Friday, March 25, 2005

For Those With MP3 Players

Following a lead from slashdot I've found a free lecture archive on that includes the Library of Congress Series on the Digital Future, which features presentations by David Weinberger and Larry Lessig, among others. Not only is it free, but due to's Red Tag Sale, it's also 50% off! What a deal!

ps. I don't know if allows deep linking, if it doesn't work, do a search on for Lawrence Lessig, click on the Library of Congress Speech, then click on the link to C-SPAN on the speech page, then click on See All Matches.

Sheer Brilliance!

An alarm clock that hides from you when you hit snooze. I need one of those!

Round 2: Social Sciences (Part I)

Henry's response does an excellent job of moving our discussion along. I accept wholesale his explanation about complexity and chaos, so I'll focus on the second half regarding economic theories.

I like Henry's interpretation of Mises, and I can see where he found support for it and I think this is the correct interpretation, but I'd like to note for the record that Mises' statement regarding action necessarily being rational and that the term rational action is pleonistic does not jive with Henry's explanation. Mises is actually asserting that volitional action is necessarily rational. I disagree with him even on that point, but it is a far more defensible position than stating (as Mises does) that all action is rational.

Given this interpretation of Austrian subjectivism, I think there are two approaches through which behavioral criticisms could be viewed. The first would be to assert that even volitional actions can be irrational. The second is to suggest that there may be more economically significant actions than Mises would suppose that are not volitional. I think these two approaches are just different sides of the same coin. I'd like to preface my discussion of these criticisms by agreeing with Henry, that behavioral critique does not render Austrian economics (or neo-classical economics for that matter) invalid, but merely offers a refinement. The assumption of rational preferences and action that characterizes neo-classical economics and Austrian economics is for the most part (as stated in my Round I:Part I response) a good assumption. This assumption is the critical insight on which both theories are based (as well as many political theories) and yields a great deal of useful theory, theories which have validated themselves quite well in actual practice. The behavioral critique is merely an effort to define some possible boundaries for the operation of these theories.

~> Read More!
Coming around then to the criticism, I think the first step is to question the realm of possibility. We don't know precisely how cognitive processes work, and probably won't any time soon. However, we know enough to speculate. Based on current knowledge I think it is valid to speculate that all cognitive processes may not be equal. We know that the brain is a mechanistic device, that neurons fire in networks, that different parts of the brain are engaged for different purposes. We also know from information theory (as was brilliantly illustrated in Henry's chaos discussion) that some calculations are more difficult than others, and that there are many different methods to achieve approximate results and many degrees of precision which can be applied to calculations for approximation. We also know from computer science that many of the tasks of calculation in which the brain engages are phenomenally complex and difficult from an information processing standpoint. Even given equivalent processing power, human programmers would face immense difficulty trying to program something that could accomplish all that the brain does. Taken altogether, I conclude from this that the brain employs many wonderful shortcut algorithms (heuristics) to allow it to perform with the remarkable efficiency that it does.

From here we need to note a few things about heuristics. We know that (by definition) in the act of approximation, some precision is lost. From experience in mathematics and computer science we know that each heuristic has certain limiting characteristics; each heuristic has varying strenths and weaknesses. In some cases one algorithm for compressing an image file will outperform a second algorithm, where a different image file may yield the reverse result. We also know that it's usually (but not always) the case that the more efficiently a heuristic performs, the greater the loss of precision.

At this point we might make a few conclusions and assumptions about brain operation. Due to its use of various heuristics, it is likely that the brain performs more efficiently on some types of calculations than others. Perhaps more importantly, if we are willing to contemplate that the brain may use more than one unique heuristic to solve the same problem in different situations, the brain may yield a varying quality of results to the same question based on which heuristic is applied at a given time. The final step needed to reach the behavioral position is to suppose that external factors may consistently (and non-volitionally--I'll come back to this) trigger the use of one heuristic over another.

There are a lot of assumptions involved here, and I don't ask you to accept them all as true. I would only ask that you consider them as reasonable proposals not obviously contravened by present knowledge about cognitive processes (and I would be entirely happy to hear any criticisms you have on this point). What you are looking at is the central premise of the deductive argument of behavioral theory. It is a theory which Henry rightly states cannot be proven at this point.

The experiments carried out by behavioral psychologists, as Henry notes, do not fully eliminate the possibility of interfering factors (including rational volitional reasons for the actions taken). However, these data are not meant to prove anything, but rather to offer some support, by whatever limited means are available to us, to the premise above. I again disagree with Mises' position that because we cannot know how cognitive processes work nor definitely predict what action they will produce we must treat them as ultimately opaque and (while accepting Mises' own assumptions on cognition) question no further. His assumptions about which actions are volitional and that volitional actions are rational are no less a reach than the assumptions of behavioral theory. As an unknown quantity, cognitive processes remain open to deductive argument and to experimentation such as it is.

From my perspective, I find the assumptions made by behavioralists to be emminently reasonable. They very much conform to my own intuitions about cognitive processes and my knowledge of data processing and heuristic algorithms and my observations of human behavior. I find that behavioral experiments, although they vary in quality (and I agree that the VCR one is particularly weak), do offer at least some support for behavioral theory. The results of many of them are difficult to interpret as anything but the application of a weak heuristic in a decision which, in other circumstances, humans are capable of applying a stonger one.

To determine, finally, how behavioral theory plays with Austrian subjectivism requires behavioral heuristics to be placed within the context of actions, volition, and rationality. This may be a discussion about cognitive processes, but I see it as rather more a matter of semantics. The key cognitive insight (and a largely subjective one at that) is that we don't generally think in terms of heuristics. I had been planning on making an argument of this, but arriving here I realize that this argument would probably equal in length the rest of this post and I'm not up for that at the moment. Feel free to challenge this premise and I will flesh it out at a future date. For now, suffice it to say that the immense amount of effort invested by cognitive scientists, behavioralists, and computer scientists to uncover the heuristics utilized by the brain speaks volumes about our conscious awareness of the heuristics applied on our behalf. While we do experience a conscious phenomenon of weighing decisions before us, resulting in volitional action, the selection of heuristics and the application of them in the weighing process appears to be entirely subconscious.

The rest of the analysis descends into a semantic morass. In undergrad I took a 500-level philosophy course that dedicated an entire semester to a single question: What is agency (i.e. how do we define a person's actions)? Based on my experiences therein I'll offer the following conclusion to the above conundrum: Nobody has the first fricking clue what any of this means. At some point in the discussion the level of detail is such that we have no remaining useful intuitions about the basic terms (action, volition, intent, etc.) and they become maleable and in some senses interchangeable. But I'll try...

First, going back to my initial theory of rational as "consistent with or based on reason," I conclude that the variation in outcomes caused by the application of various heuristics are irrational. The output of the more precise heuristic here represents a rational action. By contrast the output of the subpar heuristic is simply not consistent with or based on reason. It is rather the product of, in essence, a cognitive defect. There is a sense in which you could say even the better heuristic is irrational, since it also is frequently an approximation, and it is only by comparison to the subpar heuristic that it appears rational. In other words, there is a danger here that I am calling any nonoptimal (in some ultimate sense) decision irrational. That is not my intent. I think there is something noteworthy about the supposition that a) the human mind can apply heuristics of varying quality to the same problem and b) external stimuli can consistently alter which heuristic is applied. I do not assert that the reasoning relied on needs necessarily to be optimal to be rational, but only that the subpar heuristic is inconsistent with that individual's own ability to reason through the problem (applying their own subjective values and objectives in the process), and that the subpar heuristic is applied not due to a rational choice (i.e. I don't have time to think this through), but as the result of the nonvolitional impact of seemingly irrelevant external circumstances. It is this quality that makes it irrational.

Next, in these cases the action is volitional in any meaningful sense, and yet the decision is framed by heuristic analysis which is subconscious and involuntary. What does that mean? One could say that this infection of nonvolitional framing which resulted in an irrational act caused the act to be effectively nonvolitional. This would fit with Mises' view of action (being nonvolitional, it is no longer assumed to be rational), although the scope of behavioral impact on economic actions would remove from his theories many actions that I think he would have thought covered by them. The alternative, which seems rather more straightforward to me, is to consider this a volitional action, but an irrational one, hence my basic conflict with Mises' assumption.

In either case the results would be the same. In the former, we've just removed a lot of economically significant actions from Mises' theory. In the latter Mises' theory would need to be amended to cover only rational volitional actions and the same thing occurs. In either case we now have a whole class of actions for which we need to reformulate existing economic theories.

Whew. Well, that shoots my afternoon. :)

Thursday, March 24, 2005

Re: A Critique of Social Science (Hank's Response)

Henry has been having some trouble with blogger, so I'm posting this for him. JB.

First I would like to thank you for taking the time to consider and criticize my writing. I allowed myself a little break after I read Joe's first response and feared that I might be a bit overwhelmed when I noticed upon coming back that there were three further additions. But to my relief these have merely refined the earlier arguments and done much of my work for me. So I will continue in my informal fashion and address the concerns that have arisen thus far.

The Issue of Inclusivity and the Barrier of Complexity

In terms of inclusivity I am largely in agreement with those criticisms that have so far arisen.

I am inclined, as Barry suggested, to declare that we ought to consider the physical or hard sciences those to which my criticisms are of little relevance. Everything else would then be soft science. There is of course the underlying philosophical issue, which Joe recognizes, that fundamentally, my arguments are universally applicable. That is, when I say, for instance:

"Many things will be nearly constant among the study populations… the effects of these factors will not be averaged out, nor will the experimenter have any sense as to which of them are significant."

There is no way that we can be certain that such a complaint could not be leveled against any experiment whatsoever. The constant that modifies the force of gravity may only appear constant. We have only been making physical observations for a very short period of time and there may certainly be significant variables that we have not accounted for because they change so slowly that the difference has been unnoticeable in the last hundred or thousand years (these are after all cosmologically miniscule time frames).

~> Read More!
Or, as Joe noted, the relations that we observe may be entirely superficial and coincidental and the real variables that govern the behavior of the phenomena we seek to understand could yet be entirely unknown to us.

In either case we must recognize that technically my arguments apply to all knowledge. All human knowledge is fundamentally uncertain. Thus we must fall back upon practical certainties. For the phenomena that we most thoroughly understand we cannot imagine any variables which we have failed to consider, and regardless of whether or not we fully understand the true basis of the phenomena we are at least able to make virtually perfect predictions as to the outcomes that the phenomena in question result in. Though the earlier arguments apply to our understanding of gravitation we can still use our knowledge of it to weave the paths of space probes in intricate patterns through the gravitational fields of the bodies of our solar system with uncanny precision.

