understanding the natural universe is understanding the notion of causality. This idea can be stated simply as the relationship between two dependent events, where one is the caused and the other is the cause. Science works only because the natural world exhibits causality. In physics, causality is more accurately viewed as interaction between two events, objects or situations, with each of the two being both cause and effect at the same time.

“Everything that happens……. presupposes something upon which it follows by rule”

- Immanuel Kant, Second Analogy

Case-I

Sethu from India believes that the Hindu god Ganesha is the keeper of his fortunes. Sethu spends 5 hours every week, praying to and performing duties for Ganesha. He strongly believes that his actions have been keeping him safe and comfortable.

In his regular life, Sethu is an engineer. His job requires him to possess and frequently rely on an exceptional amount of data on cause and effect. Even when he decides to go perform his puja, he doesn’t just close his eyes and wish that he was at the temple. He gets in his car and goes through the motions, knowing that the mechanics of the automobile will be the effect. He has a naturalistic understanding of these things. Cause and effect are intuitive in this way.

Yet when Sethu gets to the temple, he stops thinking in naturalistic terms. A very different type of behavior sets in. He appeals to what can only be conceived of as magic. This is his supernaturalistic side.

What happens here is that Sethu goes from a world where causality operates, to one in which causality does not apply, and he makes this switch based on no evidence at all! At the point where he begins to seek a supernatural explanation, Sethu stops subscribing to the real and observable principles of cause and effect and starts believing in magic.

“Shallow men believe in luck, believe in circumstances. Strong men believe in cause and effect.”

Ralph W. Emerson

Case-II

Jen in the US knocks on wood to avoid tempting fate every time she boasts about herself to someone. She doesn’t really think about it past the ritualistic rap of knuckle on cedar. Her life is full of these meaningless idiosyncrasies.

But Jen is a successful businesswoman. She makes extremely rational decisions analyzing numbers all day long, to seek and identify patterns. She has an exceptional grasp of her natural surroundings, using the principles of cause and effect extremely well to navigate through life. Yet the superstitions are all right there. The early morning coffee and horoscopes, the frequent tarot card readings and psychic healing visits- all side by side with the everyday real-world things she does.

Jen finds it really easy to switch back and forth between the magical fantasy world ,where cause and effect do not apply, and the real naturalistic world where they do.

“[WHAT IS SUPERSTITION?] – To disregard the true relation between cause and effect.”

Robert G. Ingersoll, 1898

Case-III

Yalda in Morocco believes that allah is the reason she exists. In fact, allah is the reason everything exists, since he created everything. But the laws of cause and effect do not apply to allah. In fact, he created those as well.

Meanwhile, she exercises her mind everyday at her job as a computer programmer. She understands how the code she writes has an effect, which has another effect and so on. Yalda acts as we all do when it comes to practical matters, under the premise that cause and effect apply in our universe. But when it comes to allah, she suspends belief in reason. She does not stop to question the logical incoherence of claiming to know anything at all about an all-knowing being who cannot be known because he is beyond cause and effect.

“All reasonings concerning matter of fact [the empirical reality] seem to be founded on the relation of Cause and Effect.”

David Hume

In each one of these cases there are two types of behaviors- those based on naturalistic ideas and those based on supernaturalistic ones. If we extend this

The Illustrated Sutra of Cause and Effect: 8th century, Japan.

reasoning to numerous beliefs in popular culture, it becomes apparent that everywhere a supernatural concept is evoked there is a required suspension of the laws of causality. In fact, belief in any supernatural requires a voluntary surrendering of the reasonable and fundamental assumption of science that all things must have a natural cause. To the superstitious mind, magic appears to be a reasonable solution- a sufficiently explanatory state of affairs. This sort of thinking is manifested in everything from belief in homeopathic medicines and psychic healing, to belief in god.

Not only is causality key to understanding natural reality, but understanding the causal nature of reality is also important towards attaining a better idea of who we are as sentient beings. The three above case-studies all defer to an external supernatural force. However, there is another type of supernatural belief, one that is just as prevalent and harmful, but involves looking inward, into oneself. This is the belief in the idea of an internal supernatural self; a soul.

The belief in a soul is manifested in many forms in human society, most prominently in the widespread belief in “free” agency. This is the illusion of an uncaused entity within us; the seat of our consciousness and sentience. This type of uncaused “free” agency is commonly known as free-will, or more technically, contra-causal free-will.

Is it possible, or even advantageous to forgo the supernatural belief in contra-causal free-will? Will our society be able to function morally without the notion of uncaused agency? Can personal responsibility survive as a fundamentally beneficial social construct, even in the absence of free-will? The answers to these questions and others will be covered in future parts of this series on naturalistic philosophy. The next one will be on the nature of knowledge, it’s forms and its attainment (epistemology).

Enjoy this brief video that I made as a very basic introduction to the tenets of Naturalism.

Click here to view the embedded video.

Related posts:

1. Atheist/ Freethinker Meets in Pune and Mumbai
2. Naturalism: Scientific, Philosophical and Socio-Political.
3. Naturalism Logo Contest: $500 1st Prize
4. Worldview Naturalism
5. Hinduism: Religion, Culture or Way of Life?
6. COMPLEXITY EXPLAINED: 10. What is Life?

(Note: All previous parts in the Complexity Explained series by Dr. Vinod Wadhawan can be accessed through the ‘Related Posts’ listed below the article.)

Man invented language to satisfy his deep need to complain, opined Lily Tomlin. On a more serious note, the evolution of language, speech, and culture are believed to be some of the causative factors for the rapid evolution of the size and capacity of the human brain. The emergence of human language has been a major milestone in the relentless evolution of complexity on our planet, and has also played a role in the evolution of human consciousness. Apart from the emergence and evolution of language, I also discuss memetics and econophysics in this article.

15.1 Introduction

A mostly Lamarckian process whereby evolution of a transformational nature proceeds via the passage of acquired characters, cultural evolution, like the stellar evolution before it, involves no DNA chemistry and perhaps less selectivity than biological evolution. Culture enables animals to transmit survival kits to their offspring by nongenetic routes; the information gets passed on behaviourally, from brain to brain, from generation to generation, the upshot being that cultural evolution acts much faster than biological evolution.

