timelets

"We are prone to think that we have here are degrees of certainty, with 2+2=4 enjoying the highest certainty. We don't realize that what we have here are not degrees of certainty, but kinds of certainty. And the kinds of certainty are as various as the kinds of proposition in question. *"

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This crucial point is often lost in probability calculations. Nassim Taleb gets it though.

* “Different kinds of certainty have different kinds of grounds. And what it is that is certain is, in each such case, a categorially different kind of proposition. The grounds for mathematical certainty are deductive proofs, and mathematical propositions are rules, not descriptions. The certainty of a perceptual statement such as ‘The curtains are red’ lies in its being evident to the senses – look and see! The certainty of an empirical prediction is determined by its conclusive empirical evidence. And the certainty of a highly theoretical proposition of science, such as e = mc2, is determined by the holistic confirmation of the theory of which it is a part.
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What applies to certainty applies also to truth.
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Empirical propositions, mathematical propositions, logical propositions and ethical propositions are categorially different. And that’s why what it is for propositions of categorially different kinds to be true is also so different, even though the term ‘true’ is unequivocal.”

Peter Hacker;. “A Beginner's Guide to the Later Philosophy of Wittgenstein.”

AI [mis-]alignment amplifies human alignment problem:

Right now, workers are potentially training AI how to make them obsolete. And they often don’t realize it.

The kind of AI used by companies, called an enterprise AI system, can capture everything you do at work and use that information to train itself. These systems can record your interactions within the platform—the prompts you write, the documents you create, the queries you run.

In other words, the company can potentially track—and claim ownership of—every keystroke you make within the system, every idea you document there, every tool you build using that platform.


This dynamic may fundamentally change the relationship between employer and employee. The stakes are so high and so urgent that both sides are rushing to position (or protect) themselves. Executives are rapidly implementing enterprise AI systems, seeking productivity gains and competitive advantage—and they often aren’t disclosing the implications for job security and privacy. Meanwhile, at least some employees are secretly adopting personal AI tools, sometimes violating corporate policies, so that their employers can’t capture everything they know and do.

Individual opt-out of AI is often impossible, so unions and professional associations need to pay attention. With collective bargaining, workers could demand transparency about the use of enterprise AI and demand fair compensation for the knowledge it gathers. Without collective power, individual employees will keep clicking “accept” on agreements that restructure their jobs simply because they have no alternative.

https://www.wsj.com/lifestyle/careers/ai-knowledge-capture-employees-a69a0e1c

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However, this would require shifting incentives away from maximizing engagement and toward epistemic responsibility, which is difficult given current business models.

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It would be an interesting challenge to come with up a technology and a business model that solves the problem.

Also related https://youtu.be/qlPHGnChhI4?si=03mDoaAYAFJnEfCE&t=4004

truth conditions (theoretical intentionality) vs satisfaction conditions (practical intentionality)

The great characteristic of the mathematical mind is its capacity for
dealing with abstractions; and for eliciting from them clear-cut
demonstrative trains of reasoning, entirely satisfactory so long as it
is those abstractions which you want to think about. The enormous
success of the scientific abstractions, yielding on the one hand
_matter_ with its _simple location_ in space and time, and on the other
hand _mind_, perceiving, suffering, reasoning, but not interfering, has
foisted onto philosophy the task of accepting them as the most concrete
rendering of fact.

Thereby, modern philosophy has been ruined.

-- Whitehead. Science ..., 1925

A good checklist:

“... modules are task specific, problem specific, or opportunity specific as often as domain specific, if not more often. Still, ontology is a terrain that inferential modules typically exploit.”

--Dan Sperber. “The Enigma of Reason: A New Theory of Human Understanding.”

I guess, "task" here is synonymous to "routine."

To make a Secondary World inside which the green sun will be credible, commanding Secondary Belief, will probably require labour and thought, and will certainly demand a special skill, a kind of elvish craft.
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A reason, more important, I think, than the inadequacy of stage-effects, is this: Drama has, of its very nature, already attempted a kind of bogus, or shall I say at least substitute, magic: the visible and audible presentation of imaginary men in a story. That is in itself an attempt to counterfeit the magician's wand.
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if you prefer Drama to Literature (as many literary critics plainly do), or form your critical theories primarily from dramatic critics, or even from Drama, you are apt to misunderstand pure story-making, and to constrain it to the limitations of stage-plays. You are, for instance, likely to prefer characters, even the basest and dullest, to things. Very little about trees as trees can be got into a play.


J.R.R. Tolkien, Of Fairy Stories.

It's probably not a coincidence that flourishing of Fantasy in movies is happening alongside major technological advances in audio-video. Paradoxically, technology enables magic.

...the simplicity of the perceptual judgment on which the setting up of the proof culminated is what made the difference and carried conviction. Pasteur was not stinting in the laboratory and outside in concentrating interest and discussion on a few extremely simple perceptual contrasts: ab­ sence/presence; before/after; living/dead; pure/impure.
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even if the Pasteurians developed a biology in the laboratory, they did not practice a labo­ratory biology. They did not leave to others, as apparently happened in England, the job of using or applying their results, contenting themselves with "pure science."

--- BL, TPoF, 1993.

cf. AlphaGo.
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A couple of good quotes about how a problem statement shapes its potential solution.
https://youtu.be/sje2AZOrww0?t=1051

Let's suspending our moral judgement for a minute.
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