With regard to what we may practically label as soft sciences this is not true. In the case of these sciences we can easily conceive of variables that may be significant but for which we are not accounting. Likewise in these sciences we regularly experience failures in prediction. Thus I would say that although in a strict sense all science is soft we might with a fair degree of certainty arrange them into the practical categories hard and soft.

I would also pause to note that the traditional classification of various types of science are largely arbitrary and, well, merely traditional. There are certainly fields of study that we yet call physics because they have grown out of the earlier fields of physics but which deal with such complexity that we must call them soft. I would also agree with Joe in seeing the medical sciences as existing on both sides of the boundary. I would not say that this is the argument that applies to string theory and advanced cosmological theories; these are merely speculation and as such are not science. I think their popularity largely arises from the same causes as that of the social sciences. This is not to say that there is no place for such theories or that their proponents are fools. Merely that they are speculations the validation of which is yet pending and thus are not posited (at least, not legitimately) in any way as scientific facts. They are neither hard nor soft.

As to the boundary of complexity itself this discussion should be illuminating. As we can never be certain that we are accounting for all of the significant variables, we can never be certain as to how complex an event is. In this strict sense there is no barrier. All phenomena are potentially too complicated for us to arrive at certain conclusions with regard to them. But of course we must consider the barrier not in the absolute sense but in the practical sense. Thus it is the line that I have already defined between hard and soft. I do not pretend that in the marginal regions this line is well defined. I do however maintain that the majority of cases are not marginal. Most of the principles of physics are predictive in an absolute sense; they will describe the future states of the system in proportion to the detail of the input data. For these phenomena we cannot conceive of any variables for which we are not accounting. We can say with just as much conviction that these things are false with regard to the social sciences in general.

I will conclude this section with a caveat that bears within itself the seed of a related argument. I have said that the social sciences are, in general, soft. Sometimes it is true that we may arrive at principles with regard to social phenomena which are relatively absolute. I will posit a general principle with regard to human behavior: Human beings abhor the touch of flame and they will strive to prevent themselves from being consumed by it. As much as any statement we may make with regard to human behavior as it occurs in the world this is certain (of course the exceptional phenomena of self-immolation is troublesome to this postulate; it would be a serious blow to the credibility of physics if objects occasionally fell up). Yet the question remains, of what use is this fact to us? The questions which we wish to solve with regard to social life involve the full complexity of human social interaction: what will be the interest rate on ten-year federal bonds 3 years hence? What political party will best enhance the well being of the people? How do we avoid social strife and physical violence? The acknowledgement of the initial fact does not help us to understand the more complex phenomena of which it is only a small part. We may understand the behavior of gravity and this may allow us to predict the path that a projectile will follow, but only if that path involves minimal interference. A cannon ball that is affected only by the wind will follow a relatively predictable path. An elastic rubber ball bouncing downhill on a roughly paved street in heavy traffic will not. Regardless of the fact that we know that the ball will follow roughly parabolic paths between collisions we are helpless to predict its actual overall path with any semblance of accuracy. Our fact about the behavior of men would likewise be useful if we were placing bets upon whether the man we are about to light on fire will attempt to extinguish the flames or rather quietly submit to their consumption of his flesh. Yet it is of little use in solving more broadly the questions related to human action. This point was implicit in my earlier arguments. For instance, I did not claim that the individual assertions upon which Matthew Rabin's paper was based were necessarily false in and of themselves, merely that in the context of the wider problem they were pitifully insufficient.

Chaos and the Transit of the Complexity Barrier

Here I will talk a bit about complex and chaotic systems. I am not an expert but I believe that I understand enough to cover the points that are relevant to our discussion. I would encourage you to engage this subject with confidence, as I don't think that it is at all beyond the average person to understand these things. As I stated in my first paper, the essence of mathematical ideas is best expressed in plain English; we need resort to equations only for the purpose of calculation (and as we don't need to make any calculations we won't need equations except as conceptual examples).

We must begin with systems that are neither complex nor chaotic. These rare systems are those for which we may discover exact solutions.

An example here would be two spherical objects moving through space exerting gravitational forces upon one another. We can write out the force acting upon each body exactly. The force will always be in the direction of the other body, it will be proportional to the product of the masses of the two objects, and it will be inversely proportional to the square of the distance between them. If we have an equation for the acceleration (the force equation that I just mentioned) we can integrate it to find an equation that calculates the velocities of the objects. Once we have the velocity equation we can integrate again to get an equation that will tell us the positions of the objects at future times. This position equation will allow us to plot the exact trajectory that the objects in question will follow given any initial setup (combinations of masses, initial positions, and initial velocities).

The preceding scenario was only made possible by our ability to integrate the equations in question. This is far from given. Equations that we can integrate are actually quite exceptional in real world problems. In the case above it is possible to do the integrations, but if there had been three objects instead of two it would not have been so. In taking such a step we move from the realm of exact solutions to the realm of approximate solutions.

I will step briefly aside to illustrate the concepts of exact and approximate solution.

[Imagine an object being thrown upward (we must neglect air resistance, so imagine we're on the moon). As before we can come up with the acceleration equation immediately: a = -g. That is to say, gravity is always pulling down with a constant force g (g is negative as I have defined the downward direction to be negative and up to be positive). In fact the gravitational force diminishes as the object moves upward (away from the body attracting it) but we are assuming that we can't throw it high enough for such changes to be significant. By integrating we can discover the velocity equation for the thrown object: v(t) = -g x t + vi. That is to say, the object has an initial velocity vi imparted by our throwing it and over time that velocity is reduced by the operation of the acceleration g. Vi is positive, as we have thrown the object upward. Here t is meant to signify time. Thus our velocity, v is reduced by g for each unit of t. Thus after one second (assuming that our unit of time is the second) v(1) = vi - g. If our initial velocity upward (vi) was 20 and g was 4 then it would take five seconds before our actual velocity (v) was reduced to zero (this is the point when the object ceases to move upward and it is the moment before it begins to move downward, thus it corresponds to the highest point of flight). Now by integrating once again we may discover the equation for the position, or height of the object: h(t) = 1/2 x -g x t ^2 + vi x t + hi. Now we have multiplied the first term by t to get t^2 and we have multiplied it by one half (or divided it by two). We have done this in order to calculate the change in position that results from the acceleration g. -g x t tells us what change in velocity g has resulted in (and this is why we have -g x t in the equation for v). Since initially g had had no effect this component starts at zero but by time t the acceleration g has generated a contribution to velocity equal to -g x t. So the average velocity due to g between time zero and time t is (-g x t + 0)/2 or (-g x t)/2 hence the factor of 1/2. In order to figure out how much distance was traversed due to this component of velocity we must multiply the average velocity by the time that the object has been traveling at this velocity t. Hence the additional t and thus we get 1/2 x -g x t^2. The we have vi x t which is easily understood, as the vi component of velocity is unchanging, thus we merely multiply vi times the time t to figure out what distance vi has caused the object to traverse. And finally we have the initial height hi which is the position that the object was thrown from: if t = 0 then hi = h.

This is the simplest example of something similar to the two-body problem described in the third paragraph of this section. The main purpose of it for now is to illustrate that when integration can be done we get nice equations, equations that we can simply plug numbers into in order to get exact solutions. Now I will solve the same problem imagining that we knew only the acceleration equation and that we could not arrive at the velocity and position equations using integration. This will require an approximate or numerical solution.

We know that we have an object beginning at a height hi traveling at an initial velocity vi and being accelerated downward at an acceleration g. We wish to know where this object will be at a future time t. Well, we know that at time t = 0 its position h will be h = hi. We also know that its velocity at t = 0 is v = vi. Thus we could assume that, for discrete periods of time, everything in the problem remains constant. Let us use intervals of one-tenth of a second. Thus we presume that for the first tenth of a second v = vi. If this is the case then at time t = 1/10 our height h will be h = hi + vi x 1/10. Our new velocity will be v = vi + -g x 1/10 and now this velocity will be constant for the next tenth of a second. So after two tenths of a second (t = 2/10) the object's height h = hi + vi x 1/10 + (vi + 1/10 x -g) x 1/10 and so on for each consecutive tenth of a second. If we wish to figure out where the object is 4 seconds after it is thrown we must execute 40 iterations of this process to find the answer. This is obviously much more difficult than simply plugging numbers for t, g, hi, and vi into the exact equation: h = 1/2 x -g x t ^2 + vi x t + hi. Furthermore, it is less accurate than doing so. The numerical answer will only be approximately accurate whereas the exact solution will be as accurate as the values of the inputs. You can, of course, increase the accuracy of the numerical method by reducing the length of the intervals between iterations but you must exchange the time required to make more calculations for the accuracy gained. ]

Now that we may use the concept of exact and numerical solutions we can proceed with the first step away from the most simple phenomena--those that yield to exact solutions--and toward more complex phenomena--those that require numerical solutions. The problem of three spherical bodies moving in space influencing one another via the force of gravity does not have an exact solution. There is no equation into which we can plug the initial conditions in order to find precisely what the subsequent states will be. We must utilize a numerical solution to solve this problem. This is manageable. Modern computers were designed for the express purpose of performing such numerical solutions (and business calculations which are different) and they greatly facilitate this procedure. But the important thing to recognize is that the transition from the two-body to the three-body problem does not involve a 50% increase in computational involvement but rather a manyfold increase.

After the transition from exact to numerical solutions we continue for some time along the complexity continuum without encountering a similar barrier. In this region additional factors will increase the overall computational complexity of the system faster than linearly but not in the exaggerated way that it jumped when we crossed the barrier of exact solution. When we move from the three-body problem to an equivalent four-body problem the computational complexity increases by more than thirty three percent and here is why.

In the three-body problem we have to do three sets of calculations per iteration, one for each body. For the four-body problem we need four sets of calculations. If they were the same calculations as before we would expect the computation to take 33% longer, but the fourth body increases the complexity of all of the computations for each of the other bodies. With three bodies we had to take into account the position of only the other two, now with four we need to take into account the position of three other bodies in order to calculate the resultant force on each body for each iteration. The inclusion of the fourth body, then, not only requires that we make an additional set of calculations each iteration but it also makes each individual set of calculations more involved. Further, with four bodies we have to make four approximations per iteration and the resulting increase in error is compounded with each iteration. Thus we are required to further reduce the intervals between iterations in order to achieve the same level of accuracy.

We can see that the more complicated a system is, the greater the complexity will be increased by an additional element.

So long as we can make a wide variety of approximations this is still not too troublesome. Experience has shown that we can engineer a wide variety of useful systems using numerical computation techniques and our powers of computation are rapidly rising; although a doubling in computing power may fall significantly short of resulting in a doubling of the complexity of the systems we may explain, progress is being made.

