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‘Off Label’ Use of Imaging Databases Could Lead to Bias in AI Algorithms

The findings, published this week in the Proceedings of the National Academy of Sciences, highlight the problems that arise when data published for one task are used to train algorithms for a different one. Jonathan Tamir, assistant professor of electrical and computer engineering in the Cockrell School of Engineering and a member of the UT-led National Science Foundation AI Institute for the Foundations of Machine Learning, is one of the study’s co-authors.
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