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“The End of Science”: Can We Overcome Cognitive Limitations?

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Alexander Riegler “The End of Science”: Can We Overcome Cognitive Limitations? VOLUTIONARY EPISTE- Abstract be true for any model, in- E mology has brought cluding narrative and forth the idea of science mathematical models. “Why is the universe knowable?” DAVIES (1990) as an evolutionary sys- wonders. In this paper, I argue that science is not a The success of models is tem (cf. CAMPBELL 1974, matter of knowing any universe. Rather, it is a—as their predicative power. I OESER 1984, RIEDL 1983). history has shown—superior method of guidelines of conclude that due to cog- From systems theory of how to organize experiences yielding predictive power. nitive limits of human sci- evolution (RIEDL 1977) Historically, two types of models have given rise to the entists, model-building is and the theory of punc- effectiveness of science, narrative and mathematical also subject to limitations. tuated equilibrium models. Based on cognitive psychological investiga- By using computational (GOULD/ELDREDGE 1977) tions, I point out that due to the human nature of sci- devices, those limitations we know that evolution entific reasoning both types of models are limited. might be transcended. does not proceed homo- With the advent of computational devices scientific geneously. Rather, peri- investigation may now be extended to “externalized Different ods of stasis are inter- deductions”, which are not subject to a limited short- rupted by dramatic term memory and slow performance. To shift this to perspectives on changes. Over the last computational science we have to recognize that mod- scientific activity few centuries we have els in all three approaches have basically the same Ralph GOMORY (1995) experienced science as a function. Although this might not solve the realist’s argues that the choice of dynamic enterprise with question of how models relate to the world (at a deep appropriate perspectives is several revolutions. Will philosophical sense), it will guarantee the continued significant if we want to we now face the stasis of existence of contemporary science beyond the cogni- make the unknown visible: science? These argu- tive barrier. “[I]n distinguishing the ments are not purely the- Key words known or the unknown oretical: In a recent from the unknowable, the book, John HORGAN ex- Philosophy of science, cognition, complexity, models, level of detail can be deci- plicitly speaks of “The reality, constructivism, problem solving, artifacts. sive” (p88). End of Science” (1996). This is also true if we In this paper, I outline the mechanisms of the “evo- look at philosophy of science: to find the “proper” lution of science” by first finding an appropriate explanation which both explains success and failure perspective on the philosophy of science. Then, af- of science. Unlike many other papers on the present ter a short review (and rejection) of HORGAN’s thesis, topic (e.g., LAUDAN 1977, STENT 1978, VAN FRAASSEN I identify three core problems to science. These 1980, NERSESSIAN 1987, FAUST 1984, GIERE 1993), I problems, which are mainly motivated by cognitive will not focus on yet another philosophical treat- psychology, have become serious since science ment. Rather, I will deal with the subject of science started to deal with complexity. Computer models in a pragmatic way which aims at the success of pre- have been proposed to cope with this latest frontier dictions. The following list locates this position of science. However, such models have not received among all possible views on the philosophy of sci- acceptance among the scientific community due to ence. Furthermore, the list summarizes what we po- the presumingly arbitrary relationship between tentially can expect from a philosophy of mind. For computational model and “the reality out there” the rest of the paper, I will, triggered by recent dis- (the reminiscence syndrome). I argue that this must cussions about the end of science, outline why we Evolution and Cognition ❘ 37 ❘ 1998, Vol. 4, No. 1 Alexander Riegler should concern ourselves with a possible limitation The last two items especially may yield the expecta- to science at all and what a possible solution might tion that in future, when the content of scientific look like.1 theories will have transcended the limitation of the We must clearly outline what a philosophy of sci- human mind, computers (or other artifacts) may ence should do for us: take over the business of exploring Nature. 