Reid Concert Hall, Bristo Square, Edinburgh EH8 9AL

Over the last decade, a range of practices have emerged as scholars, practitioners, and regulators attempt to ensure that AI investments don’t go off the rails. Practices like red-teaming marry earlier approaches to content moderation and security, but others are being developed specifically for the Generative AI space. Many of these fit under the broader rubric of “responsible AI.” How sociotechnical systems are designed, developed, and deployed is not inevitable. It behooves us all to grapple with known pitfalls, minimize risks, and nudge the systems towards constructive ends. In this talk, danah will explore the range of traps that those seeking to minimize harm have, are, and will face as they attempt to ground fast-moving developments and offer frameworks for thinking about the present moment.

In this talk, danah boyd will discuss the ways risks and harms are being addressed in AI development. She’ll explore the range of traps that those seeking to minimize harm have, are, and will face as they attempt to ground fast-moving AI developments and offer frameworks for thinking about the present moment.

Bio

danah boyd is a Partner Researcher at Microsoft Research and a Distinguished Visiting Professor at Georgetown University. Her research focuses on the intersection of technology and society, with an eye to how structural inequities shape and are shaped by technologies. She is currently conducting a multi-year ethnographic study of the US census to understand how data are made legitimate. Her previous studies have focused on media manipulation, algorithmic bias, privacy practices, social media, and teen culture. Her monograph “It’s Complicated: The Social Lives of Networked Teens” has received widespread praise. She founded the research institute Data & Society, where she currently serves as an advisor. She is also a trustee of the Computer History Museum, a member of the Council on Foreign Relations, and on the advisory board of Electronic Privacy Information Center. She received a bachelor’s degree in computer science from Brown University, a master’s degree from the MIT Media Lab, and a Ph.D in Information from the University of California, Berkeley.

Hosted by the Critical Data Studies Cluster, with the Bridging AI Divides (BRAID) programme