Eric Chaisson, Cosmic Evolution

According to Richard Dawkins (1989), ‘most of what is unusual about man can be summed up in one word: “culture”.’ Of course, one must make a distinction between ‘culture’ and ‘society.’ ‘A society refers to an actual group of people and how they order their social relations. A culture . . . refers to a body of socially transmitted information’ (Barkhow 1989). The term ‘culture’ encompasses ‘all ideas, concepts and skills that are available to us in society. It includes science and mathematics, carpentry and engineering designs, literature and viticulture, systems of musical notation, advertisements and philosophical theories – in short, the collective product of human activities and thought’ (Distin 2005).

15. 2 Evolution of Language

If there had been no speech, then right and wrong, truth and falsehood, good and bad, attractive and unattractive would not have been made known. Speech makes known all this. Worship speech.

Chandogya Upanishad VII-2-1

As far as humans are concerned, language has got to be the ultimate evolutionary innovation. It is central to most of what makes us special, from consciousness, empathy and mental time travel to symbolism, spirituality to morality.

Kate Douglas

Somewhere in the last 100,000 years or so, human beings hit upon language. Human language must have seemed an odd-sounding innovation to the other animals around. But by allowing the expression of arbitrarily complicated concepts, human language allowed people to process information in a highly distributed fashion. The distributed nature of human information processing in turn allowed people to cooperate in new ways, forming groups, associations, societies, companies, and so on. Some of these new forms of cooperation proved strikingly effective, as various forms of distributed information processing, such as democracy, communism, capitalism, religion, and science, took on a life of their own, propagating themselves and evolving over time. It is the richness and complexity of our shared information processing that has brought us this far.

Seth Lloyd, Programming the Universe

It is notable that, on an evolutionary time scale, there has been an exceptionally rapid expansion of brain capacity in the course of evolution of one of the ape forms (chimpanzees?) to Homo sapiens, i.e. ourselves. This has happened in spite of the fact that the genome of humans is incredibly close to that of chimpanzees. The evolution of language, speech, and culture are believed to be some of the causative factors for this rapid evolution of the human brain. Let us see how.

Homo sapiens was preceded by Homo heidelbergensis, which also had a fairly large brain, but was not very effective as a hunter. He was not able to establish ecological dominance over other animals, even after two million years of evolution. The human advantage is believed to have arisen from the emergence of language. ‘No topic is more intriguing and more difficult to address concretely than the evolution of language, but … [it] is almost a kind of sixth sense, since it allows people to supplement their five primary senses with information drawn from the primary senses of others. Seen in this light, language becomes a kind of “knowledge sense” that promotes the construction of extraordinarily complex mental models, and language alone may have provided sufficient benefit to override the cost of brain expansion’ (Klein and Edgar 2002).

The reference to ‘the cost of brain expansion’ here is to the fact that in humans the brain takes up ~20% of the metabolic resources of the body, and the brain tissue requires 22 times more energy than a comparable piece of muscle at rest.

Deacon (1997) emphasizes the big difference between human language (talking) on one hand and the various modes of communication among other live entities: ‘Although other animals communicate with one another, at least within the same species, this communication resembles language only in a very superficial way – for example, using sounds – but none that I know of has the equivalents of such things as words, much less nouns, verbs, and sentences. Not even simple ones.’

Deacon (1997) continues: ‘Though we share the same earth with millions of living creatures, we also live in a world that no other species has access to. We inhabit a world full of abstractions , impossibilities, and paradoxes … We tell stories about our real experiences and invent stories about imagined ones, and we even make use of these stories to organize our lives. In a real sense, we live our lives in this shared virtual world. … The doorway into this virtual world was opened to us alone by the evolution of language, because language is not merely a mode of communication, it is also the outward expression of an unusual mode of thought – symbolic representation. Without symbolization the entire virtual world is … out of reach: inconceivable … symbolic thought does not come innately built in, but develops by internalising the symbolic process that underlies language.’

Homo heidelbergensis had a big brain. But was he also a great symbolic thinker? Probably not. Deacon argues that probably a single symbolic innovation triggered a coevolution of language and brain-size. Greater brain power resulted in a greater capacity to symbolise, speak, think. The cascading effect led to more complex languages and more complex brains. But all this required social interaction and support: ‘Language is a social phenomenon. … [and] … The relationship between language and people is symbiotic.’

Deacon traces the evolution of social complexity by assuming that the early humans were dual-parenting. Since their sense of smell was not very acute (thus ruling out a role for chemical signalling through pheromones), some other type of sexual signalling evolved between the male and the female. This is how social communication originated and evolved as a kind of social hormone.

Other than sex, availability of food is the major factor determining the survival of a species. Males had to cooperate with one another for hunting. Deacon again: ‘Males must hunt cooperatively; females cannot hunt because of their ongoing reproductive burdens; and yet hunted meat must get to those females least able to gain access to it directly (those with young), if it is to be a critical subsistence food. It must come from males … [who] … must maintain constant pair-bonding relationships.’

This need for hunting in groups resulted in the evolution of a social structure implying a symbolisational solution to the problem of survival. This is because symbolic reference, as also speaking and thinking, are basically of a social nature. There was naturally a concomitant evolution of the speech organ (voice box).

Grooming

According to Robin Dunbar, ‘One of the most important ways that primate allies show their affection to each other is by grooming. Grooming not only gets rid of lice and other skin parasites, but it also is soothing. Primates turn grooming into a social currency that they can use to buy the favour of other primates. But grooming takes a lot of time, and the larger the group size, the more time primates spend grooming one another. Gelada baboons, for example, live on the savannas of Ethiopia in groups that average 110, and they have to spend twenty percent of their day grooming one another. … If we had to bond our groups of 150 the way primates do, by grooming alone, we would have to spend about 40 to 45 percent of our total daytime in grooming.’

The primates in the savannas also had to find food, and therefore such a large investment of time in grooming would have caused a non-sustainable work vs. life balance. Language emerged as a better way of bonding.

Evolution of word-speaking species

Humans began with sound language, gradually increasing the vocabulary. But there is a severe limit to how many sound calls you can have which still sound distinct. The next step in the evolution of language was a stringing together of sounds into specific sequences, namely words. Word-speaking species naturally had an evolutionary advantage.

