Accepted to 2020 NBER conference on Economics of AI PhD workshop

I attended the 2020 NBER conference on Economics of AI and its graduate student workshop.

The current strands of work in economics of AI can be summarized in a few directions: 1) Understanding AI as a general purpose technology and a form of “new capital”. What are the implications on productivity and growth? 2) Subsequently how is automation going to impact the future of work? 3) Subsequently given rise of tech giants/algorithm collusion, what are the implications in industrial organization and antitrust regulations? 4) How does AI influence decision-making? (theoretical/empirical evaluation, some methodological innovation here for empirical evaluation as it requires causal inference) 5) misc innovative implementations of ML particularly causal ML in policy evaluation.

There are definitely mutually benefitial research opportunities in the (4) research direction on decision-making between econ and human computer interactions. (5) causal ML is unsurprisingly yet criticaly important in econ/policy evaluation, although the reliance on counterfactual notions need to be carefully supplemented with behavior evidence.

I met many famous economists. As you can see, I’m still new here…