A post by John F. DeCarlo.
The famed Shakespearean actor, Edmund Kean, supposedly declared on his death bed: “dying is easy; comedy is hard.” Might the same be said about ‘doing’ science? For while Newtonian equations are still used for their ease and quickness, they are conditionally limited, and fundamentally, misleading. Accordingly, I would like to address the Quine/Duhem Paradox and offer a critical evaluation of the Bayesian response of abiding by self-credences and offer an alternative procedural methodology.
The Quine/Duhem Paradox is fairly straight forward: No hypothesis can be tested in isolation from an indefinite set of auxiliary hypotheses; and in order to show that a hypothesis is mistaken, is it necessary to isolate that hypothesis from its set of auxiliary hypotheses; therefore, no hypothesis can be fully proven.
The Bayesian response to this epistemological-methodological dilemma is to introduce the notion of degrees of belief that an investigator has for a hypothesis, relative to others. Then, as new information emerges, one reevaluates the likelihood of that information being compatible with each original possibility. In this respect, the Bayesians solve the Quine/Duhem paradox by rejecting the claim that: in order to show that a hypothesis is mistaken, it is necessary to isolate that hypothesis from its set of auxiliary hypotheses. Instead, they assert that: it can be determined whether the set of auxiliary hypotheses should be rejected based on the degree to which those auxiliary hypotheses are believed to be true.
However, a case in point: Einstein, who radically inverted the Newtonian world view, and who was right about the nature of photons, the existence of atoms and molecules, the relationship between energy and mass, the relative nature of time, and the universal nature of gravity, was, to his dying day, dead-set wrong about the quantum world. In other words, he unconditionally ruled out certain imaginative leaps based on his own self-credences.
In contrast, as I have asserted more fully in Transcending Bayesian Self-Credences, certain parameters can be implemented regarding the use of the imagination relative to the history of scientific investigation. More specifically, I have delineated the intricate connection between historical periods of scientific insight, breakthrough, and revolutionary vision, and a corresponding cyclical pattern of creative-imaginative thought structures embedded in those discoveries, with particular emphasis on the histories of physics and biology.
As will be noted more fully, below, the structural patterns of imaginative insight include: positive and negative analogies, synthesis, blind spots, thin places, inversions, poly-holism, and wild and divergent strands, many of which often stand outside the purview and the self-credences of investigating scientists. To this effect, it is contended that science, historically, has proceeded by the use of these structural types of imaginative insight and that scientists can and should rely on these strategies to remedy the classical problems concerning the justification of contending hypotheses.
In other words, not unlike legal precedents, where certain historical cases represent situational contexts in which arguments have been made and upheld by the court system, the structural types of imaginative insight might alert an investigator to consider previously ignored or overlooked features, even as cultural and/or institutional forces warrant against them. This is especially significant in cases of negative analogy, blind spots and thin places, inversions, and wild and divergent thoughts. Conversely, the historical and logical sequence of the structural types of imaginative insight can restrain the imagination to what is generally feasible at a particular historical-intellectual juncture. For example, synthesis follows positive and negative analogies, inversions follow synthesis -- but sometimes only before or after blind spots and thin places have been flushed out -- and inversions often culminate in poly-holism.
This is, however, not to say that scientists should abandon their hunches and guttural responses to a scientific problem. In fact, any keen scientist knows that hunches, intuitions, and/or intimating feelings are the Great Equalizer, especially since there is no logic of discovery. In this respect, while the assertion that emotion is a facet of reason and a means of epistemic access can be historically located in Kierkegaard’s notion of the subjective thinker, I follow the lead of Catherine Elgin that emotions are a part of an integrated network of mutually supportive cognitive claims, and as such, can at least provide orientation that render particular epistemological facets salient, and at best, indicate and resonate with corresponding truth claims. Moreover, by indicating previously ignored features and unknown patterns, emotions can provide new insights.
