I just finished reading Mr. Swofford's commentary, and while I commend him for wading into that realm as I think the philosophy of science is where the virtues and vices of scientific theories are fought, I think he misreads Kuhn on some key elements.
1) Kuhn himself argues that the probabilism that bridges the observation/theory gap has to be assumed in order to even be considered which makes it part of the current paradigm. Therefore, referencing Kuhn to cite that there's a coming paradigm shift and that paradigm shift is probabilistic in nature, even though probabilism by Kuhn's own admission doesn't count as a paradigm shift is paradoxical.
In their most usual forms, however, probabilistic verification theories all have recourse to one or another of the pure or neutral observation-languages discussed in Section X. One probabilistic theory asks that we compare the given scientific theory with all others that might be imagined to fit the same collection of observed data. Another demands the construction in imagination of all the tests that the given scientific theory might conceivably be asked to pass.
Apparently some such construction is necessary for the computation of specific probabilities, absolute or relative, and it is hard to see how such a construction can possibly be achieved. If, as I have already urged, there can be no scientifically or empirically neutral system of language or concepts, then the proposed construction of alternate tests and theories must proceed from within one or another paradigm-based tradition. Thus restricted it would have no access to all possible experiences or to all possible theories. As a result, probabilistic theories disguise the verification situation as much as they illuminate it. Though that situation does, as they insist, depend upon the comparison of theories and of much widespread evidence, the theories and observations at issue are always closely related to ones already in existence. Verification is like natural selection: it picks out the most viable among the actual alternatives in a particular historical situation. Whether that choice is the best that could have been made if still other alternatives had been available or if the data had been of another sort is not a question that can usefully be asked. There are no tools to employ in seeking answers to it. (pg 144-145)
Link to Structure of Scientific Revolutions
2) In Kuhn's model of the
Phases of Science, the second phase involves the accumulation of anomalies, which expose weaknesses of the old paradigm. Instead of recognizing anomalies as mere problems with the theory, Popper hung his hat on falsificationism as the solution, to which Kuhn replies that falsification falls prey to the same objections as probabilistic verification.
A very different approach to this whole network of problems has been developed by Karl R. Popper who denies the existence of any verification procedures at all.2 Instead, he emphasizes the importance of falsification, i.e., of the test that, because its outcome is negative, necessitates the rejection of an established theory. Clearly, the role thus attributed to falsification is much like the one this essay assigns to anomalous experiences, i.e., to experiences that, by evoking crisis, prepare the way for a new theory. Nevertheless, anomalous experiences may not be identified with falsifying ones. Indeed, I doubt that the latter exist. As has repeatedly been emphasized before, no theory ever solves all the puzzles with which it is confronted at a given time; nor are the solutions already achieved often perfect. On the contrary, it is just the incompleteness and imperfection of the existing data-theory fit that, at any time, define many of the puzzles that characterize normal science. If any and every failure to fit were ground for theory rejection, all theories ought to be rejected at all times. On the other hand, if only severe failure to fit justifies theory rejection, then the Popperians will require some criterion of “improbability” or of “degree of falsification.” In developing one they will almost certainly encounter the same network of difficulties that has haunted the advocates of the various probabilistic verification theories.(pg 145-146)
This is a bit schizophrenic, because in our discipline the same guy who wrote this in the Fingerprint Sourcebook, is also leading the charge in the 'new paradigm' which is characterized as really just the old paradigm by Kuhn who is being used to incorrectly justify the new paradigm by Mr. Swofford.
Sir Karl Popper (1902–1994) recognized the difficulty of defining science. Popper, perhaps one of the most respected and widely known philosophers of science, separated science from nonscience with one simple principle:falsifiability. Separation, or demarcation, could be done if a theory or law could possibly be falsified or proven
wrong (Popper, 1959, 1972). A theory or law would fail this litmus test if there was no test or experiment that could be performed to prove the theory or law incorrect. Popper believed that a theory or law can never be proven conclusively,no matter the extent of testing, data, or experimentation. However, testing that provides results which contradict a theory or law can conclusively refute the theory or law, or in some instances, give cause to alter the theory or law. Thus, a scientific law or theory is conclusively falsifiable although it is not conclusively verifiable (Carroll, 2003).
Fingerprint Sourcebook, Chp 14
3) Kuhn's work has been remarkably analyzed and he wrote a follow up thesis explaining the virtues of later theories that came to replace earlier theories (read paradigm shift) in a paper called
Objectivity, Value Judgment, and Theory Choice. They are:
- Accurate - empirically adequate with experimentation and observation
- Consistent - internally consistent, but also externally consistent with other theories
- Broad Scope - a theory's consequences should extend beyond that which it was initially designed to explain
- Simple - the simplest explanation, principally similar to Occam's razor
- Fruitful - a theory should disclose new phenomena or new relationships among phenomena
While the probability model as a theory lacks some aspects of these, as it relates to being fruitful, I'd say probability models have yet to demonstrate such fruitfulness. When a probability model can say something fruitful with regards to the Mayfield, Lana Canen, Shirley McKie and the Zero Point Identification prints, I'd be happy to listen. I think technology in the field (AFIS) has actually made the most impact on the field and has actually driven the biggest paradigm shift. The problem is, it was also cited in the
OIG Report as the main contributor to the first cause of several in producing the error. Now, the
latest round of probability models is based on an AFIS algorithm. Something doesn't add up.
One benefit we get with being 'behind the times' is that we can see that the new paradigm has some serious problems of it's own as they are on display with the D.C. DNA Crime lab. I'd like to see a commentary on how policies or IAI Probability Evaluation committees would prevent/handle such instances. Since ER is on the IAI committee, perhaps he can tell us how such concerns are being considered.