25 Indeed, Lakatos was sharply critical of Popper’s definition of (the methodology of) science as based upon the sole use of propositions that are falsifiable. “For Popper’s criterion ignores the remarkable tenacity of scientific theories. Scientists have thick skins. They do not abandon a theory merely because facts contradict it. They normally either invent some rescue hypothesis …[or] they ignore [the anomalous results]. …[S]cientists talk about anomalies, recalcitrant instances, not refutations. History of science, of course, is full of accounts of how crucial experiments allegedly killed theories. But such accounts are fabricated long after the theory had been abandoned.” Id. This criticism, as expressed, is based upon his view of how scientists act, but Lakatos also argues, in effect, that the test of falsification is not possible. See also, Polanyi, “The Creative Imagination,” Chemical and Engineering News 44 (1966), p.85 (“Verification and falsification are both formally indeterminate procedures.”).
26 Another problem is that of “underdetermination,” where the theory does not provide a unique explanation of causation. See, e.g., Peter Lipton, Inference to the Best Explanation (2004) (Second Edition), pp.5–7.
27 Professor Barrow attributes the realization of the crucial significance of the initial conditions to two of the “deepest thinkers of the nineteenth century,” James Clerk Maxwell and Henri Poincare, quoting Poincare’s statement that “a very small cause which escapes our notice determines a considerable effect that we cannot fail to see, and then we say that the effect is due to chance. … [I]t may happen that small differences in the initial conditions produce very great ones in the final phenomena. A small error in the former will produce an enormous error in the latter. Prediction becomes impossible… .” Id.
28 As we shall discuss further, all predictions will be subject to the ceteris paribus condition: the prediction of the theory will be realized on the assumption that nothing else material to the result, beyond what has been hypothesized in the making of the prediction, occurs in the process. Many scientific predictions can be tested in a laboratory where extraneous factors can be controlled or, at least, measured. In other cases, the theory may incorporate all of the necessary causal factors within the parameters of current technology for measurement or, in other words, experimental error. Such theories can be considered as applying to “closed systems”—all relevant variables are within the system. However, the ceteris paribus condition is particularly daunting in “open systems,” subjects like economics and biology—it is almost inconceivable that any prediction made by an economist or evolutionary biologist subject to the ceteris paribus condition could be realized in the real world. The theory will never be able to incorporate and control for or measure all relevant factors, and there will always be relevant factors that have changed. So, unless we are prepared to deny the status of “science” to certain bodies of study that we have generally considered to be scientific, we may conclude that there has to be a broader set of criteria that determines whether a theory is scientific. Such theories have been called “explanation sketches,” since a complete explanation can never be achieved, only more and more complete explanations as additional variables are incorporated into the theory. Carl G. Hempel and Paul Oppenheim, “Studies in the Logic of Explanation,” Philosophy of Science, XV (1948), pp.130–39.
29 Of course, one could undertake an interesting exploration in the history of ideas to ascertain the actual origins of the root concept and the influences of various intellectuals on others. One could also speculate on the apparent concurrent emergence of ideas (whose “time has come”) that seems to appear in the history of ideas. Naturally, the concepts of competition and survival of the fittest also can be—and have been—applied to the “evolution” of various bodies of thought, including the natural sciences.
30 Let me add, and explain, a caveat to this assertion. There has been some empirical evidence of regularity or predictability in the observed, laboratory evolution of bacteria. See Carl Zimmer, “Watching Bacteria Evolve, With Predictable Results,” The New York Times, Science, August 15, 2013. Research conducted under the direction of Joao Xavier at Memorial Sloan-Kettering Cancer Center, the results of which were published in the journal Cell Reports, demonstrated that a common species of bacteria called Pseudomonas aeruginosa repeatedly experienced mutations in the same gene that produced bacteria that could travel faster through the medium in which they were raised so as to obtain more food. This study dealt with only a specific adaptation in a specific environment. Dr. Xavier is quoted as saying: “In this case, it could be that there are only a few solutions in the evolutionary space.” Id. Given that the particular mutation was capable of giving rise to a physical characteristic that was clearly useful, if there were no other viable mutations that could be as useful, then it was predictable with large numbers and repeated reproduction that such a mutation would be likely to appear in new samples. It is hard to imagine the state of knowledge that would be required for scientists to have predicted such a mutation if they had never seen it before.
31 The practice of diagnostic medicine may more accurately be characterized as intuitive rather than probabilistic. The distinction I am making can be captured in the question “Could a computer be programmed (at least, theoretically) to be as effective a diagnostician as a human being is?” To the extent that the successful practice of diagnosis and treatment depends upon intuitive and creative insights, then that level of achievement will be beyond the capability of the computer because such insights are not computable.
32 For example, concerns have been expressed about the meaning of certain clinical trials that fail to detect any statistically meaningful effects of a drug across the sample group, despite individual stories of almost miraculous effects of the same drug on particular individuals. The explanation may be in our failure to understand “just how individualized human physiology and human pathology really are.” Clinton Leaf, “Do Clinical Trails Work,” The New York Times, Sunday Review, The Opinion Pages, July 14, 2013. In other words, there may be quite specific factors in particular individuals with a certain disease that make a drug highly effective, while many others with the “same” disease may not have those factors.
33 Byers discusses the different uses of the words “subjective” and “objective.” Citing the New Oxford American Dictionary, he notes that “objective” can be used to mean free of personal opinion or of a personal (biased) perspective but can also used to mean “not dependent on the mind for existence.” Byers suggests that science is objective in the first sense, but not necessarily so in the second. Id., pp.92, 98.
34 I admit that part of the wonder I felt as I began to master neoclassical value theory, and then more traditional industrial organization economics, was the recognition that it seemed to provide an intellectual framework to the Mid-western Republican political values with which I had been raised during the late 1950s and early 1960s. I then promptly saw that one of the reasons for the violent antipathy toward the economics department being expressed by most of my college contemporaries in the elite Eastern academy of the late-1960s was the very fact that a significant part of the established doctrine did indeed seem to provide support for free markets, inequality in the distribution of wealth and income and laissez faire government economic policies. The fact that economists were making substantial progress in understanding externalities, the consequences of inequality and other short-comings of the established doctrines was quite irrelevant.
35 Arthur Stanley Eddington, the Plumian Professor of Experimental Philosophy at Cambridge University during the first half of the twentieth century and a contemporary and colleague of Albert Einstein, believed that fundamental science describing the physical world could be developed by pure thought. Observation and experimentation were useful tools that could greatly speed the process of discovery but were, nonetheless, ultimately unnecessary. He declared that “My conclusion is that not only the laws of nature but numerical values of the fundamental relationships or forces that are presumed to be constant, such as the speed of light and the gravitational constant, can be deduced from epistemological considerations,