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Joshua Gans, a professor at the University of Toronto and co-author of "Power and Prediction: The Disruptive Economics of Artificial Intelligence," joins Kevin Frazier, the AI Innovation and Law Fellow at the University of Texas School of Law and a Senior Editor at Lawfare, to evaluate ongoing concerns about AI-induced job displacement, the likely consequences of various regulatory proposals on AI innovation, and how AI tools are already changing higher education.
Select works by Gans include:
A Quest for AI Knowledge (https://www.nber.org/papers/w33566)
Regulating the Direction of Innovation (https://www.nber.org/papers/w32741)
How Learning About Harms Impacts the Optimal Rate of Artificial Intelligence Adoption (https://www.nber.org/papers/w32105)
Hosted on Acast. See acast.com/privacy for more information.
By Lawfare & University of Texas Law School4.6
2323 ratings
Joshua Gans, a professor at the University of Toronto and co-author of "Power and Prediction: The Disruptive Economics of Artificial Intelligence," joins Kevin Frazier, the AI Innovation and Law Fellow at the University of Texas School of Law and a Senior Editor at Lawfare, to evaluate ongoing concerns about AI-induced job displacement, the likely consequences of various regulatory proposals on AI innovation, and how AI tools are already changing higher education.
Select works by Gans include:
A Quest for AI Knowledge (https://www.nber.org/papers/w33566)
Regulating the Direction of Innovation (https://www.nber.org/papers/w32741)
How Learning About Harms Impacts the Optimal Rate of Artificial Intelligence Adoption (https://www.nber.org/papers/w32105)
Hosted on Acast. See acast.com/privacy for more information.

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