NYU faculty member, working on AI/cognitive science/crowdsourcing issues involving language understanding. Newish to EA.


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How to run a high-energy reading group

Riffing on this, there's an academic format that I've seen work well that doesn't fit too neatly into this rubric:

At each meeting, several people give 15-30m critical summaries of papers, with no expectation that the audience looks at any of the papers beforehand. If the summaries prompt anyone in the audience to express interest or ask good questions, the discussion can continue informally afterward.

This isn't optimized at all for producing new insights during the meeting, but I think it works well in areas (like much of AI) where (i) there's an extremely large/dense literature, (ii) most papers make a single point that can be summarized relatively briefly, and (iii) it's possible to gather a fairly large group of people with very heavily overlapping interests nad vocabulary.

RyanCarey's Shortform

This is probably overstated—at most major US research universities, tenure outcomes are fairly predictable, and tenure is granted in 80-95% of cases. This obviously depends on your field and your sense of your fit with a potential tenure-track job, though.

That said, it is much easier to do research when you're at an institution that is widely considered to be competitive/credible in your field and subfield, and the set of institutions that gets that distinction can be smaller than the (US) top 100 in many cases. So, it may often make sense to go for a postdoc if you think it'll increase your odds of getting a job at a top-10 or top-50 institution.

Estimation of probabilities to get tenure track in academia: baseline and publications during the PhD.

Academic here:

  • Essentially all of these numbers vary wildly  across subfields, across countries, and on other assumptions like how prestigious the labs are that you're considering. Judging based on numbers from physics, or from US PhDs overall, could leave you off by an order of magnitude or more. They also vary significantly over time. 
  • The populations in PhD programs vary a lot from field to field as well, and how you fit relative to those populations will help tilt the odds. Being intrinsically motivated and a good English writer (the two things I can tell about the OP) could give you a pretty big leg up in your odds of finishing and getting a job relative to the median CS PhD student at a good US research university, at least assuming that you have the technical qualifications to be admitted. In a Philosophy program, by contrast, that'd be baked into the admissions criteria, and wouldn't tell me much.
  • FWIW, here are some ballpark 80% confidence intervals based only on my recent experience. These are conditioned on what I know about the OP (AI safety area, good English writer, intrinsically motivated). I'm focusing on the US because that's what I know, and I'm generally assuming top-50-or-so universities in CS, which is where you can be reasonably confident that you'll have the resources and public platform to do high-impact research. I work in AI, but I don't have much yet experience with AI safety. I have been involved in general admissions for two PhD programs with an AI focus, and two others.
    • P(admission to a good PhD program | serious effort at applying) = 
       1-15% without substantial prior research experience, 
       5-60% with limited research experience (at least one serious paper with a recognized collaborator, but nothing presented as a first author at a competitive venue)
       50-90% with strong research experience (at least one paper with a recognized collaborator, presented as a first author at a competitive venue).
    • P(graduate within six years | enroll) = 70-95%
    • P(assistant professor job at a US top-100 research university directly after PhD | graduate within six years and apply) = 5-50%
      P(assistant professor job at a top-100 research university  within three years after PhD | graduate within six years and apply) = 30-75%
      P(long-term US research job that supports publishing, academic or otherwise, within three years after PhD | graduate within six years and apply) = 85-95%
    • P(granted permanent tenure within nine years of starting as an assistant professor | make a serious attempt to stay) = 85%-98%
Is shareholder activism worth it?

Thanks, Wayne!

This looks like a good starting point for further research, but it's hard to take much that's actionable from this without more background in finance. Is there anything you'd take away as advice to a smallish-scale individual investor?

Is shareholder activism worth it?

Thanks! This is helpful, and nudging me away from this approach.

Do you know of any good primers to get a better sense of how/when these levers get used on socially relevant issues?

Is shareholder activism worth it?

Hrm, this is useful context, but I think you may be getting at a different issue. For the mutual funds that I'm looking at, they seem to be viewing shareholder activism as a potential avenue to have prosocial (ESG) impact on the companies that they invest in, such that their activism strategy likely increases fees a bit without impacting returns either way.