Michael I. Jordan studies electrical engineering and machine learning at UC Berkeley. He has expressed frustration with the current state of AI discourse – namely, the focus on “AGI” (artificial general intelligence) and the obsession with creating individually conscious entities that mimic human behavior and might ultimately surpass us. Instead, MIJ wants to build tools of engineering and economic theory to enhance human society using machine learning. Some examples of these applications include: counting and classifying galaxies, biology research, and creating better business models for artists to profit from their work. He’s on the board of the music distribution platform UnitedMasters: https://unitedmasters.com/

Check out some of his scholarly work below:

“Principled Reinforcement Learning with Human Feedback”:

“Incentive-Aware Recommender Systems in Two-Sided Markets”:

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Starring JT Parr
Created by JT Parr & Pedro Salinas
Directed by Pedro Salinas
Edited by Trevor Ames
Produced by Jake Rohret