Do you tell every high school quarterback to drop everything and focus on getting in the NFL? Encouraging people to aim for low-probability events with huge failure downsides is almost cruel. You know what is likely to happen to Bob if he drops out? He’s likely to waste all his day on video-games because he’s addicted to them, and only the social pressures of school managed to break through his addiction to make him actually do stuff. All his friends are still in school and find his decision baffling, they still talk to him, but less and less over time. You know what becomes really hard once you drop out? Finding a girlfriend. Suddenly a year goes by with only a barely functional iphone app to show for it, and while Bob hasn’t quite ruined his life, he is cursing his stupidity for dropping out of an ivy league school.
There are safer ways to experiment: ask for a semester off, try to build something during summer break instead of going at a fancy internship, maybe focus only the bare minimum on your classes while you do something else on the side, or take graduate level classes while you’re first-year undergrad, or sacrifice your social life and sleep to work on something else concurrently with classes. Failing at any of these leaves you in a recoverable position.
I think the fundamental misunderstanding here is that you are attributing a much smaller success probability to my ideas than me.
It is very likely that becoming highly skilled at AI outside of college will make you both useful (to saving the world) and non-homeless. You will probably make more progress toward your goal than if you stayed “tracked” (for almost any goal, assuming short AI timelines).
Bob isn’t likely to waste all his day on video-games? I wonder why you think that? I mean, conditional on him being addicted, perhaps. But surely if that was his problem, then he should focus on solving it.
Do you somehow attribute lower capabilities to people than I do? I certainly think that Bob can figure out a way to learn more effectively than his college can provide. He can prove this to himself if he has doubts.
None of this is the point. Many people have much more ability to take risk than we assume. Giving people overly risk-averse advice, and assuming the bad case scenario as highly likely as you are doing right now, seems very hurtful.
The last few jobs I got were from techs I put on my CV after spending a few weeks toying with them in my free time.
At some point I quit my job and decided to take all my savings and spend as long as I could working on open-source projects in Rust.
I’m currently in a job with triple the pay of the previous one, thanks to networking and experience I got after I quit.
So while my experience isn’t relevant to AI safety, it’s pretty relevant to the whole “screw the hamster wheel, do something fun” message.
And my advice to Alice and Bob would still be “Fuck no, stay in your Ivy League school!”
I don’t care how much of a genius you are. I think I’m a genius, and part of why I’m getting good jobs is my skills, but the other part is there’s a shiny famous school on my resume. Staying in that school gave me tons of opportunities I wouldn’t have had by working on my own projects for a few years (which is essentially what I did before joining that school).
There are measured risks and there are stupid risks. Quitting school is a stupid risk. Maybe you’re enough of a genius that you beat the odds and you succeed despite quitting school, but those were still terrible odds.
So, obviously my estimates of the chance of success for any given person will depend on the person, for all I know an hour-long talk with you would completely convince me that this is the right decision for you, but for the median ivy-leaguer CS student, I am really not convinced, and for the median CS student outside good schools, it’s definitely a bad idea, most CS students really are much dumber than you’d think. If you have a track record of being able to complete long personal projects with no outside motivation or enforcement mechanism, under the stress of your livelihood depending on the success of this project (and the stress of your parents and friends not understanding what the hell you’re doing and thinking you’re ruining your life), then this is evidence that going off-track wouldn’t be disastrous. I have tried it, found it more difficult than I expected, and subsequently regretted it and went back to the normal track (though still with plenty of weird experiments within the track).
It is very likely that becoming highly skilled at AI outside of college will make you both useful (to saving the world) and non-homeless.
In the minds of hiring managers at normal companies, “AI experts” are a dime-a-dozen, because now those words have been devalued to mean whoever took Andrew Ng’s course on ML. You can’t get a data scientist job without a degree (which would presumably be the non-homeless fallback position), you certainly can’t get a research position at any of the good labs without a PhD, you can try publishing alone, but again this basically never happens. I suppose you could try winning Kaggle championships, but those have almost no relevance to AI safety, you could try making money by doing stock prediction with the numer.ai project, and making money that way (which is what I did), and that would provide some freedom to study what you want, but that’s again really hard. If you want to get grants from openPhil to do AI safety, that might be something, but really the skills you learn from getting good at AI safety have almost no marketable value, there is a very narrow road you can walk in this direction, and if anything goes wrong there isn’t much of a fallback position.
People can certainly handle more risk and more weirdness than they think, but there are many levels of risk increase between what the average student does and dropping out of school to focus on studying AI on your own.
