The Goals of Science - Philosophy of Computer Science - Free Computer, Programming, Mathematics

At least three different things have been identified as the goals of science:description,

explanation, andprediction. They are not independent of each other: At the very least, you need to be able to describe things in order to explain them or to predict their behavior. But they are distinct: A theory that predicts doesn’t necessarily also explain (for some examples, see Piccinini 2015, p. 94).

4.5.1 Description as the Goal of Science

Ernst Mach was a physicist and philosopher of science who lived about 130 years ago (1838–1916), at the time when the atomic theory was being developed. He was influenced by Einstein’s theory of relativity and is probably most famous for having investigated the speed of sound (which is now measured in “Mach” numbers, “Mach 1” being the speed of sound).

For Mach, the goal of science was to discover regular patterns among our sensations in order to enable the prediction of future sensations, and then todescribethose patterns in an efficient manner. Scientific theories, he argued, are (merely)shorthand—or summary—descriptionsof how the worldappearsto us.

According to the philosophy of science known as “physicalism”, our sensory per- ception yields reliable (but corrigible)4knowledge of ordinary, medium-sized physical objects and events. For Mach, because atoms were not observable, there was no reason to think that they exist. Perhaps it seems odd to you that a physicist would be inter- ested in oursensationsrather than in theworldoutside of our sensations. This makes it sound as if science should be done “in the first person, for the first person”, just like philosophy! That’s almost correct; many philosophically oriented scientists at the turn of the last century believed that science should begin with observations, and what are observations but our sensations? Kant distinguished between what he called ‘noumena’ (or “things in themselves”, independent of our concepts and sensations) and what he called ‘phenomena’ (or things as we perceive and conceive them as filtered through our conceptual apparatus). He claimed that we could only have knowledge about phenomena, not noumena, because we could not get outside of our first-person, subjective ways of conceiving and perceiving the world. This is why some philosophers of science have argued that sciences such as quantum mechanics are purely instrumental and only concerned with prediction, rather than being realistic, or concerned with the way the world “really” is.

4.5.2 Explanation as the Goal of Science

By contrast, the atomic theory was an attempt toexplainwhy the physical world ap- pears the way it does. Such a goal for science is to devise theories that explain observed behavior. Such theories are not merely descriptive summaries of our observations, but go beyond our observations to include terms that refer to things (like atoms) that we might not be able to observe (yet). So, the task of science is not, in spite of Mach, merely to describethe complexity of the world in simple terms, but to explain the world:

This is the task of natural science: to show that the wonderful is not incomprehen- sible,to show how it can be comprehended. . . . (Simon, 1996b, p. 1, my italics)

One major theory of the nature of scientific explanation is the philosopher Carl Hempel’s Deductive-Nomological Theory (Hempel, 1942, 1962). It is “deductive”, because the statement (Qc) that some objectchas property Q is explained by showing that it can be validly deduced from two premises: thatchas property P (Pc) and that all Ps are Qs (∀x[Px→Qx]). And it is “nomological”, because the fact that all Ps are Qs is lawlike or necessary, not accidental: Anything that is a Pmustbe a Q. (This blending of induction and deduction is a modern development; historically, Bacon (and other “empiricists”, chiefly in Great Britain) emphasized experimental “induction and prob- abilism”, while Descartes (and other “rationalists”, chiefly on the European continent) emphasized “deduction and logical certainty” (Uglow, 2010, p. 31).)

