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Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Whether you should do a PhD doesn't depend much on timelines., published by alex lawsen (previously alexrjl) on March 22, 2023 on The Effective Altruism Forum.I wrote this as an answer to a question which I think has now been deleted, so I copied it to my shortform in order to be able to link it in future, and found myself linking to it often enough that it seemed worth making a top-level post, in particular because if there are important counterarguments I haven't considered I'd like to come across them sooner rather than later! I'd usually put more thought into editing a top-level post, but the realistic options here were not post it at all, or post it without editing.Epistemic status: I've thought about both how people should thinking about PhDs and how people should think about timelines a fair bit, both in my own time and in my role as an advisor at 80k, but I wrote this fairly quickly. I'm sharing my take on this rather than intending to speak on behalf of the whole organisation, though my guess is that the typical view is pretty similar.BLUF:Whether to do a PhD is a decision which depends heavily enough on personal fit that I expect thinking about how well you in particular are suited to a particular PhD to be much more useful than thinking about the effects of timelines estimates on that decision.Don’t pay too much attention to median timelines estimates. There’s a lot of uncertainty, and finding the right path for you can easily make a bigger difference than matching the path to the median timeline.Going into a bit more detail - I think there are a couple of aspects to this question, which I’m going to try to (imperfectly) split up:How should you respond to timelines estimates when planning your career?How should you think about PhDs if you are confident timelines are very short?In terms of how to think about timelines in general, the main advice I’d give is to try to avoid the mistake of interpreting median estimates as single points. Taking this metaculus question as an example, which has a median of July 2027, that doesn’t mean the community predicts that AGI will arrive then! The median just indicates the date by which the community thinks there’s a 50% chance the question will have resolved. To get more precise about this, we can tell from the graph that the community estimates:Only a 7% chance that AGI is developed in the year 2027A 25% chance that AGI will be developed before August of next year.An 11% chance that AGI will not be developed before 2050A 9% chance that the question has already resolved.A 41% chance that AGI will be developed after January 2029 (6 years from the time of writing).Taking these estimates literally, and additionally assuming that any work that happens post this question resolving is totally useless (which seems very unlikely), you might then conclude that delaying your career by 6 years would cause it to have 41/91 = 45% of the value. If that’s the case, if the delay increased the impact you could have by a bit more than a factor of 2, the delay would be worth it.Having done all of that work (and glossed over a bunch of subtlety in the last comment for brevity), I now want to say that you shouldn’t take the metaculus estimates at face value though. The reason is that (as I’m sure you’ve noticed, and as you’ve seen in the comments) they just aren’t going to be that reliable for this kind of question. Nothing is - this kind of prediction is really hard.The net effect of this increased uncertainty should be (I claim) to flatten the probability distribution you are working with. This basically means it makes even less sense than you’d think from looking at the distribution to plan for AGI as if timelines are point estimates.Ok, but what does this mean for PhDs?Before I say anything about how a PhD decision intera...
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