Not higher standard. (Or, probably so by many — I recognize the pattern you call out — but I think not by me.) I agree fully with what you say below. Just as true for my own mind as someone else's, though I have access to a higher bandwidth of (some) report outputs about it.
The nature of understanding, its characteristics and weirdnesses, is something that I imagine could be interesting though. Science happens to be a useful somewhat-orderly window through which to ask about it, to the extent that we can segment science off as a domain within the culture that takes a particular, distinctively pragmatic (by which I mean recursive in descriptive levels) approach to trying to recognize errors that are cryptic and hard to catch and characterize. — Intersubjectivity to catch the mistakes of subjectivity and revelatory truth; — empirical grounding to catch the mistakes of both subjective and intersubjective (mass-delusional) renderings; — a premise that refutation is generally stronger than confirmation, and a certain “open society” model (connection made for the reasons Popper did) to support that asymmetry; — formal language as a kind of debugging framework for informal reasoning; — social protocols to try to figure out what it means to “empirically ground” anything; — and hopefully more than those. All that effort at error discovery and correction, however, is ultimately grounded at least in part in people's sense that they “understand” one or another thing. Probably the generation of ideas also depends considerably on what that “understanding” constitutes. Far from wanting to claim it is unconnected to the broad schema that ML uses, I am interested in what that schema might enable us to see about ourselves, because now it can be ramified to quite complex patterns, not just the simple ones that could be investigated in the first generations after Hopfield. Obviously I am overdue on grant-reporting tasks that I am procrastinating further. Eric > On May 22, 2025, at 8:06, Marcus Daniels <[email protected]> wrote: > > Eric writes: > > “A colleague asked me last week (not a high level of domain familiarity, but > a good mind overall), what will science become in the age of ML, where there > can be claims about everything, but transparency about little of it.” > > What transparency does one have about a new hire’s mind? An employer may > have a credential from a university, or a confirmed work history, or green > wall of github commits from a credible open-source project, or a highly cited > Google Scholar profile. This doesn’t tell us anything about the mechanism of > their reasoning; it remains a black box. And yet LLM-based AI is held to a > higher standard by some. Why? > > Marcus > .- .-.. .-.. / ..-. --- --- - . .-. ... / .- .-. . / .-- .-. --- -. --. / ... > --- -- . / .- .-. . / ..- ... . ..-. ..- .-.. > FRIAM Applied Complexity Group listserv > Fridays 9a-12p Friday St. Johns Cafe / Thursdays 9a-12p Zoom > https://linkprotect.cudasvc.com/url?a=https%3a%2f%2fbit.ly%2fvirtualfriam&c=E,1,thDddg1PQrSz14Ovsc75KBCfD9gKBORpaz5lHqzyufuEDQq3d_LJNY1I7aRhJEdbV58LJAz-Vhz0X_eKqvw3SR8871X302GvKXcxRnZH&typo=1 > to (un)subscribe > https://linkprotect.cudasvc.com/url?a=http%3a%2f%2fredfish.com%2fmailman%2flistinfo%2ffriam_redfish.com&c=E,1,A68ssHIKip5ipThdgF6FpI19-Y72KyVSqfKUE75-Oiz18Xbwl_ypG0DEUYVq8Fm4Yk6MRvkdgGIRKNx4mS2yWKjwjToKRDY5sQaq7dwVyNOeb6IabrVgjd4,&typo=1 > FRIAM-COMIC > https://linkprotect.cudasvc.com/url?a=http%3a%2f%2ffriam-comic.blogspot.com%2f&c=E,1,bqgQw0Az5FdBfnlhTkIfzXMkBK-52qcwn3rortyZSbJ8g7qIcVdLPcklp-KD69878Ld83ZgmF0cnn5QNVHEqiOwkHblouyjmkl7nMPELdNRcKg,,&typo=1 > archives: 5/2017 thru present > https://linkprotect.cudasvc.com/url?a=https%3a%2f%2fredfish.com%2fpipermail%2ffriam_redfish.com%2f&c=E,1,vyxHTl1uAIQXSAGFVUqvPpGXlnCwjyPwXlwJl_zsCXDNbD3Vh4Vue1uM8mXYeab7Z29ksIGt-yPJ_Z_6MUXYS9ZKTFyB9z3lZWJg22ENRcycIewGuxWRXQ,,&typo=1 > 1/2003 thru 6/2021 http://friam.383.s1.nabble.com/
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