[Career review] “Machine Learning PhDs” by Richard Batty

We explain why it’s a high-impact area, how to work out if it’s for you, and exactly how and where to apply.

Narrated by AI.

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Outline:

(00:09) AI is improving rapidly. Here's how to learn the technology that's driving it.

(01:57) Summary

(02:27) Pros

(02:45) Cons

(03:03) Key facts on fit

(03:15) Next steps

(03:38) Recommended

(03:47) Review status

(03:52) What this profile is based on

(04:21) What is this career path?

(05:56) What does the work involve? What is it like day-to-day?

(07:01) If you want to have a positive impact, why do a machine learning PhD?

(07:07) 1. Learn about perhaps the most important technology of the next decade

(09:08) 2. Work on positively shaping the development of artificial intelligence

(09:41) Technical safety research

(10:07) Policy and strategy research

(10:38) Want to work on positively shaping the development of AI? We want to help.

(10:56) 3. Apply machine learning to other socially important problems

(12:22) 4. High-earning back-up options

(14:20) 5. Intellectually interesting work with a lot of autonomy

(14:37) Downsides

(14:40) 1. Tough for mental health

(15:13) 2. Takes a long time

(15:44) 3. Machine learning may become a lot more competitive

(16:17) How do you get in?

(17:40) How to show you can do good research

(20:41) How to work out whether the PhD would be right for you

(21:05) How to test your fit

(22:20) Should I do something else instead?

(24:16) Options similar to a machine learning PhD

(24:49) How to choose your programme

(24:53) Which research group and institution?

(28:23) Which topic?

(28:31) Deep learning

(29:23) Reinforcement learning

(30:11) Applications

(30:49) Get industry experience during your PhD

(31:50) How to get machine learning experience while doing a non-machine learning PhD

(32:23) Learn more

(32:26) Top recommendations

(32:47) Further recommendations

(34:04) Want to use an ML PhD to make the world a better place? We want to help.

The original text contained 22 footnotes which were omitted from this narration.

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First published:
June 19th, 2017

Source:
https://80000hours.org/career-reviews/machine-learning-phd

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Narrated by TYPE III AUDIO.