Imagine if there was a financial pundit who kept saying "Something really bad is brewing in the markets and we may be headed for a recession. But we can't know when recessions will come, nobody can predict them". And then every time there was a selloff in the market, they...
Take all the metaphysical models of the universe that any human ever considers. Say there are n number of mutually-incompatible ones. I don't have a good definition of this, so our estimates will vary by orders of magnitude. Start with 1:1 odds, or a 50% chance that one of them...
Katherine Milkman on Twitter notes how far off the epidemiological expert forecasts were in the linked sample: https://twitter.com/katy_milkman/status/1244668082062348291 They gave an average estimate of 20,000 cases. The actual outcome was 122,653 by the stated date in the U.S. That's off by a factor of 6.13, and those were experts. Only...
Punching people in the face is generally a bad idea. Not only is it likely to get you in trouble, but the face is one big crumple zone. Jaw, teeth, cheekbones, those are all hard and pointy. Your handbones are fragile. If you manage to put power behind the hit, they are going to have a very visible injury, which can put the observers on their side.
I think this description missed the biggest reason that head-blows are bad. Concussions are long-term cumulative. This includes shakes that are FAR gentler than "comatose" levels of head trauma. When someone gets punched in the head, the world becomes slightly more depressed, slightly more demented, and slightly dumber. Never willingly get punched in the head.
Strong upvoted because I doubt the implications will be adequately appreciated in all of LW/EA. Some cause ideas are astronomically noisy. Sometimes almost deliberately, in the service of "finding" the "highest potential" areas.
Above some (unknown) point, the odds they're somehow confused/exaggerating should rise faster than further increments up the ostensible value. I'm sure they'll claim to have sufficiently strong insight, to pull it back to the top of the EV curve. This doesn't seem credible, even though I expect the optimal effort into those causes is >0, and even though their individual arguments are often hard to argue against.
1. AGI is happening soon. Significant probability of it happening in less than 5 years.
[Snip]
We don’t have any obstacle left in mind that we don’t expect to get overcome in more than 6 months after efforts are invested to take it down.
Forget about what the social consensus is. If you have technical understanding of current AIs, do you truly believe there are any major obstacles left? The kind of problems that AGI companies could reliably not tear down with their resources? If you do, state so in the comments, but please do not state what those obstacles are.
"AGI" here is undefined, and so is "significant probability". When I see declarations in this format, I downgrade my view of the epistemics involved. Reading stuff like this makes me fantasize about not-yet-invented trading instruments, without the counterparty risk of social betting, and getting your money.
This framing isn't meaningful, nor useful. All 3 of those are ambiguous.
The point of any of this is to better predict human behavior, and better describe variation in behavior between people. That's the value pitch that society might plausibly get, from taxonomizing personality tendencies. These should be updated based on actual data, and whatever makes them more predictive. Not just speculation.
So for example, when HEXACO began distinguishing Honesty-Humility from Agreeableness, that wasn't done because someone speculated that they thought a 6th trait made sense to them. Including more languages in the lexical studies resulted in a 6th factor emerging from the factor analysis. So it's a more representative depiction of the clusterings,... (read more)
I confess I don't know what it means to talk about a person's value as a soul. I am very much in that third group I mentioned.
On an end to relative ability: is this outcome something you give any significant probability to? And if there existed some convenient way to make long-term bets on such things, what sorts of bets would you be willing to make?
There is intense censorship of some facts of human traits, and biology. Of the variance in intelligence and economic productivity, the percent attributable to genetic factors is >0%. But almost nobody prestigious, semi-prestigious -- nor anything close -- can ever speak of those facts, without social shaming. You'd probably be shamed before you even got to the question of phenotypic causation -- speaking as if the g factor exists would often suffice. (Even though g factor is an unusually solid empirically finding, in fact I can hardly think of any more reliable one from the social sciences.)
But with all the high-functioning and prestigious people filtered out, the topic is then heavily influenced... (read more)
Sorry if I'm just misreading -- in Compute Trends Across Three eras of Machine Learning it was shown that the doubling time (at that time) had slowed to every ~10 months for the large-scale projects. In this projection you go with a 6-month doubling time for x number of years, then slowing to every 20 months. My questions are:
This was a contorted and biased portrayal of the topic. If you're a reader in a hurry, skip to my last paragraph.
First, this needs clarification on who you mean by a "fox", and who you don't. There's a very high risk of confusion, or talking about unrelated things without noticing. It may help if you name 5 people you consider to be foxes, and 5 you consider to be hedgehogs.
For the rest of this comment, I'm going to restrict "fox" to "good-scoring generalist forecaster", because they would tend to be quite fox-like, in the Tetlockian sense, and you did mention placing probabilities. If there are non-forecasters you would include in your taxonomy... (read 1756 more words →)
Imagine if there was a financial pundit who kept saying "Something really bad is brewing in the markets and we may be headed for a recession. But we can't know when recessions will come, nobody can predict them". And then every time there was a selloff in the market, they tell everyone "I've been saying we were headed for trouble", taking credit. This doesn't work as a forecasting track record, and it shouldn't be thought of that way.
If they want forecaster prestige, their forecasts must be:
Take all the metaphysical models of the universe that any human ever considers.
Say there are n number of mutually-incompatible ones. I don't have a good definition of this, so our estimates will vary by orders of magnitude.
Start with 1:1 odds, or a 50% chance that one of them is correct, and a 50% chance that none were correct.
0.5/n is the prior for a given individual metaphysical model.
You might have opinions about "50%". Maybe you think humans are actually way less likely than that to ever think of the "right" one. Maybe you think we're almost guaranteed to, for some reason. I started with a very general, unimposing prior of 1:1 odds. We... (read 199 more words →)
Katherine Milkman on Twitter notes how far off the epidemiological expert forecasts were in the linked sample:
https://twitter.com/katy_milkman/status/1244668082062348291
They gave an average estimate of 20,000 cases. The actual outcome was 122,653 by the stated date in the U.S. That's off by a factor of 6.13, and those were experts. Only 3 out of 18 survey respondents managed to get the actual outcome to fall in their 80% confidence interval. If they were perfectly calibrated on this one-off prediction, about 14 should've had the actual outcome fall in their 80% confidence interval. EDIT: No that's not right; Daniel Filan points out that we wouldn't expect 14 of 18 to get... (read 157 more words →)
I suspect this heuristic (if adopted) might be easy to Goodhart, or cheaply imitate. I like the intention behind it though.