By the same token, while Marvin Minsky is right that disposition precedes proposition, this process is not merely linear and sequential; rather, there is a recursive loop, by which the affect of the initial disposition is re-activated by the propositional effect, etc. In this respect, the imaginative structures and emotional dispositions have a bi-directional correlation: emotions connect with imaginative structural forms, and imaginative structural forms connect with emotions. In this way, in contrast to Plato’s perception that poets feel inspired truths, but do not know what or why they feel it, such a bi-directional connection can, as noted above regarding the historical patterns of imaginative insight, not only constrain the imagination, but also enlarge it to possible truths that lie beyond both Bayesian pre-data priors and post evidence degrees of belief.
Hence, what follows is a categorical listing of the aforementioned structural forms of imaginative insight, along with the type of emotional register that would be evoked in an investigator relative to a corresponding set of data; and a historical example of each type of formal scientific imaginative insight:
Positive Analogy: A minor modification and/or refinement of a current point of view
Example: Kepler asserts that the earthly orbit is elliptical, not circular
Feeling: This is just about right, but it just needs a slight tweaking
Oppositional Analogy: Points out something which is different from what one would expect
Example: Smallpox is cured by looking at those not affected, not those who have been infected
Feeling: I am going down the wrong path, and need to take a different route
Synthesis: A creative integration of the shortcomings and strengths of opposites
Example: Dirac’s synthesis of quantum mechanics and special relativity
Feeling: I feel mixed and torn, and need to pull things together in a creative manner
Thin Place: According to Irish folklore the thin place is a short and narrow temporal–spatial opening that allows for insight and revelation
Example: Both dark matter and the neutrino are hard to detect
Feeling: I feel like I am overlooking something: it’s something small, but very significant
Blind Spot: Synthesis can be deceptive, for it seems to be all encompassing, but there is often something that no one even expects or anticipates
Example: The discovery of Cooper and Boson pairs – two different types of electrons
Feeling: I sense that I am missing and/or overlooking something
Inversion: Beyond a reversal, as found in the negative analogy, it involves a convoluted twist
Example: As noted above, Einstein inverts the Newtonian parameters of absolute time and space with Special and General Relativity
Feeling: I need to step back, and re-evaluate basic assumptions, axioms, and principles
Pluralism or Holism: Beyond an integrated synthesis, numerous factors are operative
Example: Biological Systems Model of: gene, cell, tissue, organ, individual, environment
Feeling: It is more complicated than I initially thought; there are multiple pieces that need to be considered and integrated
Divergent: Data diverges and pushes past the norm, into a strange range of patterns
Example: Long distance quantum entanglement, and other quantum oddities
Feeling: It’s really wild and strange, almost defying human comprehension
So, in closing, let us return to Edmund Kean’s assertion that “comedy is hard”. After all, it requires detachment and imagination, so that one can perceive incongruities and ambiguities, if not, even more startling insights and revelations. Here too, the burden on the Bayesian model is to step back and to open up, not only to the data at hand, but to one’s degrees of belief regarding what constitutes causal factors, and how they should be conceptually and theoretically framed and interpreted. At the same time, the histories of the sciences provide a bi-directional emotional-cognitive structural guide to the type of creative thought patterns which might be most worthy of hypothetical consideration.
Carroll, Sean. The Big Picture, Dutton Books, 2016.
Cowen, Ron, 2015, “Space, Time, Entanglement. Nature”, Volume 527, 11/19.
Cuonzo, Margaret. Paradox, The MIT Press Essential Knowledge Series, 2014
DeCarlo, John. “Transcending Bayesian Self-Credences,” Tropos Journal, University of Turin, Italy. Publication, Spring, 2018. (With permission of the publisher, this article is available on my Academia.edu site).
Elgin, Catherine. “Epistemology and Emotions” ed. George Brun, Uvli Dogouglu and Dominique Kunzle, London: Ashgate, 2007, 33-50.
Hesse, Mary. Analogy and Confirmative Theory. University of Cambridge, 1963.
Lewis, Sarah. The Rise: Creativity, Gift of Failure, and The Search for Mastery, Simon & Schuster, 2014
Sawyer, Keith. Zig-Zag, Wiley, 2013.
Statile, Glenn. “Analogy and the Integrity of Science”, Long Island Philosophical Society, 2008.