Now we arrive at the realm of the chaotic. It is frequently said that chaos theory is a misnomer and we must agree. Chaotic systems are not truly chaotic; that is, random and unruly. They are merely systems of such extreme complexity that numerical modeling is bound to fail because the inevitable approximations result in very significant errors. They are only chaotic in the sense that they are utterly unpredictable to us.

For our chaotic system imagine a two dimensional surface. Imagine that this is the surface of a turbulent pool of water; it contains a wide variety of flows and whirls. Now we place a bit of cork on the surface of the pool and our goal is to predict where the cork will be at some future time t. We can define the cork's location on the surface with two coordinates; let us call them x and y. We can define the flows over this surface as an equation that maps an x and a y input to a two dimensional vector. That is, for a given point on the surface (x1, y1) there will be a corresponding vector that describes the direction and magnitude of the current in this location. We can assume that the cork does not have significant momentum and that its velocity is always exactly that of the current on which it is resting. Thus at point (x1,y1) the velocity vector of the cork is identical to the current vector for the same point . We can use numerical methods to calculate the trajectory of the cork. If the cork is at (x1,y1) then its velocity at this instant is . We can multiply the velocity vector by a time interval t in order to determine the approximate displacement for that interval. We add the changes in x and y to the original position (x1,y1) to get a new position (x2,y2) = (x1 + dx, y1 + dy). We can enter the new position of the cork into the equation for the flows over the surface to find the direction and magnitude of the current at this new position. From here we may repeat the process through subsequent iterations in order to plot a trajectory for the cork.

So long as the system is not complex enough to be chaotic this method will work. Here is how we might determine whether or not it is chaotic.

With a system that yields properly to numerical computation we find that the results brought about by subsequent reductions in the time between iterations approach a final value. The paths get smoother, the final answer gets more precise and our knowledge is increased. But with a chaotic equation this is not the case. We begin with intervals of 1/10th of a second and get a tentative trajectory for the cork. When we reduce the interval to 1/100th of a second we get an entirely different trajectory. When we reduce it to 1/1000th of a second we again get an entirely different trajectory. The values do not tend toward some definite path. Now let me quote from my first commentary:

"The American Heritage Dictionary provides the following as the mathematical definition of chaotic: A dynamical system that has a sensitive dependence on its initial conditions."

Hopefully this is more meaningful now. Depending on what interval length we choose we will get a different position after the first iteration. Working from these variations on the second point (x2,y2) we arrive at entirely different trajectories. A seemingly insignificant change in the initial conditions brings about results so different that there appears to be no correlation between the initial and the later states of the system. Of course, there is a correlation. The flow equation is perfectly determinate, but, due to the impossibility of exact solution and the failure of numerical methods, we are at a loss to say what it determines. Again I quote myself:

"The formula that those economists are looking for is infinitely complex and chaotic and if they were ever able to discern it, its implications would be incalculable. Seemingly insignificant variables would form endlessly diverse combinations to trigger extremely significant events."

We know precisely the equation that describes our hypothetical pool yet the trajectory described by the cork is as mysterious as ever. Likewise, if the economists were able to derive perfectly the equation that would describe the level of the Dow Jones Industrial Average (something that I maintain is an impossibility) it would be useless to them, as its implications would remain incalculable.

Now we must discuss what precisely chaos theory is. Up to this point I have only said that chaotic systems are necessarily mysterious. If this summed up chaos theory it would not be very impressive and I would indeed be an expert. But, of course, chaos theory has more to say about chaotic systems. Chaos theory attempts to determine if there are things that we can say about chaotic systems even though we cannot predict future states with precision. With regard to our pool con bobbing cork they might be able to say that when placed in region A the cork always shoots into the upper right corner of the pool and bounces around for a while. With regard to a particular whirl there may be a region in which placed corks will always leave the whirl through the bottom half. Chaos theory then gives us an assortment of rules that we may glean from the flow equation, making it not entirely useless to us. Thus if we could arrive at equations that perfectly map the reality of economic systems then perhaps chaos theory could teach us something about the actual operation of the system even though we could not calculate actual future states.

My warning with regard to the applicability of chaos theory to social phenomena is that chaos theory, like exact solution and numerical computation, yields results only as sound as the equation that you are working from. There are many mathematicians attempting to apply the principles of chaos theory to economic problems but I do not believe that they will succeed, as the equations they are working from are insufficient (and are necessarily so as the perfect equation would require a practically infinite number of variables): garbage in, garbage out.

As to the transit of the complexity barrier, it is safe to say that this barrier is significantly mobile. It is undoubtedly true that this barrier has shifted quite noticeably in our own lifetimes. But then again, sixty miles an hour is, to us, a noticeable velocity, while the universe would end before we reached the nearest star traveling at such a speed. This is to say that though the progression of the barrier is clearly occurring it need not be significant in terms of problems which are the complexity equivalent of intergalactic distances. In the next one hundred years our computational abilities may increase one hundred trillion fold, and this would certainly allow us to solve, to our great advantage, many problems that are currently beyond us, yet our progress would still be unnoticeable in terms of ultra complex social phenomena.

I will finish with a couple of examples that ought to add heuristic weight to these arguments.

One I have stumbled across at random. I quote:

"For a single spoonful of air we would need to know the position and velocity of 1020 molecules bumping into one another about 6 x 109 times a second. The physicist Michael Berry considered a collection of oxygen molecules at atmospheric pressure at room temperature. He imagined a single electron placed at the edge of the known universe (somewhere around 1010 light-years away). After how many collisions would a given molecule in the oxygen miss a collision with another molecule which it would not have missed had the electron not been there? Remember that the electron is affecting the oxygen only by its gravitational field, which must be so weak that we can virtually discount its effect. You might think so, but in fact Berry calculated that the oxygen molecule would miss its collision after a mere 56 collisions."

I couldn't find an original source for this, so I cannot know what calculation results in this fact. Even if Berry were off by several orders of magnitude one could not predict the position of his oxygen molecules, even a fraction of a second into the future, without accounting for every particle in the universe. This is complex interdependence. Such unpredictable interactions are undoubtedly percolating up from the microscopic world at every moment.

We may also consider again the elastic rubber ball bouncing down a roughly paved street in heavy traffic that I mentioned at the end of the previous section. Perhaps thirty meters down the hill the ball is struck by a fast moving minivan and it ricochets over a nearby building. This is a very significant event in the course of the phenomenon we wish to understand. So we attempt to trace the cause of the minivan's appearance. Its driver, a middle aged woman, is traveling to the grocery store to buy a cake. This is because the cake that she had planned to serve was ruined. This is because a vase full of flowers fell upon it. This is because her housecat, in the pursuit of a buzzing housefly, bumped into the vase. The fly had entered the house because a whiff of delicious cake odor had been wafted out the window by a gentle breeze that would not have occurred had not a star located a billion miles away gone super nova a billion years ago last summer. This, again, is the sort of complexity that I am talking about. A researcher trying to understand why the ball behaves the way it does would have a wide field of study indeed. They could write papers on different types of cars. They could develop classification systems for potholes. They could explore the motivation of house cats. They could write papers about the reasons that people drive children to school or they could contemplate the effects of deep space astronomical events on gentle breezes. Quite simply, every researcher, in every university on earth, could devote all of their time to studying the problem of the bouncing ball and the poorly maintained street, and such could remain the case for a million years, and yet, they would be nowhere near exhausting the subject of study and nowhere nearer to predicting the trajectory of the ball. I do not see how anyone could believe that the GDP of the United States in 2006 or the causes of the next world war would be any less complicated than the bouncing ball (for all we know the bouncing ball could (along with an infinite number of other factors) cause the next world war or economic collapse).

Simply put, physics succeeds because it considers unimaginably simple systems in isolated situations. The social sciences fail because they cannot explore such simple systems because the most basic element of their study, a human being, is extremely complicated. It brings into the experiment all of the experiences it has ever had, it is necessarily impressed by an infinite number of uncontrollable and unique circumstances. So far as social scientists can arrive at definite conclusions these are only tiny facets of the larger equation that explains the actual system in question (a bouncing ball researcher may be perfectly correct in asserting that a reason for a vehicle to be on the road is because its occupant may be on the way to a movie, but so what?); the equation that, even if we had it, still would not be very useful. This refers back to the illusion of progress section of my original essay; the accumulation of social scientific knowledge appears promising but in reality we could fill countless libraries with such information without getting any closer to solving such questions as: How should we educate our children? How do we reduce criminal behavior? How do we enhance the satisfaction of mankind?

Deduction in General and Ludwig von Mises in Particular

Joe rightly notes that the social sciences clearly make use of deduction. Now I did state that deduction is an essential part of the scientific method, that induction only arrives at postulates and so far as scientists ever reach new conclusions and hypothesis they must use deduction; so I don't think its fair to suggest that I did not allow that the modern social sciences use deduction at all. But I do not suppose that this is what Joe meant; rather he was referring to my argument that Homo Economicus is used for modeling and not purposes of deductive argumentation. Although I do admit that my point in this regard is a bit fuzzy (this is one of the reasons that I did not give you the Rabin paper as my original contribution; it didn't hold together that well), but I think I can at least bolster it up for the time being. Before I do though I have a quick unrelated response.

I would like to say that I did not suggest that "Rabin's paper [was] purely a quixotic exercise attacking a long-defunct economic model." Indeed I think the fact that the majority of modern economists utilize this principle was clearly implied in my paper. My writing "This [assumption that men rationally strive toward the maximum fulfillment of stable and well-defined preferences] is not, therefore, the basis of any sound systems of economic reasoning" does not imply that the majority of modern systems of economic reasoning do not rely upon this principle; it merely states that such systems are unsound. Nor does the statement, "The presumption that man acts always to maximize his rational self-interest is undoubtedly the single most frequently and most easily criticized tenet of any economic theory" imply that this tenet is not integral to the dominant economic theories of our age; it is only meant to say that these theories are frequently and easily criticized, and rightly so. I was not trying to suggest that Homo Economicus was a straw man in the sense that no one used him in their arguments; I was suggesting that he was a straw man in the sense that he is admittedly faulty and his explosion in no way affects the conclusions of proper (though perhaps not popular) economic theories.

In order to defend my characterization of Homo Economicus I will need to deal with some finer points of the definitions involved. In doing so I will draw upon Mises, so this section will also deal with the criticisms of Misesian/Austrian Theory that arise in Joe's response number III.

