Dr. Sauvik Das, Carnegie Mellon University
Privacy is a core tenet for engineering ethical AI products, but what barriers do practitioners face in their privacy work for AI products and services? Without an answer to that question, we cannot hope to better support practitioners in engineering privacy-respecting AI. Through interviews with 35 practitioners who have developed AI products, we show how practitioners often have little awareness of the ways in which AI can create new or exacerbating existing privacy threats, face significant motivational barriers in their privacy work, and have little support for AI-specific privacy work. Many of these barriers are due to rigid privacy work practices, incentive structures, educational resources, and tools that have not been adequately updated to factor in how the capabilities and requirements of AI technologies can change scope of privacy threats. I will conclude with recommendations for how to better support practitioners in their AI privacy work.
Dr. Sauvik Das, Carnegie Mellon University
Dr. Sauvik Das is an Assistant Professor at the Human-Computer Interaction Institute at Carnegie Mellon University where he directs the SPUD (Security, Privacy, Usability and Design) Lab. His work, at the intersection of HCI, AI and cybersecurity, is oriented around answering the question: How can we design systems that empower people with improved agency over their personal data and experiences online? His work has recognized with eight paper awards, and he has been PI on over $2.5 million worth of funded grant proposals, including a NSF CAREER. Dr. Das has also worked as a research intern or consultant at several companies, including Google, Facebook, Twitter, and Microsoft. Dr. Das received his Ph.D. in Human-Computer Interaction from Carnegie Mellon University in 2017, following a B.S. in Computer Science at Georgia Tech.
author = {Dr. Sauvik Das},
title = {How Does {AI} Change Privacy? Towards Helping Practitioners Scope, Motivate, and Conduct Privacy Work for {AI} Products and Services},
year = {2023},
address = {Santa Clara, CA},
publisher = {USENIX Association},
month = sep
}