Sentences syntaxing words were the next level of evolving complexity. Brain size increased concomitantly to understand and remember words, syntax, grammar, and sentences (Zimmer 2001): ‘A syntax-free language beats out syntax when there are only a few events that have to be described. But above a certain threshold of complexity, syntax became more successful. When a lot of things are happening, and a lot of people or animals are involved, speaking in sentences wins … Something about the life of our ancestors became complex and created a demand for a complex way in which they could express themselves … A strong candidate for that complexity, as Dunbar and others have shown, was the evolving social life of hominids.’

This social evolution of complexity is the advantage humans have over other animals. They have the capacity to introduce and expand complexity in social life, and development of language is both a cause and an effect of this capacity. As Kate Douglas (2005) said, ‘In a sense, language is the last word in biological evolution. That’s because this particular evolutionary innovation allows those who possess it to move beyond the realms of the purely biological. With language, our ancestors were able to create their own environment – we now call it culture – and adapt to it without the need for genetic changes.’

Whereas humans and chimpanzees have many genes in common, the expression of certain genes is more common in the human brain. Moreover, the brains of newborn humans are far less developed than those of newborn chimpanzees, and the neural networks of human babies are developed over many years of exposure to a linguistic environment. Through a continuous process of unsupervised learning (experimentation), supervised learning (from parents, teachers, etc.), and reinforced learning (the hard-knocks of life, and rewards for certain kinds of action), the child’s brain performs evolutionary computation.

With language came the possibility of emergence of ‘memes.’ Language coevolved with memes.

15.3 Memes and Their Evolution

We are different from all other animals because we alone, at some time in our far past, became capable of widespread generalized imitation. This let loose new replicators – memes – which then began to propagate, using us as their copying machinery much as genes use the copying machinery inside cells. From then on, this one species has been designed by two replicators, not one. This is why we are different from the millions of other species on the planet. This is how we got our big brains, our language and all our other peculiar ‘surplus’ abilities.

Susan Blackmore (2000)

It is information that evolves in any type of evolution. The most basic aspects of evolution are replication of information (which involves preservation of the replicated information), and the mode of transmittal of information. Genes preserve biological information, and they use DNA for this. What about culture?

Similar to the gene, which is the unit of biological inheritance, Richard Dawkins (1989, 1998) introduced the notion of the meme, which is the unit of cultural inheritance. A meme may be some good idea, a soul-stirring tune, a logical piece of reasoning, or a great philosophical concept. Dawkins visualized that two different evolutionary processes must have operated in tandem: the classical Darwinian evolution, and another one centred round intelligence, language, and culture. Memes are, roughly speaking, the cultural analogues of genes.

The genes that exist in many copies in a population are those that are good at surviving and replicating. Through a reinforcement effect, genes in the population that are good at cooperating with one another stand a better chance of surviving. Similarly, the fittest set of cooperating memes has a better chance of surviving to form the meme pool of the population. They replicate themselves by imitation or copying (Blackmore 1999, 2000), and also by a variety of other mechanisms (Distin 2005). Cultural evolution and progress occurs through a selective propagation of the fittest set of cooperating memes.

Meme-gene coevolution

Memes evolve, just as genes evolve. In fact, any entities that can replicate, and that have a variation both in their specific features and in their reproductive success, are candidates for Darwinian selection. The coevolution of gene pools and meme pools (through language etc.) resulted in a rapid enlargement of the brain size of Homo sapiens. A large brain size, once attained, resulted in several other capabilities as well.

An important difference between memes and genes is that the speed of cultural evolution (development of ideas, customs, etc.) is far higher than the speed of genetic evolution. Nevertheless, there are several proposed analogies between the two. How far can we carry the gene analogy for understanding the nature of memes? This continues to be a subject of debate. Following Distin (2005), I list here some characteristics of memes.

The essential particulate nature of memes

The most efficient methods of replicating complexity are hierarchical (or modular or particulate). If variation were permitted in every element of a complex structure, then copying processes would lose much of their stability. In genetics, Mendel’s work established the particulateness of genes, namely the clear presence or absence of the effects of these replicators on the world. Something similar is necessary for memes in their role in cultural evolution of complexity. This means that memes must be able to fit into established cultural assemblies without their own informational content being lost or blended in the process. That is, memes must have a certain degree of particulateness, so that the results that they produce are generally of a fixed nature. Their identity should be such that they are discernible packets of information (like the genotype). But, whereas the genotype is distinct and clearly definable, the phenotype (which is a manifestation of the genotype) in biological systems possesses a certain degree of flexibility and variability. Likewise, the manifestations of memes have a certain degree of flexibility that enables their effects to be produced in a variety of cultural contexts. Copied in these ways, information is given the stability to grow and develop in complexity. The breadth and depth of human culture is thus explained by the cumulative replication of particulate information.

In both genetics and memetics, the replicators carry information about the effects that they control. In the case of genes, their independence is maintained via the medium of DNA, which preserves biological information in a form that is replicable and can produce its effects in a variety of contexts. In the case of memes, this role is performed by ‘representational content,’ which is thus the memetic or cultural equivalent of DNA.

Representational content of memes

Memes are specified by their representational content. As representations of a portion of information, memes can be regarded as having a certain content. A representation in the human mind is some piece of our ‘mental furniture’ that carries information about the world. For example, a thought that ‘the object on my desk is a book’ is a mental representation of a bit of the world (i.e. that book). Therefore ‘representational content’ refers to the information that is included in the content of our representations.

It is representational content which accounts for the mechanisms of memetic heredity and for the influence of the memes over their phenotypic effects. Distin (2005) uses the term memetic DNA for the representational content. It provides the mechanism for memetic evolution, just as DNA provides the mechanism for genetic evolution.

How is the representational content fixed in our brains?

Replicators preserve and copy specific portions of information. For memes, we should be able to identify precisely which bits are carried in each replicator. This means pinpointing the exact content of any representation, and this is something determined partly by the various properties of the object or situation being represented. Yet representational content is determined by other factors as well, e.g. by the capabilities and history of the organism doing the representing.