The definition that will be most important to us here is that of the term 'rational'. As Joe rightly points out Mises relies upon something that appears quite similar to Homo Economicus. The difference between what Mises proposes and the rational actor Homo Economicus is quite subtle. In fact, virtually all of the ways in which Mises differs from the classical economists are quite subtle, as they must be, for the classical economists were no fools. But it is most often Mises' most brilliant insights that are most quickly criticized by those who cannot help making the same mistakes that the classical economists have made. It is certainly true that on page nineteen of Human Action Mises states:

"Human action is necessarily always rational. The term "rational action" is therefore pleonastic and must be rejected as such. When applied to the ultimate ends of action, the terms rational and irrational are inappropriate and meaningless."

It is also true that this statement is absolutely fundamental to the entire body of work that is Human Action, but it is not true that the behaviorists can successfully criticize this statement. It is a definitional, not an objective, statement. His goal is to define human action, and here we must consult what he means by 'rational' as is elaborated on page twenty:

"When applied to the means chosen for the attainment of ends, the terms
rational and irrational imply a judgment about the expediency and adequacy
of the procedure employed. The critic approves or disapproves of the method
from the point of view of whether or not it is best suited to attain the end in
question. It is a fact that human reason is not infallible and that man very
often errs in selecting and applying means. An action unsuited to the end
sought falls short of expectation. It is contrary to purpose, but it is rational,
i.e., the outcome of a reasonable—although faulty—deliberation and an
attempt—although an ineffectual attempt—to attain a definite goal. The
doctors who a hundred years ago employed certain methods for the treatment
of cancer which our contemporary doctors reject were—from the point of
view of present-day pathology—badly instructed and therefore inefficient.
But they did not act irrationally; they did their best. It is probable that in a
hundred years more doctors will have more efficient methods at hand for
the treatment of this disease. They will be more efficient but not more
rational than our physicians."

This is to say that, by rational, he means that action is considered and supported by reasons. He is contrasting conscious action with unconscious physical response. When one ingests a toxin one does not weigh reasons and costs in determining whether or not to use one's biological defenses to attempt to break down the poison. You do not consider the pros and cons before blinking when an object comes flying at your face. These are not actions in the sense that Mises is speaking of. The principles that he demonstrates in Human Action are only true of conscious, volitional, and, in this sense, rational action. They are absolutely true with regard to action, as such, and they are of no consequence with regard to unconscious response. This is what Mises means when he says " Human action is necessarily always rational." In this sense the statement truly is pleonastic. The statement understood in this way cannot be refuted by behavioral observation.

It is in using a very different definition of rational in a very similar context that the employers of Homo Economicus make a concession to modeling. Although I must admit that this error was originally made by the classical economists who reasoned largely in a deductive fashion. It could only have been necessary for the development of objectively true predictive models. That is, the definition used by Mises is actually indisputable and hence, is an excellent building block for a deductive argument. The alternative, which we have labeled as Homo Economicus, is easily disputable and as such is not a suitable premise for deduction. But it does have other merits. If we assume rational to refer to a specific set of behaviors, those ideally suited to the achievement of specific goals, we can model human behavior. We can say that given goal A, there is only one behavior B, which is ideally suited to the achievement of this goal. If we then assume that man is, in this sense, rational, we can, given his preferences, predict exactly his behavior. The assumption that man is rational in this sense is indisputably false.

Now moving on to the criticisms of Human Action not related to Homo Economicus. We arrive at the quote:

"Concrete value judgments and definite human actions are not open to further analysis. We may fairly assume or believe that they are absolutely dependent upon and conditioned by their causes. But as long as we do not know how external facts--physical and physiological--produce in a human mind definite thoughts and volitions resulting in concrcete acts, we have to face an insurmountable methodological dualism"

Again only by misinterpreting this quote can it be criticized. It comes from the section explaining that we must consider human action to be an ultimate given. This is true because we do not understand its causes. We cannot penetrate the barrier of human action in our economic reasoning so we must acknowledge this fact. We cannot say, based upon our analysis of the firing of neurons, whether an individual will buy a Ford Taurus or a Honda Accord. We cannot predict whether a person will choose to work overtime or go golfing. Thus "concrete value judgments and definite human actions are not open to further analysis", and they will remain so "as long as we do not know how external facts--physical and physiological--produce in a human mind definite thoughts and volitions resulting in concrete acts". I did not think that the behaviorists had achieved such things but perhaps I am just ill informed. Indeed, the sentences that complete the paragraph from which the above quote was taken make it quite clear that Mises does not necessarily consider understanding the underlying causes of human behavior as "futile" (as I do), but merely as a task yet to be accomplished:

"Concrete value judgments and definite human actions are not open to
further analysis. We may fairly assume or believe that they are absolutely
dependent upon and conditioned by their causes. But as long as we do not
know how external facts—physical and physiological—produce in a human
mind definite thoughts and volitions resulting in concrete acts, we have to
face an insurmountable methodological dualism. In the present state of our
knowledge the fundamental statements of positivism, monism and
panphysicalism are mere metaphysical postulates devoid of any scientific
foundation and both meaningless and useless for scientific research. Reason
and experience show us two separate realms: the external world of physical,
chemical, and physiological phenomena and the internal world of thought,
feeling, valuation, and purposeful action. No bridge connects—as far as we
can see today—these two spheres. Identical external events result sometimes
in different human responses, and different external events produce sometimes
the same human response. We do not know why.

In the face of this state of affairs we cannot help withholding judgment
on the essential statements of monism and materialism. We may or may
not believe that the natural sciences will succeed one day in explaining
the production of definite ideas, judgments of value, and actions in the
same way in which they explain the production of a chemical compound
as the necessary and unavoidable outcome of a certain combination of
elements. In the meantime we are bound to acquiesce in a methodological

Even if the behaviorists where to explain the underlying causes of human behavior the act would render Mises' work incomplete rather than false.
Before going, for a moment, on the offensive I will cover the final Mises quote in III:

"whether or not the means chosen are fit for the attainment of the ends aimed at." (p. 21)

This statement is not, originally, used in reference to human behavior or human rationality, but with regard to the science of human action itself. Putting the quote into context is again quite useful:

"In this sense we speak of the subjectivism of the general science of human
action. It takes the ultimate ends chosen by acting man as data, it is entirely
neutral with regard to them, and it refrains from passing any value judgments.
The only standard which it applies is whether or not the means chosen are fit
for the attainment of the ends aimed at."

In fact, if one were to assume that human action where always perfectly suited for the attainment of the ends aimed at, this statement would be nonsensical, as the science of human action would be entirely superfluous. Mises is not an idiot. He is saying that the science of human action is neutral with regard to ends and that its object is to help man choose means that are suitable to attain his ends whatever they might be.

Now I would like to take a moment to analyze the following statement from III:

"It is precisely the claim of the behavioralist that an individual's actions do not rationally correspond to that individual's own value judgments. It is not a matter of imposing outside values (which Von Mises here argues against), but merely questioning the validity of assuming the rationality of action as defined by consistency with the desires and value judgments of the actor."

How do the behaviorists determine what a person's value judgments are? I suppose they must ask the individuals. But then, responding itself is an act. How can the researchers be certain that it is in the response to the question "What are your value judgments?" that an individuals true interests are represented rather than in their subsequent actions? Is it not possible that a person's value judgments change with time and that their actions are consistent with their valuations at the moment of action? Could the truth not also be that people are not generally capable of (or willing to) accurately identifying their own value judgments? If a man says that he values, above all else, his income, and then, on Sunday morning, he goes to church is he acting irrationally? Or is he simply more clearly aware of his desire for income than his desire for a reduction in his fear of death and uncertainty, or perhaps his valuation of social approval and conformity. If a man (who states that his objective is to maximize the quality of the VCR he purchases relative to his dollar cost) buys the more expensive of two VCRs when, had a third option, cheaper than the other two, been available, he would have chosen the middle alternative, is he truly acting irrationally or, is it possible, that he is optimizing preferences that he did not know how to express. Perhaps he should have said that he would also prefer not to have to spend too much time learning about VCRs. In accordance with such a preference he may have made his decision based upon a rule of thumb that is different in a case where three options are present than if two are. Perhaps one rule is that one should never buy the lowest cost alternative for such a product is generally shabby and inferior and the ownership of such a thing is popularly regarded as shameful. The second rule of thumb is that one need not purchase the most expensive option, as this is extravagant and wasteful. In a case where only two alternatives exist the two rules cannot be satisfied simultaneously and the first rule is a more significant value for this individual than the second. Thus he buys the more expensive VCR. In the case with three options he may satisfy both rules and thus he buys what in the first case was the least expensive VCR. One cannot say that, within the context of these explicit valuations, his decision was irrational. One might say that it is irrational to hold the contradictory values of trying to obtain the finest product for the least money and making the purchase while learning as little about the product as possible, but this would require the observer to impose a value judgment upon the actor.

Indeed as a heuristic exercise view yourself introspectively. In every action are you not optimizing your own satisfaction? If you tell others that you are striving to succeed in a given course and then you skip class, or ignore an assignment, have you done so out of a failure to recognize that the action will bring about results contrary to your goal? Or is the case merely that you have experienced a preference that overrode your initial desire to succeed in the course, such as a desire for leisure, a desire to spend time with a girl, or a desire to go drinking with your friends? Is it reasonable to expect that, asked the question, "What are your preferences?" you will accurately enumerate all of your actual preferences and be able to order them in such a way that will be universally true? It seems far more rational to say that if in circumstances A I choose to skip class and stay in bed the action itself represents my true preference. At the moment that I declared my intention to succeed in my class I may have been absolutely sincere, but I am equally sincere in my valuation of sleep over the class when I turn off my alarm and roll over.

Returning to the case of the VCRs, we have seen that to choose two different VCRs in what are technically the same circumstances can be a rational action. There is no objective way to determine which VCR was a better value in an absolute sense, and from the perspective of the buyer the cases were substantially different; he operated in accord with his actual values. A person may act differently in a crowd than they would if they were alone, but are they violating their preferences or are their preferences for conformity and acceptance overriding the preferences that would have been dominant in the absence of the crowd? To declare that a person's actions contradict their values and desires presumes that the critic understands the actor's values and desires; a premise that I hope I have demonstrated is highly suspect. It is just this sort of false certainty that deludes the followers of the social sciences. Mises' work is truly scientific because of the extraordinary care that he takes not to assume the veracity of what is not certain.

Post Script

Thank you again for taking the time to consider my ideas. I understand that I have been running a bit long but it is a great pleasure for me to put these ideas into writing. I hope that you will continue to spend some time in critical response. There is no better catalyst for clear thought than external challenge and review.

