SherkanerUnderhill comments on To contribute to AI safety, consider doing AI research - Less Wrong

26 Post author: Vika 16 January 2016 08:42PM

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Comment author: SherkanerUnderhill 29 January 2016 02:00:34AM *  3 points [-]

Hi Victoria,

I am highly interested in AI safety research. Unfortunately, I do not have a strong math background and I live in an area distant from AI research. After spending some time thinking about my future I have come to the decision to go for a math intensive PhD in some area not far from MIRI or FLI. I have only the bachelor degree in Engineering with major in Computer Science and Software Engineering. Currently, I spend most of my time working full time as a software developer, preparing for a GRE general exam and thinking about PhD and FAI.

Andrew Critch from MIRI and Berkeley is very enthusiastic about pursuing the PhD. He suggested the Statistics. I would be glad to know your opinions about PhD/AI & FAI research. Here is a list of some questions, which are bothering me.

  • What do you think would be more relevant for AI safety research - CS, Statistics or something else?
  • What areas of research are the most promising for AI safety, in your opinion?
  • Is it better to pick the research area close to what MIRI working on, or a more general AI research one (such as a ML).
  • Is it possible to increase the chances of successful admission by gaining some research experience before the admissions in this year? Or is it better to spend the time in some other way?
  • Does the Math GRE subject test increase the chance of admission?
Comment author: Vika 30 January 2016 08:24:40PM *  3 points [-]

I would recommend doing a CS PhD and take statistics courses, rather than doing a statistics PhD.

For examples of promising research areas, I recommend taking a look at the work of FLI grantees. I'm personally working on the interpretability of neural nets, which seems important if they become a component of advanced AI. There's not that much overlap between MIRI's work and mainstream CS, so I'd recommend a more broad focus.

Research experience is always helpful, though it's harder to get if you are working full time in industry. If your company has any machine learning research projects, you could try to get involved in those. Taking machine learning / stats courses and doing well in them is also helpful for admission. Math GRE subject test probably helps (not sure how much) if you have a really good score.

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