Some organisms are capable of forming representations the content of which is determined by a combination of the relevant properties of that which is represented, and the organism’s own individual and social learning capacities. Such organisms are able, in other words, both to preserve information and to transmit it among themselves.

In the case of complex representations, which have links not only externally to perceptions and behaviour but also internally to other representations, the resultant behavioural flexibility can enable us to track down their content more completely. It should be possible to test all of the links, by altering the associations that the organism encounters, and observing the effects on its behaviour. Only representations with this determinacy of content can count as memes, since a crucial aspect of any replicator is the preservation of given information.

Thus memes are representations which preserve their content in a way that can be copied between generations. As representations, they are specifically those bits of our mental furniture which control our behaviour in response to the information that they carry. In other words, the basis of memes in representational content is precisely what accounts for their ability to exert executive effects on the world.

Multiple representational systems

Representations gain meaning from their context within a representational system (RS), and the uniquely human capacity that lies at the heart of culture is our ability to copy and develop RSs, as well as adding individual representations to our repertoire: the ability, in other words, to meta-represent. Natural languages, as also systems of mathematical and musical notation, are some examples of cultural RSs, and each is peculiarly appropriate to its particular cultural area. Human minds acquire replicators on an ongoing basis throughout their lives, and this means that they can acquire novel RSs as well as novel representations. Amongst these various RSs, the natural languages have primacy: they alone benefit from an innate device for their acquisition. Yet they benefit, too, from the innate ability to meta-represent – and it is this which allows us also to develop nonlinguistic RSs, whose diverse rules and structures are realized in media other than speech. Once these sorts of RS have been taken into account, it becomes clear that there are many concepts that are not available to us until the RS that supports them has been developed.

Human minds and culture

According to Distin (2005), humans are born with a degree of mindedness that includes, for example, the ‘representation instinct’: an ability and tendency to learn and manipulate vast numbers of representations, as well as the various systems in which they are embedded. And this innate mental potential of an infant is realized as a result of exposure to the cultural environment.

Genes preserve and replicate biological information by building vehicles for their own propagation and protection. The effects of the genes are found in the machines that they build for their survival, and their replication also depends ultimately on this same machinery. Memes depend for their replication on a faculty of the human mind that is ultimately of a genetic nature, namely the representation instinct. Organisms, as well as minds, develop via interaction between the innate potential and the environment, and in the case of the mind a crucial part of that environment comprises of the memes. A human mind is thus partly a product of the memes, but only because it has the innate potential to interact with and develop in response to these memes. And culture is the product of human minds, although the preservation of information in representational content ensures that the culture we see today is mostly the result of memes produced by human minds of long ago. The development of human minds depends on a combination of two types of processes: their innate potential is the result of an interaction between genes and the physical environment, and that potential is fulfilled as a result of interaction with memes.

The selfish meme?

Memes are best thought about not by analogy with genes but as new replicators, with their own ways of surviving and getting copied.

Susan Blackmore

Dawkins (1989) described the essence of his ‘selfish gene’ theory as the insight ‘that there are two ways of looking at natural selection, the gene’s angle and that of the individual.’ The essence of his selfish meme hypothesis is the insight that there are two ways of looking at cultural change, the meme’s angle and that of the human individual.

One of the most significant implications of the theory of Dawkins’ selfish gene is that the individual organism was not an inevitable outcome of genetic evolution: it so happens that genes have banded together to build survival machines, but the only crucial feature of any form of evolution is the replicator – the unit of selection. Although organisms clearly exist, and have a perspective from which the world of genes is irrelevant to their everyday lives, fundamentally their lives and evolution are determined by that world. According to Distin (2005), no analogous insight arises from the theory of the selfish meme, because memes do not build survival machines. Their replicative mechanisms, and the means of their variation and selection, lie in genetically determined human faculties, and not in vehicles that they themselves build.

Dennett (1991) and Blackmore (1999), however, take the view that we are meme machines, just as we are gene machines. Consequently, they argue that ‘there is no conscious self inside’ those machines; and that ‘a complex interplay of replicators and environment’ is all there is to life. Our sense of self may not be illusory, but our sense of control over the collective products of our minds may well be. Although our minds provide the mechanisms of memetic evolution, there is a very real sense in which the directions of that evolution are independent of us.

15.4 Econophysics

A financial market is a complex system in which a large number of traders interact with one another, and also react to external information, and determine the ‘best’ price for a given item. The time evolution of the price and the number of transactions of a traded item is generally unpredictable. The time series indicating the price variation of an item is found to be essentially indistinguishable from a stochastic or random process. Like other complex systems, financial markets are open systems with many interacting subunits, and the subunits interact nonlinearly.

The efficient-market hypothesis

An efficient market is defined as one in which all the available information is processed instantly when it reaches the market, and in which this fact is immediately reflected in new values of prices of the traded assets. The efficient-market hypothesis (EMH) says that any market is highly efficient in determining the most rational price of a traded item or asset. It was originally formulated in the 1960s. There are two assumptions involved here: (i) the market is efficient; and (ii) the behaviour of traders is strictly rational.

Why does the time series of returns appear to be random? This is because it carries so much information that there are no readily discernible regularities in it. It is, by and large, a nonredundant time series. The information it carries is almost irreducible, or algorithmically incompressible for most practical purposes (cf. Part 4). The EMH requires that the concerned time series for market prices has a dense amount of nonredundant information. Since there are limits on the speed and capacity of our computers, a time series carrying this information is almost indistinguishable from a totally random time series. Of course, analysis of the deviation from a totally random time series is a good way of testing the degree of validity of the EMH in a given situation.

The law of diminishing returns

Suppose there is good demand for a commodity because of its attractive existing price. Naturally, the price will increase. This will then reduce the demand. And a reduced demand will entail a lowering of the price, and so on, till the demand and the price have reached a state of equilibrium. Thus negative feedbacks tend to stabilize an economy, as per conventional economic theory. This law of diminishing returns implies a single equilibrium point for an economy, and such situations are amenable to analytical control.

By and large, resource-based economic activities (e.g. agriculture and mining) tend to follow the law of diminishing returns. By contrast, knowledge-based parts of an economy are generally governed by the law of increasing returns or positive feedback.