I would briefly like to advertise the work of Ludwig von Mises. As Joe indicated, his primary work Human Action (and many secondary ones) is available for download at It is a bit long and you might prefer to buy a hard copy but it is well worth the read. In the context of my experience I would say that it is the finest philosophical work of the twentieth century. You may disagree, but if you are a logically minded person you will not be able to stop yourself from admiring the rigorous consistency and conceptual breadth of his work.

Sunday, March 20, 2005

Re: A Critique of Social Science

Once again, I find myself strapped for time (the Madness of March has inflicted me) and so I can only offer limited comments on the very heady posts of late. My objective in this post is to highlight my views and concerns, particularly where they may differ from Henry's or Joe's. I hope this conversation keeps going so that I can add more later without the conversation having long past into the archives.

First, Henry, your post was very impressive and thought-provoking. My immediate concern is that I am not really sure what are the dividing lines between the physical sciences and the social sciences. My best guess is that you would say that a social science is that which is not susceptible to the scientific method -- if in fact that is your position, I would recommend the term "humanities" instead. Social sciences like psychology and sociology have made important advances through the scientific method, and I believe it is unfair to discard the entire field because not all academic inquiry within a field meets rigorous scientific inquiry.

Second, I believe that the softer sciences play an important role in the development of understanding, although I readily agree that many conclusions that social scientists reach extend too far. As Joe noted in a recent post, the same can be said for the frontier of natural science. In my view the criticism you make is better framed as one of overreaching. Yet that overreaching is what causes the next generation of the curious to challenge existing claims and add to knowledge.

Third, I disagree that the objects of study within social science are chaotic, at least any more so than the materials studied within the natural sciences. I recognize that strictly, a system cannot be "more" or "less" chaotic, but I believe what we see as an impenetrable morass of complexity may become coherent through advances in technology. For instance, neuroscience has allowed us to better understand human behavior and will continue to add to our genuine knowledge. Even if there are many variables that play into a complex system, there may be ways to isolate one or several events to demonstrate a causal relationship. I do not understand chaos theory that well, and maybe someone with better understanding of the subject could explain, but it seems to me that understanding a complex system must begin somewhere, and chaos theory allows a starting point.

I think Henry's post will give us fodder for discussion for a long time to come. I would find it helpful to take a point at a time, and Joe has offered some good counterpoints (most of which I stand behind) with respect to behavioral economics. Maybe we can focus on that point for starters and work from there.

Saturday, March 19, 2005

Re: A Critique of Social Science (part III)

In an effort to get to the bottom of the Austian theory I went to and downloaded Mises' Human Action. I hardly have time to digest the entire thing, but I figured I'd read through the first 20 pages or so, and in doing so struck upon a passage that describes precisely the challenge offered to Austrians by behavioralists. The Austrian theory apparently is built entirely upon the analysis of (surprise) human action. They do indeed dispose of the need for rational utility maximizing preferences, however, they do so by imputing those preferences into action:
Human action is necessarily always rational. The term "rational action" is therefore pleonastic and must be rejected as such. When applied to the ultimate ends of action, the terms rational and irrational are inappropriate and meaningless. The ultimate end of action is always the satisfaction of some desires of the acting man. Since nobody is in a position to substitute his own value judgments for those of the acting individual, it is vain to pass judgment on other people's aims and volitions. No man is qualified to declare what would make another man happier or less discontented. The critic either tells us what he believes he would aim at if he were in the place of his fellow; or, in dictatoria1 arrogance blithely disposing of his fellow's will and aspirations, declarcs what condition of this other man would better suit himself, the critic.
Mises, Human Action, p. 19.

It is precisely the claim of the behavioralist that an individual's actions do not rationally correspond to that individual's own value judgments. It is not a matter of imposing outside values (which Mises here argues against), but merely questioning the validity of assuming the rationality of action as defined by consistency with the desires and value judgments of the actor. My online dictionary turns up the following definition of rational: Consistent with or based on reason; logical. Behavioralists question whether all action is actually consistent with or based on reason and logic, as Mises flatly assumes that it is. Mises also states:
Concrete value judgments and definite human actions are not open to further analysis. We may fairly assume or believe that they are absolutely dependent upon and conditioned by their causes. But as long as we do not know how external facts--physical and physiological--produce in a human mind definite thoughts and volitions resulting in concrcete acts, we have to face an insurmountable methodological dualism.
Mises, Human Action, p.18.

Beyond assuming that action is necessarily rational, Mises believes it futile to try and determine what cognitive processes lie behind action. Behavioralists disagree. Their experimentation on this matter, while, as previously discussed, falling short of full scientific rigor, provide results that should certainly be troubling to Mises in his claims above. This, I think, poses a serious challenge to the Austrian theory of action and ought not to be dismissed out of hand. Am I wrong on this?

Moreover, I think it is a challenge that Miseians would be hard-pressed to answer. I fail to see how the Austrian school avoids any of the problems of rationality attributed to Homo Economicus. The difference, it seems to me, between the Homo Economicus theory and the subjectivist Austrian theory is merely in their analysis of the desired ends of human action. Homo Economicus, I take it, assumes that actions are directed towards wealth maximization, whereas the subjectivists don't care what the objective is, but only "whether or not the means chosen are fit for the attainment of the ends aimed at." (p. 21) Both theories, however, assume rationality in pursuing their chosen ends, and both are therefore subject to behavioral defects.

Friday, March 18, 2005

A Backdoor Entrance For Legal Marijuana

Slate has an article by Tim Wu (the guy I had hoped to work for this summer) on the possibility that the WTO could find U.S. drug policy to be an illegal barrier to free trade. He builds a fairly strong legal case for WTO intervention, but for political reasons I can't imagine it happening until Canada and other like nations go from mere nonenforcement of anti-drug laws to outright legalization.

Re: A Critique of Social Science (part II)

In this episode I'd like to consider what exactly is the complexity barrier and where it lies. It seems to be that the idea of the barrier is easily stated, but determining where it lies is less simple. The barrier marks the boundary between phenomenon which yield to rigorous scientific experimentation and those too complex for experimenters to isolate significant factors or where no experimentation can be done. Henry is basically correct in placing the social sciences on the untestable side. V argues that this characterization is overinclusive and that there are some meaningfully testable social science findings. I'm willing to buy his premise, but I don't know of any particularly good examples, so I'll leave that discussion for him.

However, I think that while this barrier tells us something important about the social sciences, it does not stand as a wall between the social sciences and the physical sciences. Significant parts of the physical sciences also fall on the untestable side, or in the gray middle ground. The medical sciences serve as a particularly good example. Epidemiological studies resemble in many ways the sort of data obtained by social scientists, and come with many of the same caveats with regards to the difficulty of isolating significant factors. Even many smaller drug tests suffer these flaws, though to a smaller degree. Blind tests and control groups add a good measure of rigor to these tests, but cannot claim to isolate interfering factors in any absolute way. We don't completely understand the causal mechanics of many afflictions, drugs, and treatments, and can only measure their effects on people, an inexact process. Additionally the vast realm spanning neurology (a physical science) and psychology (a social science) is difficult to characterize decisively as testable or nontestable. Ryan may know something of this.. :)

Other physical sciences also encounter barriers of testability. String theory, for example, is a popular topic of physics, but has so far not yielded to any useful testing. Likewise, cosmology is an entire field built around untestable theories. Cosmologists gather immense amounts of data against which to compare the predicted results of their theories, but they remain unable to ever perform actual experimentation.

The matter of what qualifies as a scientifically rigorous test that sufficiently isolates relevant factors is something of a philosophical question. We can't know, even in a high school physics experiment on acceleration whether aliens are firing a gravity gun from orbit at our ball, skewing results, or whether the supposed constants of the universe vary over time, and perhaps today was just a heavy day in the universe. But we reasonably decide to dismiss concerns about such improbable factors and consider this experiment to be rigorously scientific. While my example is silly, I wonder how far this judgment extends and how we define the boundary.

It also is interesting to note that in many of these cases the barrier of testability shifts over time. MRI's, electron microscopes, particle colliders and other technological tools have shattered barriers of testability in many fields. In other cases all that might be needed is a new insight into the predicted effects of a theory (i.e. string theory) that would yield a testable phenomenon.

None of this is to suggest that the social sciences are any more rigorous than Henry stated. However, I think it is inaccurate to level this criticism only at social sciences as compared to the physical sciences. It is an important barrier, and an enhanced awareness of the barrier would be useful to people employed in the sciences, or interested in them. The truth value of a claim in a testable field is obviously different from the truth value of a claim in an untestable field, and it would be helpful if more people were cognizant of the distinction.

Wednesday, March 16, 2005

R.J. Samuelson: Still My Hero

I don't know of another columnist who selects more relevant and important topics or so effectively analyzes the core issues of those topics without ever revealing partisanship. This week he takes on the state of global trade.

Re: The FCC Can't Rule The World

The D.C. Circuit ruled today to allow challengers of the FCC's impending broadcast flag requirement (previously reported on BWJ here) an additional two weeks to demonstrate valid standing. Dissenting, Judge Sentelle argued that the case should have been dismissed on standing. :)

Sunday, March 13, 2005

Re: MGM v. Grokster

As a follow-up to the discussion on the Grokster case, I came across this article in the Washington Post observing that BitTorrent, the next stage in the evolution of filesharing programs, is being embraced for its legitimate commercial use. That means whatever happens with respect to the Groksters of the world, BitTorrent is likely here to stay.

Re: A Critique of Social Science (part I)

Hank, sorry it's taken so long to respond on this. You've got a lot of interesting stuff there. I agree with the general assertion that there is some barrier of irreducible complexity beyond which the scientific method cannot yield verifiable results, and that as a general matter the social sciences fall on the wrong side of that barrier. I like your thought that deductive arguments should be given greater consideration in social sciences, and that it is possible and desirable to more frequently argue from first principles.

I was just talking with Mr. Veritas about this, and we formulated a number of criticisms. In some instances your theory seems underinclusive (i.e. much of this criticism could apply to elements of the hard sciences), in others, overinclusive (experimentation in social sciences can uncover something of truth). Implicit in that discussion is exactly what composes this barrier of complexity, and where it precisely lies. I think it's also an interesting question to what extent that barrier is malleable based on technological capability and keen insight. I am also not sure that we know that there are significant quantum effects that govern the operation of the brain which would place human behavior conclusively on the far side of the complexity barrier. V raises the question of whether Chaos Theory can shine any light on complex human interactions despite the inability to model a single human. Also, I'm not certain that the application of research in the social sciences is as separate from deductive reasoning as you suggest. I'm going to address this last point now, with the added hope of fleshing out your theory through some discussion of application. I will try to take up some of the other topics in the coming week or two as time allows, I know V is hoping to post some on this, and we're hoping to drag Ryan in as well, particularly on the fact questions relating to the brain and chaos theory.

