All of Lê Nguyên Hoang's Comments + Replies

Thanks for the interesting comment. Perhaps to clarify, our current algorithms are by no means a final solution. In fact, our hope is to collect an interesting database to then encourage research on better algorithms that will factor, e.g., the comments on the videos.

Also, in the "settings" of the rating page, we have a functionality that allows contributors to input both their judgments and their confidence in their judgments, on a scale from 0 to 3 stars (default is 2). One idea could be to demand comments when the contributor claims a 3-star confidence judgment. This can allow disputes in the comment section.

Hi Apodosis, I have done my PhD in Bayesian game theory, so this is a topic close to my heart ˆˆ There are plenty of fascinating things to explore in the study of interactions between Bayesians. One important finding of my PhD was that, essentially, Bayesians end up playing (stable) Bayes-Nash equilibria in repeated games, even if the only feedback they receive is their utility (and in particular even if the private information of other players remain private). I also studied Bayesian incentive-compatible mechanism design, i.e. coming up with rules that in

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I promoted Bayes-up on my YouTube channel a couple of times 😋 (and on Twitter)

The YouTube algorithm is arguably an example of a "simple" manipulative algorithm. It's probably a combination of some reinforcement learning and a lot of supervised learning by now; but the following arguments apply even for supervised learning alone.

To maximize user engagement, it may recommend more addictive contents (cat videos, conspiracy, ...) because it learned from previous examples that users who clicked on one such content tended to stay longer on YouTube afterwards. This is massive user manipulation at scale.

Is this an existential... (read more)

This is probably more contentious. But I believe that the concept of "intelligence" is unhelpful and causes confusion. Typically, Legg-Hutter intelligence does not seem to require any "embodied intelligence".

I would rather stress two key properties of an algorithm: the quality of the algorithm's world model and its (long-term) planning capabilities. It seems to me (but maybe I'm wrong) that "embodied intelligence" is not very relevant to world model inference and planning capabilities.

Don't make the mistake of basing your notions of AI on uncomputable formalisms. That mistake has destroyed more minds on LW than probably anything else.

By the way, I've just realized that the Wikipedia page on AI ethics begins with robots. 😤