The law of increasing returns

As demonstrated by the pioneering studies of Brian Arthur during the 1990s, positive feedbacks often occur in an economy, with the resultant multiple equilibrium points. Small shifts in the economy can get amplified, rather than smothered out. The economy evolves like any open, nonlinear complex system. There can be multiple bifurcations in phase space, and it is difficult to predict which bifurcation branch will be chosen by the market forces. What is more, once the random events select a particular branch or path in phase space, the choice tends to get locked-in, regardless of the advantages of the alternatives. An example is the history of the VCR industry. The market started out with two competing formats, VHS and Beta, selling at about the same price. It appears, in hindsight, that Beta was technically superior. In the beginning there were increasing returns for each format, as their market shares increased. For example, a large number of VHS recorders in the hands of consumers motivated the vendors to stock more prerecorded tapes in the VHS format. This encouraged more people to buy VHS recorders. The same law of increasing returns operated for the Beta format also. In the beginning there were fluctuations in the fortunes of the two competing brands, attributable to factors such as external circumstances, ‘luck’, and corporate manoeuvring. Then, perhaps by chance, increasing returns on early gains by VHS (reduced production costs per unit on increased volumes of production) tilted the game in favour of VHS, driving the other technology out of the market. This is something which could not have been predicted in the beginning.

The law of increasing returns can go beyond the product with which a company started (Arthur 1990): ‘Not only do the costs of producing high-technology products fall as a company makes more of them, but the benefits of using them increase. Many items such as computers or telecommunications equipment work in networks that require compatibility. When one brand gains a significant market share, people have a strong incentive to buy more of the same product so as to be able to exchange information with those using it already.’

Path dependence

In a positive-feedback economy, although the individual transactions are small and essentially random events, they can accumulate by the positive (nonlinear) feedbacks. A number of characteristics or historical antecedents of positive-feedback economies can be listed:

1. In a particular industry, there is often a clustering of firms in a specific geographical location. A different location would have been better, but there is a kind of freezing of historical accidents in what has actually happened. Why? The first firm chooses a location for some logical (or even illogical) reason. The choice of the second firm depends not only on the (real or perceived) merits of that region, but also on the fact that it is profitable to be near the first firm. There is cascading effect because the third firm may be influenced more by the presence of the first two firms in that region, than by the absolute merit of that region; and so on.

2. Railroad gauges are what they are at present because, once a particular choice was made (even arbitrarily), it was economical to stick to that choice everywhere in that region. There is a self-enforcement effect operating here.

3. The initial advantage possessed by a country or a multinational corporation can snowball into total dominance at the global level, until a better or cheaper product overcomes the monopoly. This highlights the importance of industrial research in any knowledge-based economy. Anther important factor is the timing of release of a product.

In the language of evolution of the phase-space trajectory, what we are seeing here are random bifurcations in phase space. Once a branch of a bifurcation gets selected for further time-evolution, there is no going back; there is only a locked-in trajectory along a particular path in phase space. Thus the evolution of a positive-feedback economy has a strong path dependence. This path dependence can cause even hitherto successful economies to become locked into inferior paths of development. There is always a danger that a sound technology, with good long-term potential, may get rejected just because it has a long gestation period and slow initial growth. Similarly, when two new technologies compete, the one with a better initial acceptance by people may oust the other from the market, even when the other technology is inherently better (as shown by later events). Early superiority or ‘selectional advantage’ is no guarantee of long-term fitness. Arthur (1990) cites the example of how the U.S. nuclear-power programme got ‘phase-locked’ into the light-water-cooled reactors option, even though the high-temperature, gas-cooled, reactor designs may be inherently superior.

The bottom line is that, unlike negative-feedback economies, positive feedback economies do not head for a unique equilibrium; their phase-space trajectory is not path-independent. Like in a chaotic system, even identical-looking initial conditions can lead to divergence in trajectories, simply because even small events or errors may get hugely amplified as time passes. Long-term accurate forecasting then becomes difficult, if not impossible.

15.5 Concluding Remarks

The emergence of humans has sharply accelerated the rise of overall complexity of our Earth. This has happened, and is still happening at an ever-increasing pace, because of the evolution of cultural complexity. A major reason for this is the very high level of intelligence possessed by humans. I shall discuss intelligence and consciousness in the next article in this series.

Human beings and their institutions process more energy per unit mass than do stars or galaxies.

Eric Chaisson, Cosmic Evolution

Dr. Vinod Kumar Wadhawan is a Raja Ramanna Fellow at the Bhabha Atomic Research Centre, Mumbai and an Associate Editor of the journal PHASE TRANSITIONS

Related posts:

1. COMPLEXITY EXPLAINED: 7. Cosmic Evolution of Complexity
2. COMPLEXITY EXPLAINED: 8. Evolution of Chemical Complexity
3. COMPLEXITY EXPLAINED: 13. Evolution of Biological Complexity
4. COMPLEXITY EXPLAINED: 16. Evolution of Intelligence and Consciousness
5. COMPLEXITY EXPLAINED: 6. Emergence of Complexity in Far-from-Equilibrium Systems
6. COMPLEXITY EXPLAINED: 14. Biological Complexity at the Edge of Chaos

Living entities have evolved to possess enormous amounts of order and complexity. Can Darwinian natural selection alone explain this order? Probably not. We must also take note of the inherent tendency of all complex adaptive systems to move towards self-organized states of optimum order. Biological and other kinds of complexity thrive best at the ‘edge of chaos,’ and this is where evolutionary forces usually operate. The dynamics of complexity around the edge of chaos is ideally suited for evolution that does not destroy self-organization.

14.1 Introduction

Self-organization is a characteristic feature of any open, far-from-equilibrium complex system. As emphasized by Stuart Kauffman, it is on this existing order that Darwinian natural selection operates and further adapts it to the environment. In other words, natural selection is not the sole source of order in biology. Being complex systems, biological entities tend to self-organize anyway. As Kauffman said in At Home in the Universe (1995):

I suspect that the fate of all complex adaptive systems in the biosphere — from single cells to economies — is to evolve to a natural state between order and chaos, a grand compromise between structure and surprise. Here, at this poised state, small and large avalanches of coevolutionary change propagate through the system as a consequence of the small, best choices of the actors themselves, competing and cooperating to survive.