1. Is it a pure philosophical exercise where argu- What can such computers “learn” from human ments of various authors are compared, thus scientific activities, and what does “Nature” refer to? building a discourse which does not necessarily Are there limits to science carried out by humans? If “ground” (HARNAD 1990) in the subject (i.e., sci- we don’t face any such limits, we barely need any entific activity)? However, the ultimate goal of artificial extensions. Too much “pleasure” is in- any scientific inquiry is not to be an end in itself. volved in the process of generating scientific knowl- Rather, it has a constructive character in that it edge. But, as with transportation, walking also may allows us to extend the set of actions which we use provide much pleasure, nevertheless society would in order to predict and perceive our world in an not be able to survive without motorized means of increasingly better way. transportation. This is a good demonstration of hu- 2. Is it descriptive in order to explain what has hap- man nature: Although we have been using motor- pened to date? Any description may be based on based vehicles for many decades, we still, and in fact sociological models (cf. KUHN 1962), on a psycho- more than ever, enjoy our biological movement, not logical approach (cf. GIERE 1993), or even on a to mention that our health depends on it. To draw computational philosophy of science (cf. an analogy, in the future scientific reasoning might THAGARD 1988). be done by machines, nevertheless we will still enjoy 3. Is it a normative instrument which tells scientists the intellectual challenge by tackling problems how to do science, such as the research method- which we can grasp with our (narrow) mind. In the ology of the logical positivists (SCHILPP 1963) or following chapter, I will present these restrictions in Karl POPPER’s rejection of induction (1934)? more detail, starting from the positivist’s fear that 4. Is it generative in that it is capable of predicting the big parts of the scientific pie have already been what the future of science will be? Can we expect eaten, leaving only crumbs for contemporary (and that the principal limits of science can be specified future) scientists. analogously to GÖDEL’s Incompleteness Theorem, which poses limits on formal systems (e.g., CASTI The end of science? 1996a)? Following an entirely positivist view on science, can we even expect the end of science I was recently reminded of the possibility that sci- since “all great revolutions are already behind us” ence might come to an end by the provocative book as proposed by the recent The End of Science book of John HORGAN (1996) with the self-explaining title by John HORGAN (1996)? The End of Science. “The great scientists want, above 5. Or will it provide insights and mechanisms all, to discover truth about nature”, John HORGAN which—in the long run—can be automatized wrote in his 1996 book. And since “researchers and therefore passed over to artificial artifacts already mapped out physical reality”, all that is left which then will carry out scientific reasoning? is to fill in details2. To be more concrete, “all” refers Such proposals have been around for many de- to good science, which is capable of producing “sur- cades already, cf. the General Problem Solver of prises”, i.e., scientific revolutions as has been intro- NEWELL and SIMON (1972) and BACON of LAN- duced by DARWIN, EINSTEIN and WATSON & CRICK. GLEY et al. (1987) More pragmatically, one may However, “all” neither refers to the (boring?) scien- think of the usage of computers in mathematics tific activities of filling in all the gaps within the as the first sign of this development. For exam- map mentioned above, nor to applied science. And ple, the famed four-color conjecture (APPEL/HAK- it does not refer to what HORGAN calls “ironic sci- EN 1977), which demonstrated that problems ence”, those efforts of physicists and chaos-com- may no longer be tackled by traditional, human- plexity-researchers (“chaoplexologists” in HORGAN’s based methods. It made use of the power of hun- terminology, p192) which argue for the existence of dreds of hours of computation on supercomput- high dimensional superstrings and life inside com- ers in order to calculate individual cases rather puters. than to prove the problem in a traditional math- HORGAN dissociate himself from any relativist ematical way. view on science brought forth to a large audience by Evolution and Cognition ❘ 38 ❘ 1998, Vol. 4, No. 1 “The End of Science”: Can We Overcome Cognitive Limitations? Thomas KUHN (1962) in the early 60s3. He therefore Certainly, no theory can ever reach the status of cannot help but think that all present scientific universal applicability. This is also true for any the- knowledge is the complete framework to describe ory that wants to explain the dynamics of scientific and cope with reality. Taking a KUHNIAN perspective activity. Rather, it seems useful to explain science to into account, he might rather—possibly correctly— an extent which will allow us to formalize its key speak of an end of the current paradigm.4 Indeed, as mechanisms and to transfer it to artifacts. Melanie MITCHELL (1995) in her response to HOR- GAN’s previously published paper “From Complexity What could the problems be? to Perplexity” (1995, p1) pointed out, that “[t]he specter of the “end of science” periodically appears The problems which may cause a decay of progress in the scientific and popular literature, often at the in human science are rooted in its members: the end of one scientific era (e.g., NEWTONIAN mechan- human scientists and their cognitive apparatus.
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