First, I disagree with your characterization of Rabin's paper as purely a quixotic exercise attacking a long-defunct economic model. The rational, utility-maximizing actor is a staple of Western economic theory (although apparently not the Austrian theory). I would very much appreciate it if you could elucidate the basic deductive argument for Mises' irrational capitalism. I understand that as an advocate of the Austrian School, you reject Rabin's position for the reasons you stated, but as your audience is not necessarily familiar with (or in agreement with) the Austrian economic theory, we would be well served to hear where the foundation lies, if not on rational actors. The balance of the criticism of Rabin's positions seems largely reliant upon this.

Moreover it doesn't strike me that Homo Economicus is a concession to modeling. As far as I can tell, he rather resembles a deductive device. As an example here is a premise from James Mill's deductive argument for democracy (my paraphrase): Human beings apply accessible government power (rationally) to serve their own pleasure and avoid pain. The premise of Homo Economicus (again, my paraphrase): Human beings act (rationally) in markets to serve their own pleasure and avoid pain. These sound very similar to me. I know the former is an element of deduction, why not the latter? On what distinction do you separate Homo Economicus from a premise of deductive argument and name it a predictive modeling approximation? To the extent that Rabin is criticizing a deductive premise, is he not applying research in the role that you suggest for the social sciences?

I also don't see the inherent conflict between relevant data and calculable data. It is indisputable that deductive arguments call up many controversies of fact (see any legal decision). It is also true that some issues of fact are more critical in a given argument than others, and that some issues of fact yield more easily to research than others, and finally that the ones more easily researched are not necessarily going to be the ones that are most critical. However, I see no problem with researchers, faced with this dilemma, plucking the low-hanging fruit. If some premise of the argument is easily assessed through research, why not engage in that research even if it is not the most critical premise? Some premises will necessarily remain within the realm of rhetorical debate indefinitely (or nearly so), but those for which useful insight can be gained through research should be examined. There is the possibility that undue focus and disproportionate resources will be applied to those areas which do yield insight through research and experimentation, and I agree that this could be a problem. However, this is a problem of resource allocation, and I don't think taints the results of the research.

I'll hold off until hearing more of the Austrian School before really engaging this issue, but my feeling is that the rational maximizer is a fundamental underlying premise of nearly all Enlightenment social, political, and economic thought -- fundamental to the point of frequently going unstated. And thus data that suggests limits on the rational maximizing function carry wide-ranging ramifications. I would also suggest, that behavioral criticism aside, the rational maximizer is a generally defensible, useful, and important premise.

p.s. Mr. V highly recommends the book Consilience by Edward O. Wilson on this topic. Hopefully he'll say more on that. If you get a chance you might check it out and provide some feedback.

Thursday, March 10, 2005

Re: MGM v. Grokster

I wish I had more time to comment on this issue than I presently do, but I wanted to take a moment to share my thoughts after reading the 9th Circuit decision and some of the briefs submitted to the Supreme Court.

I find the issue of substantial noninfringing use to be a tougher issue than Joe does. In Sony-Betamax, the infringing use was relatively minor in comparison to the lawful use (in that case, the ability of consumers to "time-shift" content was deemed fair use). With respect to the P2P software, the noninfringing use, although real, is very small when sized up against the infringing uses of the software. That forces the Court to evaluate how much noninfringing use is enough--a particularly vexing problem considering the Congress has given the Court no meaningful direction. At the end of the day, I believe the Court will likely conclude that so long as the noninfringing use provides some meaningful benefit, that will be enough. Otherwise, the Court may wind up discouraging innovation and technology, and I am sure they are hesitant to avoid that consequence.

Second, it seems important that the software distributors are still profiting from their programs and that they have released numerous upgrades, each of which have allegedly facilitated infringement rather than attempted to correct it. Because this is case is only at the summary judgment stage, I believe the case will be reversed and remanded if the Court concludes the copyright holders have demonstrated a genuine issue with respect to those issues (the ongoing profits the software distributors receive and the upgrades that have facilitated copyright infringement). I do not know whether these claims are true, but from the briefs of the copyright holders it sure seems likely they will prevail.

I want to give this stuff some more thought, but that is my initial view anyway.

Saturday, March 05, 2005

A Critique of Social Science

After a couple of abortive attempts at producing a tightly written essay explaining why I do not believe that the social sciences are sciences by any stretch of the imagination I have decided to put forth an informal compiling of reasons. This approach has the advantageous characteristic of ease of writing thus assuring that I will finish it. Perhaps critical review will help me to shape it better. I was simply unable to work out a satisfactory framework that would put my criticisms into a logical order.

I will begin with the obvious criticism to which all of my other criticisms may be linked. The events examined by social scientists are infinitely complex and thus are not subject to the methods of the physical sciences. That is, an essential characteristic of a properly conducted scientific experiment is that all significant variables are cataloged and controlled and this is not possible when the system includes a human being. This is obvious, though I will explain briefly so that no one may doubt the truth of it.

First I refer to physics, as it is the most fundamental of the physical sciences and its very simple systems yield best to the methods used in the physical sciences. In physics the events described are always very simple. They involve a handful of uniform particles or some like thing, but in order to describe these exceptionally simple systems physicists must utilize mathematical equations that are virtually unrivaled in complexity among any of the other physical sciences. The human brain is, in terms of complexity, to these simple systems as a supernova to a flickering candle. And the relationship between the difficulties involved in explaining a system and the number of relevant variables is not linear, it's exponential. Thus if we need a super computer to describe the almost unthinkably simple systems explained by physics we would need a quantum computer the size of a city block to describe the human brain. But this over simplifies the task at hand.

~> Read More!

In reality even a perfectly efficient computing machine the size of the entire universe could not predict the behavior of a single human brain. First, one could never produce the input data necessary to prime the system. This is because perfect knowledge of the initial state would be essential for making sound predictions, while Heisenberg's uncertainty principle assures us that we can never achieve perfect knowledge of the initial state. Furthermore, even if we were to magically obtain the necessary data, our computations would immediately begin to run contrary to the actual behavior of the system due to quantum level effects. That is, on the quantum level the universe is not mechanistic but probabilistic. Thus future states could only be determined to be more or less probable (a weak reward for having turned the entire universe into a brain simulator). I leave contemplating how much more complicated the combined interactions of the polities of the human race may be as an exercise for the reader.

At this point hopefully you are thinking, of course we cannot predict the outcome of an individual decision making process with absolute certainty. This is not necessary; all we need is a decent approximation, one that will yield better results than our current approximations. This would be sufficient reward to justify our efforts. Unfortunately this too is impossible. In order to demonstrate this we need only think about the nature of a chaotic system.

The American Heritage Dictionary provides the following as the mathematical definition of chaotic: A dynamical system that has a sensitive dependence on its initial conditions. That is to say, in a chaotic system, seemingly insignificant alterations in the initial conditions will lead to profoundly significant differences in later states. The brain is a chaotic system. In a chaotic system small approximations will lead to colossal failures of prediction.

In physics mathematical approximation is justified. To understand the behavior of a gas in a balloon it is useful to consider the average velocity and mass of the particles constituting it. To understand the behavior of a parliament it is not at all useful to consider these properties with regard to the members that constitute it. When considering the expansion of the balloon the exact disposition of each particle is of no consequence, indeed, if it was, the science of thermodynamics could not exist (for the movement of an individual particle in a gas is highly chaotic and would far surpass our powers of calculation). When considering an action of the parliament any minutest detail of the disposition of its members may be of great significance and thus a mathematical science of politics is misguided.

In a highly complicated system virtually all variables are interdependent and their importance with regard to the desired output are also highly variable. Thus what appears for a period of time to be the most significant variable may, at a seemingly random time become far less important while some obscure and unconsidered variable may move, for a period, into prominence. Indeed, it is certain that the majority of variables in such a system are connected to one another in exceedingly complicated ways such that the particular convolutions of the system must remain mysterious. Thus a ten variable or twenty variable or one-hundred variable model will inevitably fail to encompass variables which are of primary importance in determining the outcomes of the system. The physical sciences use controlled experiments because any significant variable that is unaccounted for will ruin the value of the data; in the social sciences the very idea of a controlled experiment is ludicrous. Richard Feynman, in a speech attempting to explain why the social sciences fail[1] explains that it is the scientist's duty, if he wishes to achieve meaningful results, to carefully document all of the reasons why his conclusion may be unjustified. This he rightly notes is not common practice among social scientists. This seems understandable, for a scientist might exhaust his entire career trying to exorcise all of the potential sources of error in any social science experiment. But this is, of course, the point. If social scientists had been scrupulously honest with themselves from the beginning they would never have gotten past the first experiment for they would still be accounting for uncontrolled variables.

Another problem can be seen when one looks at what happens to the data available when social scientists try to subdue it with mathematics. This is that the data gets selected. This is not necessarily a bad thing. It depends upon the criteria you are using to select. For instance, a good criterion would be relevance. But this is not the criterion that mathematical computation forces upon social scientists. No, that criterion is numerability. Those data that can easily be quantified become weighted as exclusively important and those that do not yield to numeration are categorically excluded. But in the subjects of social science there are many non-numerical inputs that are of critical importance. This is always true of an epistemology, it filters the input data accepting only those bits that are amenable to it's methods; to a man with a hammer everything looks like a nail. The obvious truth though is that there are many factors that are of critical importance in a social science that must be ignored if one wishes to make the field amenable to calculation. Here I am reminded of one of my earlier attempts to broach the subject of the failures of the social sciences:

An Essay Motivated by a Reading of Psychology and Economics by Matthew Rabin
Matthew Rabin’s criticisms of Standard Economics, though neither new nor innovative, are perfectly apt and well considered. The assumption that men rationally strive toward the maximum fulfillment of stable and well-defined preferences is indeed absurd. This is not therefore the basis of any sound systems of economic reasoning. Rabin’s suggestion that models based upon this postulate should be revised to accommodate the inconsistencies that he observes is noted and rejected upon the basis that even such a revised model would be so seriously flawed as to be useless. The error in Rabin’s reasoning resides in the presumption that an accurate and useful model of human economic behavior is attainable. All reasonable and useful economic theories, such as that of Ludwig von Mises are composed, explicitly, without the inclusion of this erroneous belief.

The presumption that man acts always to maximize his rational self-interest is undoubtedly the single most frequently and most easily criticized tenet of any economic theory. Man acting in this way has long been referred to as Homo Economicus and one can get the flavor of this long-standing debate by reading the astonishingly pertinent Wikipedia entry regarding that term (this being the first item on the list when one googles Homo Economicus). Of course, it is quite likely that Rabin was fully aware of the history of his paper’s topic and went ahead with publication because he believed that it made a useful contribution to the aforementioned debate.