He mentions ‘chaos.’ Let us begin by getting familiar with some elementary concepts in chaos theory.

14.2 Elements of Chaos Theory

A chaotic system is characterized by unpredictable evolution in space or time, even though the differential equations or difference equations describing it are deterministic (if we can neglect noise). The motions in a chaotic system are unstable, and this instability leads to a sensitive dependence on initial conditions. In the language of algorithmic information theory (cf. Part 4), chaos has the largest (but finite) degree of complexity.

Several basic features of chaos can be illustrated by recourse to the so-called logistic equation. It embodies a 1-dimensional feedback system, and was formulated as early as in 1845 to model the population dynamics of a species. The question posed was: How will the population of a species, confined to a certain geographic area, vary from year to year? Obviously, the population in a year t+1 will depend on the population in the previous year t: x_t+1 = kx_t; here k is some suitable constant of proportionality (or a control parameter). This equation simply models the fact that the larger the population is, the more is the number of offspring it would produce. But this cannot be the full story. There are other factors to consider. For example, if the population in the year t becomes too large, there can be an extra decimation of the numbers, either by predators, or due to shortage of food, or due to the altered competition in the reproduction dynamics. Therefore a more realistic logistic equation is as follows:

_{xt+1 = k xt (1-xt)}

Even this is only a simplistic model of population dynamics, and more sophisticated models have been proposed and investigated. But it is sufficient for providing a good insight into how chaos sets in under certain conditions.

It is convenient to describe the population x as a fraction of the largest value, N, that it can attain. Then x varies between 0 and 1. For any fixed value of k, a plot of x_t+1 against x_t gives an inverted parabola, and x_t = 0.5 corresponds to the top point on the parabola. Putting x_t = 0.5 in the above equation gives x_t+1 = k/4. Since x cannot be larger than 1, the largest value that the control parameter k can have is 4.

A fascinating variety of dynamics, including chaos, is observed as k takes various values in the range 0 to 4. Suppose we imagine a situation for the population in which k is less than 1. Suppose x₀ is the value of the population in a particular year t = 0. Then we can use the logistic equation to calculate the expected population x₁ in the next year. Then x₁ can be put back into the logistic equation to obtain the population value x₂ for the following year. We can carry out such iteration repeatedly.

Figure (a) shows how the population will change in successive years if we take k = 0.95. We find that the population eventually becomes zero. This eventual or final value of x, denoted by x*, is an attractor; attractors were introduced in Section 12.4 (Part 12). There is a basin of attraction such that every starting value x₀ is eventually drawn towards the attractor x* = 0. Thus if k < 1, we have a fixed-point attractor at the zero value of the population; the conditions are too inimical for the population to survive.

A different population dynamics is predicted by the logistic equation for 1 < k < 3. Now x* is not zero; rather it increases from a near-zero value to ~0.667 as the control parameter k is increased from 1 to 3. Figure (b) shows the results for k = 2.8.

A fundamentally different kind of dynamics emerges for 3 < k < 4: The population trajectory no longer converges to a single fixed point or attractor in phase space. Further, the trajectory becomes increasingly sensitive to the value of k. For k = 3.4 (results shown in Figure (c)), the trajectory has not one but two fixed points: one at x₁* ≈ 0.452 and the other at x₂* ≈ 0.842. This means that, from year to year, the population oscillates between ~45% and ~84% of the maximum possible value. We now have a two-point attractor (Figure (c)). We describe such an oscillating system as having a period 2.

This periodic attractor is actually just the beginning of still more complex dynamics as the value of k is increased. There is a critical value k ≈ 3.4495 beyond which we get a four-point attractor. For example, for k = 3.5 we get x₁* ≈ 0.875, x₂* ≈ 0.383, x₃* ≈ 0.827, x₄* ≈ 0.501. Such successive bifurcations of each attractor into two, such that there are 4, 8, 16, 32, .. etc. fixed points, occur with smaller and smaller increases in k.

We move into the chaotic regime of complexity for values of k above ~3.57. The periods now double every time k is increased by even an infinitesimally small amount. The number of points that comprise the attractor is now extremely large, and the trajectory looks quite erratic (Figure (d)), although there are some ranges of k values for which there is apparent stability. I have taken these numbers and the figures from the book Chaos Theory Tamed by G. P. Williams (1997), which should be consulted for many other fascinating details.

If the periods are going to double even for infinitesimally small increases in the value of k, there are two situations to face, one practical and the other computational. The practical aspect is that the logistic equation, or any mathematical model for explaining reality, has to finally interface with (or explain) experimental data, and such data can never be obtained with infinite accuracy. The computational aspect is that, even if we have access to infinitely accurate data, no computer can perform calculations based on the modelling equation(s) with infinite precision. It is irrelevant whether or not the computer program written for modelling a complex system is a simple one. This is why one makes the statement that a chaotic system, or rather a system in a chaotic regime, has the largest (though finite) degree of complexity.

Having achieved a nodding acquaintance with chaos theory, let us now hark back to the work of a stalwart in the field of complexity, namely Stephen Wolfram.

14.3 Wolfram’s Four Universal Classes of Cellular Automata

I introduced Wolfram’s work on cellular automata (CA) in Section 11.4 (Part 11). An extensive empirical analysis by him of all 1-dimensional CA showed that the patterns generated by them (even when we start from random or disordered initial conditions) can be generally divided into four distinct classes:

In Class 1, evolution from almost any initial state leads finally to a unique homogeneous state. This is like the occurrence of a ‘limit point’ or attractor in the phase space of a nonlinear dynamical system.

In Class 2, there is ultimately a sequence of simple stable or periodic structures. This corresponds to the occurrence of ‘limit cycles’ in phase space.

Class 1 patterns are repetitive, and Class 2 patterns are nested. Both are predictable after their repetitive or nested nature has been discerned, and are therefore computationally reducible. The black and white figure I showed in Section 11.4 is an example of a class 2 CA, and is reproduced here again.

Image Source : wolframscience.com

Class 3 CA exhibit chaotic or aperiodic long-time behaviour. Such CA grow indefinitely at a fixed speed. Their patterns are often self-similar or scale-invariant. They are characterized by a fractal dimension, with log₂3 or ~1.59 as the most common value for the dimension.

