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Long-Term Future Fund: Ask Us Anything!

Hey Asya! I've seen that you've received a comment prize on this. Congratulations! I have found it interesting. I was wondering: you give these two reasons for rejecting a funding application

  • Project would be good if executed exceptionally well, but applicant doesn't have a track record in this area, and there are no references that I trust to be calibrated to vouch for their ability.
  • Applicant wants to do research on some topic, but their previous research on similar topics doesn't seem very good.

My question is: what method would you use to evaluate the track record of someone who has not done a Ph.D. in AI Safety, but rather on something like Physics (my case :) )? Do you expect the applicant to have some track record in AI Safety research? I do not plan on applying for funding on the short term, but I think I would find some intuition on this valuable. I also ask because I find it hard to calibrate myself on the quality of my own research.

What are you grateful for?

I am grateful for people like Jaime Sevilla who always have time to listen and give advice and help others in the community.

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

I just posted another article I found on average publication rates in Norway for different positions, ages, fields and gender.

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

I would say you basically cannot get tenure if you don't get a PhD, so dropouts are not taken into account in any of the previous statistics as far as I understood them. All this metrics are of the kind of: x% of PhD alumni got tenure, or similar.

I actually agree that taking into account the private sector could help, but I am much less certain about the freedom they give you to research those topics, beyond the usual suspects. That was why I was focussing on academia.

EA Uni Group Forecasting Tournament!

I'd like to know if we could inscribe a bit latter than the 12th of October. In Madrid we are opening an university group but it is not set up yet.

AMA: Markus Anderljung (PM at GovAI, FHI)

There is something I would really like to know, although it is only tangentially related to the above: how is taking a postdoctoral position at FHI seen comparatively with other "standard academia" paths? How could it affect future research career options? I am personally more interested from the technical side, but feel free to comment on whatever you feel is interesting.

And since you mention it: 
What EU AI Policy we should push for? And what mechanisms do you see the EU AI policy having a positive impact, compared with the US for example? What ways do you see for technical people to influence AI governance?

Many thanks in advance!

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

I strongly agree with Ryan that success is to a relatively large degree predictable, as can be done in the PCA decomposition of point 2 above, figure 1C.
I think it would be very valuable to have such a model, but the current code is only for biology (the impact factor will fail for instance for anything different). If one wanted to fit a model to predict it, it could probably use google scholar and arxiv, but the trickiest part would be to recover the position of those people (the target), which may partially be done using google scholar.

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

You're right Ryan, I'll modify the second complicated sentence. I am actually not sure what is the difference between tenure and tenure track, to tell the truth.

However, in one of the documents above I saw that institution is not such a strong predictor (point 4), but h index seemed useful (in point 2 the h-index is discussed).

Assessing the impact of quantum cryptanalysis

I regardless believe that outside (and arguably within) quantum cryptanalysis the applications will be fairly limited.

I might be confused, but did we agree that the most useful application of quantum computing would be on chemistry and material science? I thought so, but the above sentence seems to say otherwise...

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