For our purposes it will suffice to understand why someone made this assumption, so idiotic, so obviously contrary to truths observable both internally and externally by all human beings, in the first place. The answer is, of course, that it is a simplification, the bread and butter of the modeling so essential to the epistemology of mathematical induction. That is, without such an assumption, economic calculation would not have been possible. It is certainly a stupid assumption, given that it removes the very essence of the phenomenon being described. But it is a very useful assumption inasmuch as it enables economists to construct predictive models. Unfortunately those models describe only the imaginary Homo Economicus and not his more substantial cousin Homo Sapiens.

It was Rabin’s intent to use recent findings in the field of psychology to illuminate some of the improvable flaws in theories generated using this assumption. He thought that, so long as this idea could not be discarded without giving up on all attempts to model human economic behavior (to his thinking, clearly, the only way to advance our knowledge of the subject), the least we could do was add back in some of the significant terms that had been eliminated by the original simplification. Prior to the discoveries that he highlights in his paper this was not possible. The irrationalities, failures to act in a properly self-interested fashion, and fleeting or uncertain preferences that had been excised in order to create Homo Economicus had been removed for a reason. They were not subject to numeration. The innumerable is the kryptonite of the mathematical modeler. Rabin’s insight was to recognize that psychological researchers had begun to shed some mathematical light upon a handful of previously indescribable phenomena. He suggested that perhaps some enterprising economists might set about reattaching these bits to Homo Economicus.

These bits, which might be reincorporated into Homo Economicus, are those irrationalities that happen to be easily quantifiable. As such they are useful to modeling economists. Unfortunately the rubbish bin is still full of the difference between Homos Economicus and Sapiens. These are the differences that aren’t so easy to quantify. These differences are still more than sufficient to sink any theory based upon Homo Economicus 2.0. “Wait” Rabin might exclaim, “ I understand that this model is still incomplete, but economics requires models that are not so rich as to retard the process of drawing out their economic implications. For a discipline such as economics that places a high premium on the logic and precision of arguments and the qualification of evidence, incorporating all facets of human nature is neither attainable nor desirable.” But, what Rabin would be failing to comprehend is that precise logical argumentation is an epistemology that requires all relevant information to be considered. He would be hoping to create algorithms that will solve brainteasers without all of the necessary clues. I am put in mind of some amusing words of Charles Babbage, “On two occasions I have been asked [by members of Parliament], 'Pray, Mr. Babbage, if you put into the machine wrong figures, will the right answers come out?' I am not able rightly to apprehend the kind of confusion of ideas that could provoke such a question.” Rabin is attempting to employ a methodology that he does not understand. The characteristic that determines whether a given datum would be included in the model is not relevance; it is calculability. Thus, rather than allowing his data to select his epistemology he makes his epistemology select his data. In paying undue reverence to a methodology he sacrifices the end to the means.

Homo Economicus is not an approximation in any scientific sense; he is a fiction. An approximation simplifies (or makes possible) calculation at the expense of an increased margin of error. Using models created with Homo Economicus it is impossible to calculate a margin of error. Economic modelers throw out the baby with the bathwater and the proof is in the pudding. If you wish to know the future state of the economy you may as well consult an astrologer as a modeling economist. Rabin’s observations do not constitute the vanguard of a coming influx of successful quantification techniques but merely the continuation of a constant stream that has flowed since the dawn of inductive mathematical Economics, an ongoing process of adding refinement upon refinement in the hope that superior results will be achieved. Superior results were not achieved, have not been achieved, nor will they ever be achieved so long as Economists persist in the application of inductive mathematical methods. The formula that those economists are looking for is infinitely complex and chaotic and if they were ever able to discern it its implications would be incalculable. Seemingly insignificant variables would form endlessly diverse combinations to trigger extremely significant events. Physicists use mind bogglingly complex formulas to explain systems which are almost unimaginably simple and, given that each additional factor increases the difficulty geometrically, one can safely assume that, in terms of complexity, the most complicated system understood by physics is to the state of human economy on earth as the fart of a mouse is to the big bang.
This excerpt reiterates some of the points that I have already made above and provides a concrete example of inappropriate data selectivity. The problem is that the epistemology that the social scientists adopt forces them to eliminate critical data from the field of their consideration. It is undoubtedly true that paternal love, sexual love, hatred, pride, fear or any number of other factors could each, at times, be the single overriding factor in determining an individual's actual behavior. But it is equally true that any quantization of these factors must be arbitrarily and subjectively assigned and thus could not appropriately be utilized in mathematical models. Thus mathematical models, the cornerstones of the physical sciences, are not useful in the social sciences.

One might yet claim that, although there are many uncontrollable factors in any social scientific experiment we may yet, by averaging, reduce the net influence of the uncontrolled factors to a level of insignificance. This too is false. Many factors will indeed vary randomly among the test population and for these factors the preceding assumption is largely true. But for many other factors, those which change slowly or discontinuously, this will not be true. Many things will be nearly constant among the study populations (exemplas g. they have seen a Coca-Cola advert, they have watched television, they are familiar with objective patterns of though, they have never hunted their own food with weapons of their own making, they have not lived outside of a fiat currency system), the effects of these factors will not be averaged out, nor will the experimenter have any sense as to which of them are significant. This is to say; the events of the experiment are neither controlled, nor repeatable. From such an experiment one may draw no logically appropriate correlations. The results will not be universally applicable, and the boundaries of their applicability must remain wholly unknown.

The sum of these arguments is that inductive experimental claims about the subjects of the social sciences are not entitled to any greater validity than subjective statements based upon historical or personal experience. For the argument against the validity of such subjective statements is that they don't account for the uncertain vicissitudes of the phenomena from observations of which the conclusion was drawn, and the same criticism applies equally well to experimental social science.

I will devote the remainder of these pages to answering, as best I can the following questions.

Why, if the methods utilized by the social sciences are invalid, have so many people subscribed to them for so long?

If the methods currently utilized by social scientists are misguided is there any method of reasoning that can result, with regard to social organization, in assertions the validity of which are greater than mere subjective assertions?

The origin of the social sciences is clearly rooted in a false analogy; the objects of the analogy being simple and complex natural phenomena.

The justification of the validity of the physical sciences was functionality. Prior to the rise of the modern scientific method many competing epistemologies strove to explain the cause of events in the material world. Some of these epistemologies justified more than one explanation, some countless explanations. The arrival of the objective inductive scientific method changed things. It changed things because it worked. It made predictions, and those predictions were verified by observation. Thus, in accord with the long-standing trend of cultural admission for notions that allowed individuals to successfully adapt their behavior to physical reality, the notion was admitted. The arrival of this epistemology radically transformed man's interactions with his environment. It allowed technological innovations, which previously had been enabled only by infrequent acts of subjective intuition and random chance, to be developed selectively and at will. Such a powerfully transformative notion necessarily rose to unrivaled transcendence. It is undoubtedly the core of our modern civilization.

The victory of objective inductive science also had negative consequences. It produced a willful blindness. Other epistemologies, useful within their own sphere, were cast into the dustbin, their failures exposed by the light of the new favorite. But the failures of these epistemologies were due, not to their inherent disutility but rather to their misapplication. This subtlety was lost upon the new science's enthusiasts. The new epistemology, rightly beloved by all right minded intellectuals, was unthinkingly raised to a dogmatic and unjustified supremacy. The same love-blinded enthusiasm that had induced the early philosophers to attempt to deduce the nature of the stars and of life itself led the epigones of the natural philosophers to attempt to induce the nature of man and of correct action. Thus the same sickness that befell the deductive reasoners, that of presuming the existence of a universally valid epistemology, befell their inductively reasoning descendants.

The thinkers of the nineteenth century wrongfully concluded that the epistemology that so successfully explained the simple natural phenomena so critical to proper development of useful technologies must prove equally apt when one sought to explain the more complicated phenomena that govern how and why technologies are used. After all, the two categories of phenomena differed only in scale and complexity. It seemed only natural that, just as objective science had moved from explaining very simple phenomena to progressively more involved systems, so it might proceed on through the most complex occurrences observable. Their intuition was wrong. They failed to grasp the full measure of those more complicated systems. As the complexity of systems increase the possibility of objective validation of hypotheses rapidly moves from being possible for man to being possible only for a hypothetical perfect intelligence. But the question remains: why, more than a century hence, do individuals persist in believing what is surely false?

Intellectual success led to a growing complacence; an eagerness to proceed as rapidly as possible toward more perfect understanding brought about a willingness to bypass the roots of knowledge. As the branches of knowledge grew more diverse and numerous it became generally accepted that it was sufficient for each researcher to be familiar with the growth of his own branch. But this required an implicit faith in the support and integrity of the confluent super branches, the trunk, and the roots. By the time the social sciences were conceived this tendency was in full bloom and the fathers of the new field began to work as if they were merely sprouting a new branch from the old trunk. What they failed to realize was that the newly grafted branch was an entirely different species. It derived no nourishment from the trunk and thus had no connection to roots. But they lived, and we still live, in an age in which it was (and is) almost unthinkable that one might question the epistemology of empirical science. It is the modern religion. Thus, one reason that the fallacious social sciences persist is that it is no longer routine to argue from the roots of knowledge, as was quite fashionable in the age of deductive reasoning. But once again a question arises: if the methods of the social sciences are bunk and they yield no real results why have people not forsaken them?

It is obvious that men are inclined to proceed unquestioningly in acquiescence to popularly established modes of thought. It is also clear from an examination of nineteenth century discourse that the concept of social science rapidly rose to widespread popularity. Thus one reason that the false science was propagated might have been the assumption among those rankled by uncertainty that, ranked among the countless multitudes of believers must be many individuals wiser than themselves who had seen to the roots of the matter and were certain of the validity of the social sciences. This avenue is all the more plausible when one pauses to examine modern academia where implicit faith in the validity of methods and results abounds. This may be linked to the common belief that the division and expansion of knowledge have made pursuit of the roots of ideas impractical but this is merely a lazy fallacy. Although a great tree may possess a massively intricate and diverse tangle of branches, and their combined length may encompass miles, the distance from the tip of the tallest branch to the roots is never very far. Yet again this explanation is incomplete, ideas rise to and fall from popularity with regularity, one may yet ask what has provided the social sciences with such longevity?

