I know a lot of people through a shared interest in truth-seeking and epistemics. I also know a lot of people through a shared interest in trying to do good in the world.
I think I would have naively expected that the people who care less about the world would be better at having good epistemics. For example, people who care a lot about particular causes might end up getting really mindkilled by politics, or might end up strongly affiliated with groups that have false beliefs as part of their tribal identity.
But I don’t think that this prediction is true: I think that I see a weak positive correlation between how altruistic people are and how good their epistemics seem.
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I think the main reason for this is that striving for accurate beliefs is unpleasant and unrewarding. In particular, having accurate beliefs involves doing things like trying actively to step outside the current frame you’re using, and looking for ways you might be wrong, and maintaining constant vigilance against disagreeing with people because they’re annoying and stupid.
Altruists often seem to me to do better than people who instrumentally value epistemics; I think this is because valuing epistemics terminally has some attractive properties compared to valuing it instrumentally. One reason this is better is that it means that you’re less likely to stop being rational when it stops being fun. For example, I find many animal rights activists very annoying, and if I didn’t feel tied to them by virtue of our shared interest in the welfare of animals, I’d be tempted to sneer at them.
Another reason is that if you’re an altruist, you find yourself interested in various subjects that aren’t the subjects you would have learned about for fun--you have less of an opportunity to only ever think in the way you think in by default. I think that it might be healthy that altruists are forced by the world to learn subjects that are further from their predispositions.
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I think it’s indeed true that altruistic people sometimes end up mindkilled. But I think that truth-seeking-enthusiasts seem to get mindkilled at around the same rate. One major mechanism here is that truth-seekers often start to really hate opinions that they regularly hear bad arguments for, and they end up rationalizing their way into dumb contrarian takes.
I think it’s common for altruists to avoid saying unpopular true things because they don’t want to get in trouble; I think that this isn’t actually that bad for epistemics.
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I think that EAs would have much worse epistemics if EA wasn’t pretty strongly tied to the rationalist community; I’d be pretty worried about weakening those ties. I think my claim here is that being altruistic seems to make you overall a bit better at using rationality techniques, instead of it making you substantially worse.
I used to think that slower takeoff implied shorter timelines, because slow takeoff means that pre-AGI AI is more economically valuable, which means that economy advances faster, which means that we get AGI sooner. But there's a countervailing consideration, which is that in slow takeoff worlds, you can make arguments like ‘it’s unlikely that we’re close to AGI, because AI can’t do X yet’, where X might be ‘make a trillion dollars a year’ or ‘be as competent as a bee’. I now overall think that arguments for fast takeoff should update you towards shorter timelines.
So slow takeoffs cause shorter timelines, but are evidence for longer timelines.
This graph is a version of this argument: if we notice that current capabilities are at the level of the green line, then if we think we're on the fast takeoff curve we'll deduce we're much further ahead than we'd think on the slow takeoff curve.
For the "slow takeoffs mean shorter timelines" argument, see here: https://sideways-view.com/2018/02/24/takeoff-speeds/
This point feels really obvious now that I've written it down, and I suspect it's obvious to many AI safety people, including the people whose writings I'm referencing here. Thanks to Caroline Ellison for pointing this out to me, and various other people for helpful comments.
I think that this is why belief in slow takeoffs is correlated with belief in long timelines among the people I know who think a lot about AI safety.
I don't really know how to think about anthropics, sadly.
But I think that it's pretty likely that nuclear war could have not killed everyone. So I still lose Bayes points compared to the world where nukes were fired but not everyone died.
It's tempting to anthropomorphize GPT-3 as trying its hardest to make John smart. That's what we want GPT-3 to do, right?
I don't feel at all tempted to do that anthropomorphization, and I think it's weird that EY is acting as if this is a reasonable thing to do. Like, obviously GPT-3 is doing sequence prediction--that's what it was trained to do. Even if it turns out that GPT-3 correctly answers questions about balanced parens in some contexts, I feel pretty weird about calling that "deliberately pretending to be stupider than it is".
If the linked SSC article is about the aestivation hypothesis, see the rebuttal here.
Remember that I’m not interested in evidence here, this post is just about what the theoretical analysis says :)
In an economy where the relative wealth of rich and poor people is constant, poor people and rich people both have consumption equal to their income.
I agree that there's some subtlety here, but I don't think that all that happened here is that my model got more complex.
I think I'm trying to say something more like "I thought that I understood the first-order considerations, but actually I didn't." Or "I thought that I understood the solution to this particular problem, but actually that problem had a different solution than I thought it did". Eg in the situations of 1, 2, and 3, I had a picture in my head of some idealized market, and I had false beliefs about what happens in that idealized market, just like I'd be able to be wrong about the Nash equilibrium of a game.
I wouldn't have included something on this list if I had just added complexity to the model in order to capture higher-order effects.
I agree that the case where there are several equilibrium points that are almost as good for the employer is the case where the minimum wage looks best.
Re point 1, note that the minimum wage decreases total consumption, because it reduces efficiency.
I've now made a Guesstimate here. I suspect that it is very bad and dumb; please make your own that is better than mine. I'm probably not going to fix problems with mine. Some people like Daniel Filan are confused by what my model means; I am like 50-50 on whether my model is really dumb or just confusing to read.
Also don't understand this part. "4x as many mild cases as severe cases" is compatible with what I assumed (10%-20% of all cases end up severe or critical) but where does 3% come from?
Yeah my text was wrong here; I meant that I think you get 4x as many unnoticed infections as confirmed infections, then 10-20% of confirmed cases end up severe or critical.
I think Anna and Rob answered the main questions here, but for the record I am still in the business of talking to people who want to work on alignment stuff. (And as Anna speculated, I am indeed still the person who processes MIRI job applications.)