One of the paradoxes of explanation (it is sometimes called the “paradox of anal- ysis”) is that, by showing how something mysterious or wonderful or complicated is really just a complex structure of simpler things that are non-mysterious or mundane, we lose sight of the original thing that we were trying to understand or analyze. (We will see this again in Chapter 7 when we look at Dennett’s notion of Turing’s “inver- sion”. It is also closely related to the notion of recursion (see§7.6.5), where complex things are defined in terms of simpler ones.) Simon demurs:

. . . the task of natural science . . . [is] to show how it [the wonderful] can be comprehended—but not to destroy wonder. For when we have explained the wonderful, unmasked the hidden pattern, a new wonder arises at how complexity was woven out of simplicity.(Simon, 1996b, pp. 1–2, my italics)

So, for instance, the fact—if it is a fact (we will explore this issue in Chapter 19)—that non-cognitive computers can exhibit (or even merely simulate) cognitive behaviors is itself something worthy of wonder and further (scientific) explanation.

Question for the Reader:

Are some computer programs theories? In particular, consider an AI program that allows a robot to “see” or to use natural language. Does such a program constitute a psychological (hence scientific)theoryof vision or language? If so, would it be adescriptivetheory or anexplanatory

one? (We’ll look at some answers to these questions in Chapter 15.)

4.5.3 Prediction as the Goal of Science

. . . prediction is always the bottom line. It is what gives science its empirical con- tent, its link with nature. . . . This is not to say that prediction is thepurposeof science. It was once . . . when science was young and little; for success in prediction was . . . the survival value of our innate standards of subjective similarity. But prediciton is only one purpose among others now. A more conspicuous purpose is technology, and an overwhelming one is satisfaction of pure intellectual curisity— which may once have had its survival value too.

—Willard van Orman Quine (1987, p. 162)

Einstein “thought the job of physics was to give a complete and intelligible account of . . . [the] world” (Holt, 2016, p. 50)—that is, toexplainthe world. Both scientific descriptions and explanations of phenomena enable us to makepredictionsabout their future behavior. This stems, in part, from the fact that scientific descriptions must be

generaloruniversalin nature: They must hold for all times, including future times. As the philosopher Moritz Schlick put it,

For the physicist . . . the absolutely decisive and essential thing, is that the equa- tions derived from any datanowalso hold good ofnewdata. (Schlick, “Causaltiy in Contemporary Physics” (1931), as quoted in Coffa 1991, p. 333, my boldface, Schlick’s italics)

Thus, “[t]he ‘essential characteristic’ of a law of nature ‘is thefulfillment of predictions’ ” (Coffa, 1991, p. 333, embedded quotation from Schlick).

According to Hempel (1942,§4), prediction and explanation are not mutually ex- clusive. In fact, Hempel argues that they are opposite sides of the same coin. As we saw in the previous section, toexplainan event is to find (perhaps abductively) one or more “initial conditions” (usually, earlier events) and one or more general laws such that the even to be explained can be deduced from them. For Hempel, topredictan event is to use already-known initial conditions and general laws to deduce a future event:

The customary distinction between explanation and prediction rests mainly on a pragmatical difference between the two: While in the case of an explanation, the final event is known to have happened, and its determining conditions have to be sought, the situation is reversed in the case of a prediction: here, the initial conditions are given, and their “effect”—which, in the typical case, has not yet taken place—is to be determined. (Hempel, 1942, p. 38)

But some scientists and philosophers hold that prediction is theonlygoal that is important, and that description and explanation are either not important or impossible to achieve. One of the main reasons for this comes from quantum mechanics. Some aspects of quantum mechanics are so counter-intuitive that they seem to fail both as descriptions of reality as we think we know it and as explanations of that reality: For example, according to quantum mechanics, objects seem to be spread out rather than located in a particular place—until we observe them; there seems to be “spooky” action at a distance (quantum entanglement); and so on. Yet quantum mechanics is the most successful scientific theory (so far) in terms of the predictions it makes. Niels Bohr (one of the founders of quantum mechanics) said “that quantum mechanics was meant to be aninstrument for predictingour observations”, neither a description of the world, nor an explanation of it (Holt, 2016, p. 50, my italics).

The explanation-vs.-prediction debate underlies another issue: Is there a world to be described or explained? That is, does science tell us what the world is “really” like, or is it just an “instrument” for helping us get around in it?