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Integrating Behavioral Economics and Machine Learning
February 5, 2024 @ 4:00 pm - 5:00 pm
Sendhil Mullainathan (University of Chicago)
There are synergies to be had between machine learning algorithms and behavioral economics. In one direction, many algorithms today rely on human-generated data. As such, the insights from behavioral economics, by clarifying what those data mean and do not mean, can improve algorithm design; if we are able to formalize those insights in a computational useful way. In the other direction, the same algorithms may notice patterns on these data that go against our existing models. As such, the tools of machine learning may improve our behavioral models – if we are able to extract theoretical insights from them. I will discuss projects that operate in both directions.