(Not very familiar with math.)

The Heyting-algebraic definition of implication makes intuitive sense to me, or at least after you state your confusion. 'One circle lies inside the other' is like saying A is a subset of B, which is a statement that describes a relation between two sets, and not a statement that describes a set, so we shouldn't expect that that mental image would correspond to a set. Furthermore, the definition of implication you've given is very similar to the material implication rule; that we may substitute 'P implies Q' with 'not-P or Q'.

Also, I have personally been enjoying your recent posts with few prerequisites. (Seems to be a thing.)

I have what feels like a naive question. Is there any reason that we can't keep appealing to even higher-order preferences? I mean, when I find that I have these sorts of inconsistencies, I find myself making an additional moral judgment that tries to resolve the inconsistency. So couldn't you show the human (or, if the AI is doing all this in its 'head', a suitably accurate simulation of the human) that their preference depends on the philosopher that we introduce them to? Or in other cases where, say, ordering matters, show them multiple orderings, or their simulations' reactions to every possible ordering where feasible, and so on. Maybe this will elicit a new judgment that we would consider morally relevant. But this all relies on simulation, I don't know if you can get the same effect without that capability, and this solution doesn't seem even close to being fully general.

I imagine that this might not do much to resolve your confusion however. It doesn't do much to resolve mine.

Discipline, especially internal psychological, also increases skills.

This is a little ambiguous; does he mean self-control or punishment?

I think these are all points that many people have considered privately or publicly in isolation, but that thus far no one has explicitly written them down and drawn a connection between them. In particular, lots of people have independently made the observation that ontological crises in AIs are apparently similar to existential angst in humans, ontology identification seems philosophically difficult, and so plausibly studying ontology identification in humans is a promising route to understanding ontology identification for arbitrary minds. So, thank you for writing this up; it seems like something that needed to be written quite badly.

Some other problems that might be easier to tackle from this perspective include mind crime, nonperson predicates, and suffering risk, especially subproblems like suffering in physics.

We had succeeded in obtaining John yon Neumann as keynote speaker. He discussed the need for, and likely impact of, electronic computing. He mentioned the "new programming method" for ENIAC and explained that its seemingly small vocabulary was in fact ample: that future computers, then in the design stage, would get along on a dozen instruction types, and this was known to be adequate for expressing all of mathematics. (Parenthetically, it is as true today as it was then that "programming" a problem means giving it a mathematical formulation. Source languages which use "plain English" or other appealing vocabularies are only mnemonic disguises for mathematics.) Von Neumann went on to say that one need not be surprised at this small number, since about 1,000 words were known to be adequate for most situations of real life, and mathematics was only a small part of life, and a very simple part at that. This caused some hilarity in the audience, which provoked von Neumann to say: "If people do not believe that mathematics is simple, it is only because they do not realize how complicated life is."

Franz L. Alt, "Archaeology of computers: Reminiscences, 1945--1947", Communications of the ACM, volume 15, issue 7, July 1972, special issue: Twenty-fifth anniversary of the Association for Computing Machinery, p. 694. PDF.

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This is literally the most useful thread there could possibly be for me because there are times I think "I would really like to learn about X" but don't know what the names for X in an academic setting.

So, top of my mind:

• Neuroscience of art & art appreciation
• Evolutionary basis for storytelling
• Something about disorders like Cotard's and what they mean for our understanding of consciousness

Is this a monthly thread btw? If not, it should!

I want to learn more about the basics of pathopsychology. I have read about different mental illnesses at various times in different contexts but I never really studied the basics of the standard concepts of the different mental illnesses.

Which textbook or pop-science book gives a good overview?

Tangentially, I thought you might find repair theory interesting, if not useful. Briefly, when students make mistakes while doing arithmetic, these mistakes are rarely the effect of a trembling hand; rather, most such mistakes can be explained via a small set of procedural skills that systematically produce incorrect answers.

I think there's a consistent epistemic failure that leads to throwing away millennia of instrumental optimization of group dynamics in favor of a clever idea that someone had last Thursday. The narrative of extreme individual improvement borders on insanity: you think you can land on a global optimum with 30 years of one-shot optimization?

Academia may have a better process, and individual intelligence may be more targeted, but natural + memetic selection has had a LOOOT more time and data to work with. We'll be much stronger for learning how to leverage already-existing processes than in learning how to reinvent the wheel really quickly.