Class 4 CA are the most interesting from the point of view of complex behaviour. For them the pattern grows and contracts irregularly. There are complicated localized structures, some of which propagate with time. Therefore their long-time behaviour is undecidable.

14.4 Langton’s ‘Edge of Chaos’ Idea

Evolution thrives in systems with a bottom-up organization, which gives rise to flexibility. But at the same time, evolution has to channel the bottom-up approach in a way that doesn’t destroy the organization. There has to be a hierarchy of control – with information flowing from the bottom up as well as from the top down. The dynamics of complexity at the edge of chaos seems to be ideal for this kind of behaviour.

Doyne Farmer

I introduced Neumann’s self-reproducing CA in Section 11.6. Christopher Langton (1989) (and also Norman Packard) extended the CA approach to the field of artificial life (AL) (cf. Section 10.4 in Part 10) by introducing evolution into the Neumann universe. In the self-reproducing CA created by Langton, a set of rules (the GTYPE) specified how each cell interacted with its neighbours, and the overall pattern that resulted was the PTYPE. The local rules could evolve with time, rather than remaining fixed. This pioneering work was a fine example of adaptive computation.

Langton also correlated his work on AL with Wolfram’s four universal classes of CA. We have seen above that small values of the control parameter k in the logistic equation give rise to nonchaotic behaviour. This is similar to the dynamics described by Wolfram’s Class 1 and Class 2 CA. And sufficiently large values of k result in totally chaotic dynamics, which corresponds to Class 3 CA. Langton investigated the introduction of a parameter similar to k into the rules controlling CA behaviour to check this analogy more clearly, and particularly to investigate the connection between Class 4 CA on one hand, and partially chaotic systems on the other.

After a number of trials, he came upon a parameter λ for the CA rules which corresponded to the control parameter k of the logistic equation. This λ was defined as the probability that any cell in the CA will be ‘alive’ after the next time step. In the nested CA figure above, we have chosen the colours black and white, which we can now relate to ‘alive’ and ‘dead.’ For example, if λ = 0 in the rule governing the evolution of a particular set of CA, all cells would be white or dead after one time step. The same would be true if λ = 1.

In his computer experiments, Langton found that, as expected, λ = 0 corresponds to Class 1 rules. The same was true for very small nonzero vales of λ.

As this control parameter was increased gradually, Class 2 features started appearing at some stage, with characteristic oscillating behaviour. With increasing values of the control parameter, the oscillating pattern took longer and longer to settle down.

Taking λ = 0.5 resulted in totally chaotic behaviour, typical of the Wolfram Class 3.

Langton found that clustered around the critical value λ ≈ 0.273 were Class 4 CA.

Thus, as the control parameter increased from zero onwards, he saw a transition from ‘order’ to ‘complexity’ to ‘chaos.’

The next conceptual jump Langton made was to equate this qualitative change of behaviour of CA with a phase transition. Recall that a phase transition can occur in a material when some control parameter like temperature is varied (e.g. water changes to ice as it is cooled through its freezing point). Langton realized that his control parameter λ plays a role in determining the dynamics of CA that is similar to the role played by temperature in a phase transition. At low temperatures a material is solid, say in a crystalline state, which is an ordered state. At high temperatures we have a fluid state (liquid or vapour), which signifies chaos or disorder. Langton drew the analogy with such phase transitions for describing the Class 4 behaviour in CA which sets in for values of λ around 0.273.

Phase transitions in a material are represented in phase diagrams, in which there are lines or boundaries which separate one phase from another. Langton gave the corresponding phase boundary in the Neumann universe (a kind of phase space) the name edge of chaos. We should remember, however, that this ‘edge’ or boundary is not a sharp one. It is more like a thin or thick membrane in phase space, with chaotic behaviour on one side, and ordered behaviour on the other side of the membrane. There is a gradation from chaos to complexity to order across the membrane in phase space. And complex behaviour is at its most versatile within the membrane.

Many instances can be cited for the gradation from order to complexity to chaos. Even a simple computational algorithm like the Game of Life (mentioned in Section 11.3) is a universal computing device. The Game of Life is independent of the computer used for running it, and exists in the Neumann universe, just as other Class 4 CA do. As explained by Wolfram, such CA are capable of information processing and data storage etc. They are a mixture of coherence and chaos. They have enough stability to store information, and enough fluidity to transmit signals over arbitrary distances in the Neumann universe.

There are analogies of this, not only with computation, but with life, economies, and social systems also. After all, they are all just a series of computations. Life, for example, is nothing if it cannot process information. And life strikes a right balance between too static a behaviour and excessively chaotic or noisy behaviour.

14.5 Biological Complexity at the Edge of Chaos

The occurrence of complex phase-transition-like behaviour in the edge-of-chaos domain is something very common in practically all branches of human knowledge. Kauffman (1969), for example, recognized it in genetic regulatory networks (cf. Section 12.5 in Part 12). In his work on such networks in the 1960s, he discovered that if the connections were too sparse, the network would just settle down to a ‘dead’ configuration and stay there. If the connections were too dense, there was a chaotic churning around. Only for an optimum density of connections did the stable state cycles arise.

Similarly, in the mid-1980s, Farmer, Packard and Kauffman found in their autocatalytic-set model (Section 9.4) that when parameters such as the supply of ‘food’ molecules, and the catalytic strength of the chemical reactions etc., were chosen arbitrarily, nothing much happened. Only for an optimum range of these parameters did a ‘phase transition’ to autocatalytic behaviour set in quickly.

Many more examples can be given: Coevolutionary systems; economies; social systems; etc. A right balance of defence and combat in the coevolution of two species ensures the survival and propagation of both. Similarly, the health of economies and social systems can be ensured only by a right mix of feedbacks and regulation on the one hand, and plenty of flexibility and scope for creativity, innovation, and response to new conditions on the other. The dynamics of complexity around the edge of chaos is ideally suited for evolution that does not destroy self-organization.

But why and how do complex systems move towards the edge-of-chaos regime, and then manage to stay there? Per Bak supplied a clear and profound answer in terms of his important notion of self-organized criticality.

