A Nobel Laureate on the Limits of Evidence-Based Policy
Lars Peter Hansen and Kevin M. Murphy discuss how data can inform policymaking.
A Nobel Laureate on the Limits of Evidence-Based PolicyEdmon de Haro
Rapid improvements in artificial intelligence, especially generative A.I. such as ChatGPT, have given rise to concerns about the broad set of jobs that could be fully or partially automated in the foreseeable future. Will the technology lead to widespread displacement of white-collar workers and fewer opportunities for the highly educated? Could it lead to the aggravation of existing issues with income inequality? Chicago Booth’s Kent A. Clark Center for Global Markets turned to its US and European panels of economic experts for insights.
Antoinette Schoar, MIT
“I believe the impact will be highly heterogeneous and it depends on where you set the cut off for ‘high skilled.’”
Response: Uncertain
Christopher Udry, Northwestern
“A negative impact on some specialties; positive on others. This is a disruptive technology.”
Response: Agree
Judith Chevalier, Yale
“I imagine that specialized educational programs for particular professions could have more uncertain returns.”
Response: Agree
Christian Leuz, Chicago Booth
“In the near term, this is likely correct, but it’s not clear in the long run. Education and required knowledge will adapt, and uncertainty over returns to education will likely subside.”
Response: Agree
Daron Acemoglu, MIT
“While it is possible for generative A.I. to be a useful tool for noncollege workers, I do not see the current path achieving this, and the existing evidence is more consistent with most of the burden of displacement falling on less-educated, lower-wage workers.”
Response: Agree
Kjetil Storesletten, University of Minnesota
“A.I. cuts both ways for inequality. The college premium might fall on average, but inequality will increase among high-skilled individuals.”
Response: Uncertain
Lars Peter Hansen and Kevin M. Murphy discuss how data can inform policymaking.
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