By the way, I had a quick look at what PersonalityMap reports about how intelligence and ethics are correlated among humans. The websites provides an interface to query a pretty powerful AI model that is able to predict correlations (psychological, behavioral etc.) very well. The most suitable starting question that might correlate with high intelligence that I found was “What was your ACT score, between 1 and 36?” (although one could also just work with some made-up claim like “What’s your IQ?” or “Would you describe yourself as unusually intelligent?” or so, that the prediction model could probably work with almost as well). I then checked the correlation of this with some phrases that are vaguely related to doing good:
So, based on this, it appears that at least among humans (or rather, among the types of humans who’s data is in the database of PersonalityMap, which is likely primarily people from the US), intelligence and morality are not (meaningfully/positively) correlated, so locally this does look like evidence for the Orthogonality thesis holding up. Of course we can’t just extrapolate this to AI, let alone AGI/ASI. But maybe still an interesting data point. (Admittedly this is only tangentially related to your actual post, so sorry if this is a little off-topic)
So, I was wondering whether this is usable in anki, and indeed, there appears to be a simple setting for it without even having to install a plugin, as described here in 4 easy steps. I’ll see if it makes a notable difference.
Not so relatedly, this made me realize a connection I hadn’t really thought about before: I wish music apps like Spotify would use something vaguely like spaced repetition for Shuffle mode. In the sense of finding some good algorithm to predict, based on past listening behavior, which song in a playlist the user is most likely to currently enjoy, and weighing their occurrences in shuffle mode accordingly. One could, very roughly, treat skipping a song as getting a flashcard right—it will then have some exponential backoff before it returns. But not skipping the song would be roughly like getting a card wrong, and it will show up again very soon. Of course, the algorithm shouldn’t quite be the same, e.g. listening to a song once without skipping shouldn’t have such a drastic effect (as typically the user may not be paying much attention to the music, so not skipping is a rather weak signal). But, yeah… I kind of doubt these platforms are working on anything like this, as they most likely don’t care much about such intangible value propositions that are hard to measure in A/B tests.