Do you tell every high school quarterback to drop everything and focus on getting in the NFL? Encouraging people to aim for low-probability events with huge failure downsides is almost cruel. You know what is likely to happen to Bob if he drops out? He’s likely to waste all his day on video-games because he’s addicted to them, and only the social pressures of school managed to break through his addiction to make him actually do stuff. All his friends are still in school and find his decision baffling, they still talk to him, but less and less over time. You know what becomes really hard once you drop out? Finding a girlfriend. Suddenly a year goes by with only a barely functional iphone app to show for it, and while Bob hasn’t quite ruined his life, he is cursing his stupidity for dropping out of an ivy league school.
There are safer ways to experiment: ask for a semester off, try to build something during summer break instead of going at a fancy internship, maybe focus only the bare minimum on your classes while you do something else on the side, or take graduate level classes while you’re first-year undergrad, or sacrifice your social life and sleep to work on something else concurrently with classes. Failing at any of these leaves you in a recoverable position.
I think the fundamental misunderstanding here is that you are attributing a much smaller success probability to my ideas than me.
It is very likely that becoming highly skilled at AI outside of college will make you both useful (to saving the world) and non-homeless. You will probably make more progress toward your goal than if you stayed “tracked” (for almost any goal, assuming short AI timelines).
Bob isn’t likely to waste all his day on video-games? I wonder why you think that? I mean, conditional on him being addicted, perhaps. But surely if that was his problem, then he should focus on solving it.
Do you somehow attribute lower capabilities to people than I do? I certainly think that Bob can figure out a way to learn more effectively than his college can provide. He can prove this to himself if he has doubts.
None of this is the point. Many people have much more ability to take risk than we assume. Giving people overly risk-averse advice, and assuming the bad case scenario as highly likely as you are doing right now, seems very hurtful.
To give my personal experience:
The last few jobs I got were from techs I put on my CV after spending a few weeks toying with them in my free time.
At some point I quit my job and decided to take all my savings and spend as long as I could working on open-source projects in Rust.
I’m currently in a job with triple the pay of the previous one, thanks to networking and experience I got after I quit.
So while my experience isn’t relevant to AI safety, it’s pretty relevant to the whole “screw the hamster wheel, do something fun” message.
And my advice to Alice and Bob would still be “Fuck no, stay in your Ivy League school!”
I don’t care how much of a genius you are. I think I’m a genius, and part of why I’m getting good jobs is my skills, but the other part is there’s a shiny famous school on my resume. Staying in that school gave me tons of opportunities I wouldn’t have had by working on my own projects for a few years (which is essentially what I did before joining that school).
There are measured risks and there are stupid risks. Quitting school is a stupid risk. Maybe you’re enough of a genius that you beat the odds and you succeed despite quitting school, but those were still terrible odds.
So, obviously my estimates of the chance of success for any given person will depend on the person, for all I know an hour-long talk with you would completely convince me that this is the right decision for you, but for the median ivy-leaguer CS student, I am really not convinced, and for the median CS student outside good schools, it’s definitely a bad idea, most CS students really are much dumber than you’d think. If you have a track record of being able to complete long personal projects with no outside motivation or enforcement mechanism, under the stress of your livelihood depending on the success of this project (and the stress of your parents and friends not understanding what the hell you’re doing and thinking you’re ruining your life), then this is evidence that going off-track wouldn’t be disastrous. I have tried it, found it more difficult than I expected, and subsequently regretted it and went back to the normal track (though still with plenty of weird experiments within the track).
In the minds of hiring managers at normal companies, “AI experts” are a dime-a-dozen, because now those words have been devalued to mean whoever took Andrew Ng’s course on ML. You can’t get a data scientist job without a degree (which would presumably be the non-homeless fallback position), you certainly can’t get a research position at any of the good labs without a PhD, you can try publishing alone, but again this basically never happens. I suppose you could try winning Kaggle championships, but those have almost no relevance to AI safety, you could try making money by doing stock prediction with the numer.ai project, and making money that way (which is what I did), and that would provide some freedom to study what you want, but that’s again really hard. If you want to get grants from openPhil to do AI safety, that might be something, but really the skills you learn from getting good at AI safety have almost no marketable value, there is a very narrow road you can walk in this direction, and if anything goes wrong there isn’t much of a fallback position.
People can certainly handle more risk and more weirdness than they think, but there are many levels of risk increase between what the average student does and dropping out of school to focus on studying AI on your own.