Mainak Mazumdar

Mainak Mazumdar, a data scientist, delves into the hidden perils of biased data in AI. He illustrates how flawed data from places like Shanghai and New York leads to poor decisions in job and loan allocations. Mazumdar emphasizes the undercounting of minority communities in the 2010 census, showing its dire impact on AI models. He advocates for enhanced data quality and inclusivity to ensure that AI serves everyone fairly. His insights call for a fundamental shift in how we approach data collection to build ethical AI systems.