14.6 Self-Organized Criticality

Per Bak and coworkers (1996) argued that a particularly important consequence of self-organization (in a complex adaptive system) is the occurrence of self-organized criticality (SOC).

Let us consider a tabletop on which grains of sand are drizzling down steadily. To start with, the flat sandpile just grows thicker with time, and the sand grains remain close to where they land. A stage comes when the sand starts cascading down the sides of the table. The pile gets steeper and steeper with time, and there are more and more sandslides. With time the sandslides (avalanches or catastrophes) become bigger and bigger, and eventually some of the sandslides may span all or most of the pile. The average slope now becomes constant with time, and we speak of a stationary state.

This is a system far removed from equilibrium. Its behaviour has become collective. Falling of just one more grain on the pile may cause a huge avalanche (or it may not). The sandpile is then said to have reached a self-organized critical state. The edges and surfaces of the grains are interlocked in a very intricate pattern, and are just on the verge of giving way. Even the smallest perturbation can lead to a chain reaction (avalanche), which has no relationship to the smallness of the perturbation; the response is unpredictable, except in a statistical-average sense. The period between two avalanches is called a period of tranquillity (stasis) or ‘punctuated equilibrium.’

In a system in an SOC, big avalanches are rare, and small ones frequent. And all sizes are possible. There is power law behaviour: the average frequency of occurrence, N(s), of any particular size, s, of an avalanche is inversely proportional to some power τ of its size: N(s) = s^-τ. A log-log plot of this power-law equation gives a straight line, with a negative slope determined by the value of the exponent τ. The system is scale-invariant: Usually the same straight line holds for all values of s. Large catastrophic events (corresponding to large values of s) are consequences of the same dynamics which causes small events.

This is complex behaviour, and according to Bak, large avalanches, not gradual variation, can lead to qualitative changes of behaviour, and may form the basis for emergent phenomena and complexity. Bak (1996) gave several examples to make the point that Nature operates at the SOC state (or equivalently at the edge-of-chaos state). According to him, even biological evolution is an SOC phenomenon.

How do systems reach the SOC state, and then tend to stay there? The sandpile experiment provides an answer. Just like the constant input drizzle of sand in that system, a steady input of energy, or water, or electrons, can drive systems towards criticality, and then they self-organize into criticality by repeated spontaneous pullbacks from super-criticality, so that they are always poised at or near the edge between chaos and order.

We discussed beehives and ant colonies in Part 2. They are again nothing but examples of self-organization in open mutually-interacting systems. Many more examples of such ‘out of control’ complex adaptive systems exist.

14.7 Further Evolution of Complexity at the Edge of Chaos

The next question is: What do complex systems do when they have reached the edge of chaos? In the phase space of the dynamical system, the edge of chaos is a thin membrane, a region of complexity separating the ordered regime from the chaotic regime.

I introduced complex adaptive systems (CASs) formally in Part 5 of this series. John Holland (1998) pointed out the occurrence of ‘perpetual novelty‘ in a CAS, and said that this essentially amounts to saying that the system moves around in the edge-of-chaos membrane. But that is not all. The moving around can actually take the system to states of higher and higher sophistication of structure and complexity. Learning and evolution not only take a CAS towards the edge-of-chaos membrane in phase space, they also make it move within this membrane towards states of higher and higher complexity. The ultimate reason for this, of course, is that the universe is ever expanding, and there is therefore a perpetual input of free energy or negative entropy into it.

Farmer (1986) gave the example of the autocatalytic-set model (which he proposed along with Packard and Kauffman) to further illustrate the point about perpetual novelty and the ever-increasing degree of complexity of a CAS. When certain chemicals can collectively catalyze the formation of one another, their concentrations increase by a large factor spontaneously, far above the equilibrium values. This implies that the set of chemicals as a whole emerges as a new ‘individual’ in a far-from-equilibrium configuration. Such sets of chemicals can maintain and propagate themselves, in spite of the fact that there is no genetic code involved. In a set of experiments, Farmer and colleagues tested the autocatalytic model further by allowing occasionally for novel chemical reactions. Mostly such reactions caused the autocatalytic set to crash or fall apart, but the ones that crashed made way for a further evolutionary leap. New reaction pathways were triggered, and some variations got amplified and stabilized. Of course, the stability lasted only till the next crash. Thus a succession of autocatalytic metabolisms emerged. Apparently, each level of emergence through evolution and adaptation sets the stage for the next level of emergence and organization.

14.8 Concluding Remarks

It is often not realized by Darwinists and neo-Darwinists that natural selection alone cannot lead to such high levels of order and complexity as seen in living organisms. A high degree of order already exits in complex adaptive systems because of their self-organization and perpetual-novelty tendencies. Natural selection only hones this order to still higher levels of complexity.

The self-organization feature of complex adaptive systems may worry the Creationists some more. They have been busy attacking Darwin and his followers for the ‘blasphemies,’ and have been trying to argue that the fascinating degree of order observed in living creatures cannot possibly be the result of a series of ‘accidents’ in the form of mutations etc. The fact is that, as emphasized by Stuart Kauffman and others, Darwin or no Darwin, complex adaptive systems have the fundamental property that they self-organize into states of high (and ever-increasing) degree of order, so long as they are able to exchange matter and energy with the surroundings. Darwinian natural selection does lead to some increase of complexity and order but, by and large, it only hones the already available order and complexity to help a population adapt itself to the prevailing conditions.

Dr. Vinod Kumar Wadhawan is a Raja Ramanna Fellow at the Bhabha Atomic Research Centre, Mumbai and an Associate Editor of the journal PHASE TRANSITIONS

Related posts:

1. COMPLEXITY EXPLAINED: 13. Evolution of Biological Complexity
2. COMPLEXITY EXPLAINED: 8. Evolution of Chemical Complexity
3. COMPLEXITY EXPLAINED: 3. Thermodynamic Explanation for the Increasing Complexity of our Ecosphere
4. COMPLEXITY EXPLAINED: 5. Defining Different Types of Complexity
5. COMPLEXITY EXPLAINED: 6. Emergence of Complexity in Far-from-Equilibrium Systems
6. COMPLEXITY EXPLAINED: 7. Cosmic Evolution of Complexity