What Is Your Data Worth? Quantifying the Value of Data in Machine Learning - Livestream

As data becomes the fuel driving technological and economic growth, a fundamental challenge is how to quantify the value of data in algorithmic predictions and decisions. For example, CA Gov. Newsom recently proposed "data dividend" whereby consumers are compensated by companies for the data that they generate. In this talk we will present a principled framework to quantify the value of different data in machine learning. Beyond regulatory implications, we will discuss applications to denoising, active learning, and domain adaption on large biomedical datasets. I will conclude by discussing how data valuation contributes to a broader framework of accountable AI.

Speaker: James Zou, Stanford Univ.

Editor's Note: Keren Haroush, originally scheduled for this date, will not be speaking.  Instead this talk will be given.

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