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Abstract: Modern AI systems are capable of generating synthetic representations of complex entities—from personalities to creative works—that can increasingly serve as plausible substitutes for the objects themselves. This talk examines the economic and regulatory implications of this shift via two papers. The first, “Artificial Intelligence Clones,” analyzes search and matching when people are represented by AI “clones” rather than evaluated in person—for example, when an automated recruiter interviews AI clones of job candidates. AI representations greatly expand search capacity but introduce…
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Abstract: The emergence of large language models has prompted a surge of interest into theoretical models that might give us insight into both their successes and their shortcomings. We'll give an overview of recent work in this direction, focusing on a surprising line of positive results that shows it is possible to give guarantees for language-generation algorithms even in the absence of any probabilistic assumptions, in a framework known as "language generation in the limit". These results suggest interesting notions…