One source of longevity for the erroneous principles of social science is random positive reinforcement, such as gives rise to superstitions. During the twentieth century technological innovations brought about dramatic improvements in productivity and the standard of living of the average American improved. Just as B.F. Skinner was able to demonstrate superstition in pigeons by rewarding them at random (they associated whatever behavior they had been engaging in prior to the reward as bearing a causal relationship to it and repeated that behavior) rising prosperity provided a reward to social scientists that they were inclined to attribute to their work though there may in fact have been no correlation between the events.

A second source of longevity may have been the appearance of progress. From the earliest works relating to the modern social sciences there is an air of progressive excitement. It is always perceived that we are on the cusp of great discovery, that a revolution is at hand. The ultimate reward for the hard work of the social scientists is perpetually just over the horizon. The fallacy here is that because we have demonstrated flaws in the previous theory its replacement must be significantly closer to the truth. Although the new theory may be closer to the truth, if the truth is infinitely distant it is not significantly so. If the social scientists were not blinded by optimism and ignorance it would have seemed quite odd that while in every physical science fundamental principles abide, the fundamental principles of the social sciences are in perpetual revolution. While true sciences are additive these false sciences are only negative. The reason is obvious. As was previously demonstrated, no social scientific experiment can be properly controlled, thus no principle based upon such experiments may be considered fundamental. No progress is made as new flaws are necessarily substituted for old. It is only willful ignorance of the new flaws that perpetuates the illusion of progress.

There is one final source that I can see for the continuation in the application of the social scientific philosophy. This is its persuasive utility. So long as man has been able to record his ideas it is clear he has been eager to convince his fellow men that they should organize their lives in accordance with his propositions. Every epistemology known to man has been utilized in the advancement of such arguments and the epistemology of inductive science is no different. Indeed few modern social engineers attempt to pass off their speculations without a healthy dose of social scientific evidence. Thus one might suspect that these individuals who have flourished at all times in human history have largely taken up residence in social science departments around the world. Indeed the social sciences are an ideal tool for such thinkers, as the experiments of the social sciences prove nothing conclusively they may be endlessly manipulated and contrived to support virtually any hypothesis. Indeed, my partial explorations of social scientific work have yet to uncover a non-obvious social scientific principle that has garnered accord throughout any social science discipline. Yet this is not an unreasonable thing to ask. In the physical sciences nothing is considered to be a scientific fact unless it is indisputably verified, everything else is explicitly maintained as speculative hypotheses. In this sense the social sciences contain no scientific facts and are thus not sciences.

I now turn to the question of a possible replacement for the modern social sciences. We know that we may respond to the phenomena of our experience based upon the insights afforded by subjective judgment for this is the general mode of human understanding. Our ancestors bested the vicissitudes of their environment via the application of this method yet we are justified in longing for more. Subjective judgments are necessarily uncertain; they cannot yield scientific facts. Subjective judgments clearly led to a wide array of non-useful conclusions among our primitive ancestors. Thus the question is: if the methods of inductive objective science do not apply to complex phenomena then is it possible to arrive at verifiable conclusions with regard to such phenomena? The corresponding answer is: yes. We may use the epistemology of deduction.
To this point I have engaged in a mild subterfuge. In truth there is only one epistemology capable of generating verifiable conclusions and that is reason. I have divided this category by the use of induction or deductions and by the use of objective and subjective premises. This division was justified and was useful in the earlier stages of the discussion but here an understanding of the unity of these epistemological subcategories is of great utility.

It is common, nowadays, to think of only objective premises as being valid. This belief may only be held if one neglects the roots of knowledge. In truth all knowledge is founded upon subjective principles. The validity of the logical structure of the human mind must be considered a subjective fact. We are incapable of proving or disproving its validity, as we would be required to use the logical system in question in the act of proof. All truth statements depend upon this assumption. Further all objective premises are merely inputs into this subjective system. We use our powers of observation to generate subjective analogs to the objects of our observations. It is these subjective logical artifacts that we submit to our processes of reasoning. In the physical sciences this is less obvious but these sciences are inextricably integrated with mathematics and with regard to mathematics this is plain to see. Lines and circles do not exist in the world; they are merely objects useful to cognitions. Yet it is clear that the Pythagorean theorem, a scientific fact based upon deductive reasoning applied to subjective facts, is of objective utility. Indeed, all of mathematics consists entirely of deductions from subjective premises. I challenge the reader to discover a matrix in the world at large. Physical science itself is merely a series of deductions based upon subjective premises induced through objective observation. Thus, even within the physical sciences experimental methodology is merely a facet of the overall process, it merely justifies postulates; if Euclid had stopped at the postulation of lines and circles his geometry would be pitiful indeed.

Physical science then is only a subcategory of scientific knowledge but it has been blindly glorified to the exclusion of all other sources of knowledge. It is a premise generator. Its goal is to arrive at premises which no reasonable person can deny. But so is the human mind. That is, we are capable of asserting truths and those truths are sometimes indisputable. Any such truth is a fitting subject for the operation of logical processes. If I use correct logical operations and indisputable premises then any conclusion that I reach must be a scientific fact. You may dispute my premises, you may correct my logic but short of these you must accept the validity of my conclusions. It is certainly true that philosophers have used these methods to reach a wide variety of spurious conclusions but the method was not responsible. These philosophers, without fail, either admitted questionable premises or violated fundamental logical principles.

The procedure of the physical sciences is fundamentally identical to this process. The procedure of the social sciences, though superficially similar to that of the physical sciences, is fundamentally at variance with this procedure, as they do not establish indisputable premises. Indeed, I would qualify the error in modern thinking that has lead to the discarding of old deductive truths and the acceptance of new inductive falsehoods as a form of superficiality. We have romanticized the forms related to experimental investigation and demonized those associated with old-fashioned deduction. Although I outline above the technical errors in the thinking of the social scientists I think that for many of them their error is not technical. They do not have faith in objective induction, if that was truly their epistemology they would long ago have recognized their error, I think their epistemology is that truth proceeds from lab coated equation wielders. That is they don't even have a philosophical justification for their epistemology they merely have a justification based upon subjective judgment, to quote Richard Feynman:

"I think the educational and psychological studies I mentioned are examples of what I would like to call cargo cult science. In the South Seas there is a cargo cult of people. During the war they saw airplanes with lots of good materials, and they want the same thing to happen now. So they've arranged to make things like runways, to put fires along the sides of the runways, to make a wooden hut for a man to sit in, with two wooden pieces on his head for headphones and bars of bamboo sticking out like antennas--he's the controller--and they wait for the airplanes to land. They're doing everything right. The form is perfect. It looks exactly the way it looked before. But it doesn't work. No airplanes land. So I call these things cargo cult science, because they follow all the apparent precepts and forms of scientific investigation, but they're missing something essential, because the planes don't land."

So again, the short answer to my second question is: yes. I understand that my abstracted explanation of the possibility of arriving at objective truth through deductive subjective methods may yet seem a bit hazy but this is unavoidable. Such arguments are very involved and I could not easily include a convincing example within the confines of this paper. Although I hope that this paper itself is such an example (I would also recommend the Federalist Papers, and Human Action by Ludwig von Mises), as I have not used induction in my arguments and yet I seek to demonstrate a verifiable truth. Indeed, the explosion of the social sciences could not legitimately be accomplished through inductive objective methods for the very reasons that I have stated above (hence my deliberate avoidance of the obvious argument that the social sciences don't get results). This may provide another argument as to why the social sciences have persisted for so long: their failure results from actively rejecting the methods of reasoning by which alone they might recognize the cause of their failure.


It is undoubtedly true that many social scientific experiments imply interesting relationships. It is also very likely that many of the correlations they suggest bear significant relations to truth, but these relations have only subjective weight, they do not bear the force of logical certainty. Thus, they belong in the category of historical evidence. It was the great coup of the physical sciences that they were able to arrive at data that had greater than mere historical weight. The occurrence of the attack on the world trade center in 2001 is an historical fact. It undoubtedly happened, but its placement in the chain of universal causality is reserved to that assigned by subjective understanding. We cannot truthfully say that it was 69.9% responsible for G.W. Bushes re-election for instance. All historians may agree that it was a significant factor but they are not in a position to say with certainty whether or not it was the greatest factor, much less what its exact causal relationship to the subsequent event was. This is also the type of data that the social sciences generate. It is contrary to the reality of their studies for social scientists to spurn non-numerical evidence or theories based upon such evidence, for the numerical character of their evidence does not lend it any greater credibility. Yet this is precisely what they do. They feel that they may justly ignore theories that were formulated before it was considered necessary to include statistical evidence. They use a new statistic to claim that all theories formulated before the discovery of this new statistic cannot be valid. This is nonsense. One might remove all quantization from all social science experiments and the logical weight of their arguments would not change. Indeed, it is much more useful to carefully phrase conclusions with regard to social phenomena in Standard English, this makes the arguments much more amenable to careful logical analysis. The reason that mathematical equations are useful in physics is that they allow calculation. The phrase "objects in the universe are attracted to one another with a force that diminishes as they recede from one another in precisely the same way that the intensity of a light source diminishes as you move away from it, with the mass of the object being equivalent to the brightness of the light" contains all of the information contained in the equation Fg = k(M1*M2)/r^2 and is heuristically and logically far more informative, especially to those not fluent in mathematical language. Yet physicists use the equation, but this is not to exclude the common reader, it is to include the possibility of calculation. If I wish to know precisely what force a one million kilogram object will exert on a one kilogram object that is one meter distant from it the equation is more directly useful than the plain English statement. But in the social sciences such precision is impossible and thus equations in these fields do not add to understanding. They merely encrypt and obscure the observations of researchers. This is disingenuous and it has done great harm to our understanding of these fields of knowledge. The compilation of a bunch of somewhat useful observations into one mathematical model does nothing but annihilate the value of the original observations. Charles Munger, Warren Buffett's business partner, relates such an event, "Once Warren and I bought a company and the seller had a big study done by an investment banker, it was about this thick. We just turned it over as if it were a diseased carcass. He said, “We paid $2 million for that.” I said, “We don’t use them. Never look at them.”[2] How can Buffett and Munger afford to ignore the kind of detailed synthesizing predictive studies that are the bread and butter of the big investment banks and Wall Street firms? By recognizing that they can't afford to heed them. They outperform every single one of these firms virtually every year because they understand that the only useful tools for understanding business and economics are subjective understanding and subjective deduction. A single well considered observation can be assigned a subjective relevance and mentally cataloged. To accept the results of a grand synthesizing study would require a faith in the subjective judgments of every individual that contributed to it, and further, an absurd faith in the objective nature of its conclusions. Buffet and Munger are too smart to risk the wealth of their shareholder on such baseless speculation, while the leaders of the majority of U.S. corporations are not.