RENCONTRE SANTÉ NUMÉRIQUE 5 octobre @12h
Présentée par John P. Dickerson, professeur adjoint d'informatique à l'Université du Maryland, Co-fondateur et scientifique d'Arthur AI, société de surveillance de modèles IA/ML axée sur l'entreprise
Titre : Stratégies pour créer des marchés d'appariement robuste : une étude de cas sur l'échange d'organes.
Les Rencontres Santé Numérique sont organisées par le Consortium Santé Numérique de l'UdeM.
Résumé de la conférence :
Markets are systems that empower interested parties — humans, firms, governments, or autonomous agents — to exchange goods, services, and information. In some markets, such as stock and commodity exchanges, prices do all of the “work” of matching supply and demand. Due to logistical or societal constraints, many markets, e.g., school choice, rideshare, online dating, advertising, cadaveric organ allocation, online labor, public housing, refugee placement, and kidney exchange, cannot rely solely on prices to match supply and demand. Techniques from artificial intelligence (AI), computer science, and mathematics have a long history of both being created via, and also finding application in, the design and analysis of markets of both types. AI techniques determine how to discover structure in an uncertain matching problem, learn how to decide between matching now versus waiting, and balance competing objectives such as fairness, diversity, and economic efficiency.
This talk covers optimization- and AI-based approaches to the design and analysis of markets. It focuses on managing uncertainty — specifically, on optimizing costly information gathering done before a clearing algorithm is run, and then incorporating that uncertainty into the algorithm(s) at clearing time. Techniques will be presented through the lens of kidney exchange, an organized market where patients with end-stage renal failure swap willing but incompatible donors. These markets are currently fielded nationally and internationally and are run (to varying degrees) by AI-based systems, thus surfacing pertinent questions at the intersection of ethics and artificial intelligence.
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