List, In a brief article, "How Does A.I. Think? Here’s One Theory" in the New York Times today, Peter Coy, after noting that "Computer scientists are continually surprised by the creativity displayed by new generations of A.I.," comments on one hypothesis that might help explain that 'creativity', namely, that AI is using abduction in its machine reasoning. He writes:
One hypothesis for how large language models such as o1 think is that they use what logicians call abduction, or abductive reasoning. Deduction is reasoning from general laws to specific conclusions. Induction is the opposite, reasoning from the specific to the general. Abduction isn’t as well known, but it’s common in daily life, not to mention possibly inside A.I. It’s inferring the most likely explanation for a given observation. Unlike deduction, which is a straightforward procedure, and induction, which can be purely statistical, abduction requires creativity. The planet Neptune was discovered through abductive reasoning, when two astronomers independently hypothesized that its existence was the most likely explanation for perturbations in the orbit of its inner neighbor, Uranus. Abduction is also the thought process jurors often use when they decide if a defendant is guilty beyond a reasonable doubt. Yet Peirce argues in the 1903 Lectures on Pragmatism that only abduction "introduces any new idea" into a scientific inquiry: " Abduction is the process of forming an explanatory hypothesis. It is the only logical operation which introduces any new idea; for induction does nothing but determine a value, and deduction merely evolves the necessary consequences of a pure hypothesis." I had always thought of abduction as the unique domain of the individual scientist, the creative genius (say, Newton or Einstein) who, fully versed in the most important relevant findings in his field, retroductively connects those pieces of scientific information to posit a testable hypothesis concerning an unresolved question in science. But it makes sense that an AI program employing large data bases might indeed be able to 'scan' those huge, multitudinous bases, connect the salient information, and posit an hypothesis (or some other abductive idea). Any thoughts on this? For example: Is it potentially a valuable feature and power of AI and, thus, for us (the use of AI in medical research would tend to support this view)? Is it a potential danger to us (some AI programs have been seen to lie, to 'hide' some findings, etc.; might this get out of control)? If AI can create testable hypotheses, is the role of the 'creative' scientist jeopardized? Best,' Gary R
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