Episode Topic: Machine Learning and Power

Machine learning purports to make accurate predictions and decisions about everything from prison recidivism rates to cancer diagnoses to mortgage approvals. But time and time again, scholars, activists, and journalists have demonstrated that machine learning algorithms often digitize and replicate inaccuracies, historical prejudices, and institutional harms. With so much on the line, machine learning models and the data used to train them may deserve more scrutiny.

Featured Speakers: 

• Abeba Birhane, PhD Candidate in Cognitive Science, University College Dublin
• Noopur Raval, Postdoctoral Researcher, AI Now Institute

Read this episode's recap over on the University of Notre Dame's open online learning community platform, ThinkND: go.nd.edu/b85c59. 

This podcast is a part of the TEC Talks ThinkND Series titled “Technology & Power”.

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