Session Description: This session explores how AI and algorithmic systems shape our data-driven world. We'll analyze case studies highlighting key issues like amplified systemic bias and privacy erosion. Our discussion will cover various research approaches that can be taken to study these systems, emphasizing methods that reveal the real-world impact of these technologies. We'll examine not just the systems themselves, but also their deployment contexts, the motivations of institutions creating them, and potential risks to marginalized communities.

Speaker: Surya Mattu, Lead, Digital Witness Lab, CITP

Series Overview: GradFUTURES is pleased to offer Responsible AI learning cohort in Fall 2024 in partnership with Center for Information Technology Policy (CITP) and Princeton University Press (PUP). Led by graduate students, this learning cohort leverages expertise of Princeton’s faculty, graduate students, staff and alumni, and external partners. The cohort will discuss and examine realities of Responsible AI principles: fairness, inclusiveness, transparency, reliability and safety, privacy and security, and accountability in diverse fields through guest speakers, case studies and immersive capstone. Upon successful completion of learning cohort, graduate students will receive a co-curricular certificate of completion and a micro-credential badge.

Responsible AI dimensions. We will follow the definition and dimensions of Responsible AI as outlined by Microsoft. "Responsible AI is an approach to developing, assessing, and deploying AI systems in a safe, trustworthy, and ethical way. It's a framework for building AI systems according to six principles: fairness, reliability and safety, privacy and security, inclusiveness, transparency, and accountability."