among Sciences
Not only are there cultural lags between the institutionalized practices of science and philosophy of science, there are also cultural lags among the several sciences. Philosophers of science have preferred to examine physics and astronomy, because historically these have been the most advanced sciences since the historic Scientific Revolution benchmarked with Copernicus and Newton.
Institutional changes occur with lengthy time lags due to such impediments as intellectual mediocrity, technical incompetence, risk aversion, or vested interests in the conventional ideas and the received wisdom. The newer social and behavioral sciences have remained institutionally retarded. Naïve sociologists and economists are blithely complacent in their amateurish philosophizing about basic social-science research, often adopting prescriptions and proscriptions that contemporary philosophers of science recognize as anachronistic and fallacious. The result has been the emergence and survival of retarding philosophical superstitions in these retarded sciences, especially to the extent that they have looked to their own less successful histories to formulate their ersatz philosophies of science.
Thus sociologists and economists continue to enforce a romantic philosophy of science, because they believe that sociocultural sciences must have fundamentally different philosophies of science than the natural sciences. Similarly behaviorist psychologists continue to impose the anachronistic positivist philosophy of science. On the contemporary pragmatist philosophy these sciences are institutionally retarded, because they erroneously impose preconceived semantical and ontological commitments as criteria for scientific criticism. Pragmatists can agree with Popper, who said that science is “subjectless” meaning that science is not defined by any particular semantics or ontology.
Pragmatists tolerate any semantics or ontology that romantics or positivists may include in scientific explanations, theories and laws, but pragmatists recognize only the empirical criterion for criticism.
4.10 Scientific Discovery
“Discovery” refers to the development of new theories.
Discovery is the first step toward realizing the aim of science. The problem of scientific discovery for contemporary pragmatist philosophers of science is to describe and to proceduralize the development of universally quantified statements for empirical testing with nonfalsifying test outcomes, thereby making laws for use in explanations and test designs.
Much has already been said in the above discussions of philosophy of scientific language in Chapter 3 about the pragmatic basis for the definition of theory language, about the semantic basis for the individuation of theories, and about state descriptions. Those discussions will be assumed in the following comments about the mechanized development of new theories.
4.11 Discovery Systems
The discovery system produces a transition from an input-language state description containing currently available information to an output-language state description containing the generated and tested new theories.
In the “Introduction” to his Models of Discovery 1978 Nobel-laureate Herbert Simon, one of the founders of artificial intelligence, writes that dense mists of romanticism and downright knownothingness have always surrounded the subject of scientific discovery and creativity. Therefore the most significant development addressing the problem of scientific discovery has been the relatively recent mechanized discovery systems in computational philosophy of science.
The ultimate aim of the computational philosopher of science is to facilitate the advancement of contemporary sciences by participating in and contributing to the successful basic-research work of the scientist. The contemporary pragmatist philosophy of science thus carries forward John Dewey’s emphasis on participation. But few academic philosophers have the requisite computer skills much less a working knowledge of any empirical science for participation in basic research.
Every useful discovery system to date has contained procedures both for constructional theory creation and for critical theory evaluation for quality control of the output and for restricting the size of the system’s otherwise unmanageably large output. Theory creation introduces new language into the current state description to produce a new state description, while falsification eliminates language from the current state description to produce a new state description. Thus both theory development and theory testing enable a discovery system to offer a specific and productive diachronic dynamic procedure for linguistic change in empirical science.
The discovery systems do not merely implement an inductivist strategy of searching for repetitions of individual instances, notwithstanding that statistical inference is employed in some system designs. The system designs are mechanized procedural strategies that search for patterns in the input information. Thus they implement Hanson’s thesis in Patterns of Discovery that in a growing research discipline inquiry seeks the discovery of new patterns in data. They also implement Feyerabend’s “plea for hedonism” in Criticism and the Growth of Knowledge to produce a proliferation of theories. But while many are made, few are chosen due to the empirical testing routines in the systems.
4.12 Types of Theory Development
In his Introduction to Metascience (1976) Hickey distinguishes three types of theory development, which he calls extension, elaboration and revision.
Theory extension is the use of a currently tested and nonfalsified explanation to address a new scientific problem. The extension could be as simple as adding hypothetical statements to make a general explanation more specific for the problem at hand.
A more complex strategy for theory extension is analogy. In his Computational Philosophy of Science (1988) Thagard describes his strategy for mechanized theory development, which consists in the patterning of a proposed solution to a new problem by analogy with an existing explanation for a different subject. Using his system design based on this strategy his discovery system called PI (an acronym for “Process of Induction”) reconstructed development of the theory of sound waves by analogy with the description of water waves. The system was his Ph.D. dissertation.
In his Mental Leaps: Analogy in Creative Thought (1995) Thagard further explains that analogy is a kind of nondeductive logic, which he calls “analogic”. It firstly involves the “source analogue”, which is the known domain that the investigator already understands in terms of familiar patterns, and secondly involves the “target analogue”, which is the unfamiliar domain that the investigator is trying to understand. Analogic is the strategy whereby the investigator understands the targeted domain by seeing it in terms of the source domain. Analogic involves a “mental leap”, because the two analogues may initially seem unrelated. And the mental leap is called a “leap”, because analogic is not conclusive like deductive logic.
It may be noted that if the output state description generated by analogy such as the PI system is radically different from anything previously seen by the affected scientific profession containing the target analogue, then the members of that profession may experience the communication constraint to the high degree that is usually associated with a theory revision. The communication constraint is discussed below (Section 4.26).
Theory elaboration is the correction of a currently falsified theory to create a new theory by adding new factors or variables that correct the falsified universally quantified statements and erroneous predictions of the old theory. The new theory has the same test design as the old theory. The correction is not merely ad hoc excluding individual exceptional cases, but rather is a change in the universally quantified statements. This process is often misrepresented as “saving” a falsified theory, but in fact it creates a new one.
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