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While EA has always been rather demanding, it never felt as urgent as it does today. While it always seemed tremendously beneficial to contribute to immediately preventing the further transmission of Malaria, or reducing carbon emissions, or addressing other long term issues, the opportunity to do so never felt like it would disappear in the future, allowing for long term investments in oneself, like going to college. 

 

However, AI has changed this. Based on most indications from industry experts, and prediction markets, it seems both like AI is advancing faster than previous  expectations, and that AGI is rapidly approaching. Manifold gives about a 48% of AGI being developed before 2028[1], Metaculus [2] has a median estimate by 2030, and many public figures associated with AI have revised their timelines upwards[3][4].

 

I am currently in the undergraduate class of '28, and I honestly do not know what to do. If I just continue my trajectory as a CS major, the job market I face upon graduation may be hyper competitive to enter into due to advances in current AI alone (much less AGI). Honestly, I am now highly considering dropping out of college, or at least switching majors. What do you think?

 

I would really like to help the cause of AI safety, but I don't feel like I have the potential to be a genius AI researcher, and at the earliest I would be able to get a PHD in 2031. Maybe certain AI safety charities would be valuable to donate to?

 

 

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Without being able to comment on your specific situation, I would strongly discourage almost anyone who wants to have a highly impactful career from dropping out of college (assuming you don’t have an excellent outside option).

There is sometimes a tendency within EA and adjacent communities to critique the value of formal education, or to at least suggest that most of the value of a college education comes via its signaling power. I think this is mistaken, but I also suspect the signaling power of a college degree may increase—rather than decrease—as AI becomes more capable, and it may become harder to use things like, e.g., work tests to assess differences in applicants’ abilities (because the floor will be higher).

This isn’t to dismiss your concerns about the relevance of the skills you will cultivate in college to a world dominated by AI; as someone who has spent the last several years doing a PhD that I suspect will soon be able to be done by AI, I sympathize. Rather, a few quick thoughts:

  1. Reading the new 80k career guide, which touches on this to some extent (and seeking 80k advising, as I suspect they are fielding these concerns a lot).
  2. Identifying skills at the intersection of your interests, abilities, and things that seem harder for AI to replace. For instance, if you were considering medicine, it might make more sense to pursue surgery rather than radiology.
  3. Taking classes where professors are explicitly thinking about and engaging with these concerns, and thoughtfully designing syllabi accordingly.

My concerns are oriented around CS specifically, as I literally feel I am currently worse at coding than Chat GPT, that AI will continue to improve at it in the near term, and that the CS job market will become hyper competitive due to the combination of an oversupply/ backlog of CS majors and a shrinking number of job entries. 


Thanks for the recommendation about 80K advising, that seems like a good resource.

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"EA has always bee[n] rather demanding,"

I want to clarify that this is a common but generally incorrect reading of EA's views. EA leaders have repeatedly clarified that you don't need to dedicate your life to it, and can simply donate to causes that others have identified as highly effective, and otherwise live your life.

If you want to do more than that, great, good for you - but EA isn't utilitarianism, so please don't confuse the demandingness of the two.

Fair point. In the future I will think more about acknowledging that distinction, especially when engaging with an audience (unlike this one) which isn't already comfortable with EA.

Not an answer to your original question, but beware taking answers to the Metaculus question as reflecting when AGI will arrive, if by "AGI" you mean AI that will rapidly transform the world, or be able to perform literally every task humans perform as well as almost all humans. If you look at the resolution criteria for the question, all it requires for the answer to be yes, is that there is a model able to pass 4 specific hard benchmarks.  Passing a benchmark is not the same as performing well at all aspects of an actual human office or lab job. Furthermore, none of these benchmarks actually require being able to store memories long-term and act coherently on a time scale of weeks, two of the main things current models lack. It is a highly substantial assumption that any AI which can pass the Turing test, do well on a test of subject matter knowledge, code like a top human over relatively small time scales, and put together a complicated model car can do every economically significant task, or succeed in carrying out plans long-term, or have enough commonsense and adapatibility in practice to fully replace a white-collar middle manager or a plumber. 

Not that this means you shouldn't be thinking about how to optimize your career for an age where AI can do a lot of tasks currently done by humans, or even that AGI isn't imminent. But people using that particular Metaculus question to say "see, completely human-level or above on everything transformative AI" is coming soon, when that doesn't really match the resolution criteria, is a pet hate of mine. 

I agree on the Metaculus prompt being unclear, but the manifold market is far more clear. For the purposes of resolution: 

“Artificial General Intelligence (AGI) refers to a type of artificial intelligence that has the ability to understand, learn, and apply its intelligence to a wide variety of problems, much like a human being. Unlike narrow or weak AI, which is designed and trained for specific tasks (like language translation, playing a game, or image recognition), AGI can theoretically perform any intellectual task that a human being can. It involves the capability to reason, plan, solve problems, think abstractly, comprehend complex ideas, learn quickly, and learn from experience.”


That definition seems to imply a system that will permanently change the knowledge economy, but anyways, I am more interested in what I should do with my time before such a system is developed.

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