Toward Effective Data Governance in Data-Driven Systems
Presented by Asia
Asia’s research focuses on data-driven systems at the intersection of computing and society. She collaborates with experts across disciplines and has advised the European Commission on tech policy. With experience at Microsoft and Google, her work has earned awards like the Rodota Award and recognition among the “100 Brilliant Women in AI Ethics.”
Abstract
Contemporary AI systems are characterized by extensive personal data collection despite the increasing societal costs associated with such practices. To prevent harm, data protection regulations specify various principles for respectfully processing user data, such as purpose limitation, data minimization, or the need to establish a valid basis for data processing, such as consent or legitimate interest. Yet, practical implementations of these principles in data-driven systems leave much to be desired. This talk will delve into the computational and human factors contributing to lax data protection implementations and uncover ways research can contribute to improved data governance online.