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Eduard Talamàs works on Organizational Economics, Bargaining, and Networks. He joined IESE Business School as an Assistant Professor of Economics in 2019. He obtained his Ph.D. in economics at Harvard University under the supervision of Benjamin Golub. Before joining IESE, he was a Warren Center postdoctoral fellow at the University of Pennsylvania, hosted by Rakesh Vohra. In the Autumn of 2020, Eduard was a Research Associate in The Cambridge Institute of New Economic Thinking, hosted by Matthew Elliott.
Abstract
Artificial Intelligence (AI) can transform the knowledge economy by automating non-codifiable work. To analyze this transformation, we incorporate AI into an economy where humans form hierarchical organizations: Less knowledgeable individuals become “workers” doing routine work, while others become “solvers” handling exceptions. We model AI as a technology that converts computational resources into “AI agents” that operate autonomously (as co-workers and solvers/co-pilots) or non-autonomously (solely as co-pilots). Autonomous AI primarily benefits the most knowledgeable individuals; non-autonomous AI benefits the least knowledgeable. However, output is higher with autonomous AI. These findings reconcile contradictory empirical evidence and reveal tradeoffs when regulating AI autonomy.
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