Thanks :)
I will reviel the true answer to 2 in about a week, in case anyone else want to take a guess.
To some extent "goodness" is some ever moving negotiated set of norms of how one should behave.
I notice that when I use the word "good" (or envoke this consept using other words such as "should"), I don't use it to point to the existing norms, but as a bid for what I think these norms should be. This sometimes overlap with the existing norms and sometimes not.
E.g. I might say that it's good to allow lots of diffrent subcultures to co-exist. This is a vote for a norm where peopel who don't my subculture leave me and my firends alone, in exchange for us leaving them alone. This is not unrelated to me getting what is jummy to me, but it at least one step removed.
"Good" is the set of norms we use to coordinate cooperation. If most people don't like when you pick your nose in public, then it's good to make an effort not to do so, and similar for a lot of other values. Even if you don't care about the nose picking, you probably care about some other of the things "good" coordinates around. For most people it's probably worth supporing the package deal. But I also think you "should" use your voice to help imrove the notion of what is "good".
In this example, Mr. A has learned the average numbers of red, yellow, and green orders for some past days and wants to update his predictions of today's orders on this information. So he decides that the expected values of his distributions should be equal to those averages, and that he should find the distribution that makes the least assumptions, given those constraints. I at least agree that entropy is a good measure of how little assumptions your distribution makes. The point I'm confused about is how you get from "the average of this number in past observations is N" to "the expected value of our distribution for a future observation has to be N but we should put no other information in it".
I agree that it's implausible that Mr A has enough data to be confident of the averages, but not enough data to draw any other conclutions. Such is often the case with math execises. :shrug:
Second, why are you even finding a distribution that is constrainedly optimal in the first place, rather than just taking your prior distribution over sequences of results and your observations, and using Bayes' Theorem to update your probabilities for future results? Even if you don't know anything other than the average value, you can still take your distribution over sequences of results, update it on this information (eliminating the possible outcome sequences that don't have this average value), and then find the distribution P(NextResult|AverageValue) by integrating P(NextResult|PastResults)P(PastResults|AverageValue) over the possible PastResults. This seems like the correct thing to do according to Bayesian probability theory, and it's very different from doing constrained optimization to find a distribution.
In the example in the post, what would you say is the "prior distribution over sequences of results"? All Mr A has is a probability distribution for widgets each day. If I would naively turn that in distributions over sequences of widget orders each day, the simplest option is to assume inedpenent draw from that distribution each day. But then Mr A is in the same situation as the "poorly informed robot"
The reason one can't use Bayes rule in this case is because of a type error. If Mr A had a prior probaility distribution over probability distributions, P[P_i], then he could use Bays rule, to calculate a posteriour of P[P_i], and then integrage P_final = Sum_i P[P_i] P_i. But the porblem with this is that the anser will defpend on how you generalise from P[N,N,N] to P[P_i], and there isn't a unique way to do this.
The same consept where independently invented by a larp organsier I know. Unfortunatly I stronly dislike the words they chose, so I will not repeat them. But it occurs to me that the consept of "final responsibility", or "the buck stops here", is so universaly usefull, that it's wierd that there isn't some more common term for it.
I notice that everything you list has to do with finding things. This matches my expereince. Printing is hell when ever I try to prin somewhere new. And since I print so rearely now days, this is the typical expereince. But I remember a time where I printed more often, then it was molsty just click "print" and it worked.
It seems like printers are built to be set up onece, and then be your forever printer? Which is no longer a good match for how you (and me) use printers.
Questsions for John or anyone that feels like answering:
I designed and had printed physical Hero Licences (business card size), that I've haned out at various EAGs. If anyone wants a stack to boost your Mysterious Old Wizard powers, let me know.
I got them becasue I thougt it would be a good idea, becasue I noticed that some people just need permission. But even so, I was supprised how much these where appriciated.
This post is also a good description of why I'm typically not interested in someone elses's steal-manning or devlis-advocating for a possition they don't hold. The result is often a shallow simulation, in some ways simular to an LLM ouptput, and uninteresing for the same reasons.
I didn't have this analogy untill now, becasue I've been anoyed at this since before the LLM eara, and I didn't make the connection untill this pot.
I'm supprised that intrumental convergence wasn't covered in the book. I didn't even notice it was left out untill reading this review.
Here's some alternative sources in anyone prefeers text over video:
I mean trying to signal something more specific than, e.g. dressing according to the norms of ones profession. Anything that the person would expect others to understand as some other information than "I belong here", or I have X official role.
E.g. haivng a high-vis vest if you're a rode workier, or wearing nicer cloths if you're at a dress-up occation does not count. Whereing a t-skirt advertising you like chess counts, if and only if you're not currently at a chess club, and you chose it deliberatly.