What is the optimal investment in quantitative skills?

As I plan out my summer plans I am debating how to allocate my time in skill investment. The general advice I have gotten is to increase my quantitative skills and pick up as much about coding as possible. However I am skeptical that I really should invest too much in quantitative skills. There are diminishing returns for starters.

More importantly though artificial intelligence/computing is increasing every day. When my older professors were trained they had to use IBM punch cards to run simple regressions. Today my phone has several times more the computing power, not to mention my PC. I would not be surprised if performing quantitative analysis is taken over entirely by AI within a decade or two. Even if it isn’t, it will surely be easier and require minimal knowledge of what is happening. In which case I should invest more heavily in skills that cannot be done by AI.

I am thinking, for example, of research design or substantive knowledge of research areas. AI can beat humans in chess, but I can’t think of any who have written a half decent history text.

Mind you I cannot abandon learning a base level of quantitative knowledge. AI may take over in the nex decade, but I will be on the job market and seeking tenure before then (hopefully!). 

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One thought on “What is the optimal investment in quantitative skills?

  1. I think you’re on the right track. Personally, I think the AI revolution will take longer than you think but you need the knowledge not necessarily as a doer but as a consumer. Even if the number crunching is done by software you need to understand what’s being done and what it means. The same holds for qualitative work; you need good grasp of how it’s properly done to be able to evaluate evidence presented by a researcher.

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