Bias in, Bias out: Nutrition Labels for Datasets – Kasia Chmielinski
Kasia Chmielinski will discuss their research initiative at The Data Nutrition Project and “nutrition labels” for datasets.
Kasia Chmielinski will discuss their research initiative at The Data Nutrition Project and explain the importance of “nutrition labels” for datasets on AI algorithms.
Kasia Chmielinski (they/them) is the Co-Founder and Project Lead of The Data Nutrition Project, an initiative that builds dataset quality standards and tools to mitigate bias in artificial intelligence, a technologist at McKinsey & Company, and an Affiliate at The Berkman Klein Center at Harvard University. Previously, Kasia was a digital expert at the U.S. Digital Service (Executive Office of the President) and product lead of Scratch, a project of the MIT Media Lab. When not in front of a whiteboard or a keyboard, Kasia can be found leading a Feminist Birdwatching event or cycling uncomfortably-long distances. They received their bachelor’s degree in physics from Harvard University.
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