Responsibility in AI Systems & Experiences
At RAISE, we envision a future where AI systems are developed and used strongly aligned with human ethics and values. These systems will solve complex problems and help make decisions. They will provide experiences for the users that not only augment and enhance their live, but do so with accountability.
With a wealth of faculty from over a dozen labs across disciplines, RAISE is a leading center for research and education: building, evaluating, and envisioning AI technologies in the area of Responsible AI. Together, we are working to address humanity’s existential challenges such as climate change, access to food, water, and healthcare, as well as reliable and trustworthy information and political landscape, to support an equitable, sustainable, and healthy world.
Upcoming Talks & Events
Guest Speaker
Arvind Narayanan is a co-author of the book AI Snake Oil and a newsletter of the same name which is read by 50,000 researchers, policy makers, journalists, and AI enthusiasts. He previously co-authored two widely used computer science textbooks: Bitcoin and Cryptocurrency Technologies and Fairness in Machine Learning. Narayanan led the Princeton Web Transparency and Accountability Project to uncover how companies collect and use our personal information. His work was among the first to show how machine learning reflects cultural stereotypes. Narayanan was one of TIME’s inaugural list of 100 most influential people in AI.
Abstract
Arvind Narayanan will present a new paper co-authored with Sayash Kapoo, in which they articulate a vision of artificial intelligence as a “normal technology,” standing in contrast to both utopian and dystopian narratives that portray AI as a potentially superintelligent entity.
In the presentation, Narayanan will explain why they believe the impacts of advanced AI, even if transformative, are likely to unfold gradually. He will make a critical distinction between AI methods, AI applications, and AI adoption. Additionally, he will explore a potential division of labor between humans and AI in a world shaped by advanced AI, and examine the implications of treating AI as normal technology for AI policy, AI safety, and broader human progress.
Guest Speaker
Gagan is part of the AI Frontiers group and co-leads research on AutoGen, a framework for building multi-agent AI systems. His work lies at the intersection of Artificial Intelligence and Human-Computer Interaction, with a focus on making AI systems more capable, interactive, and useful to people. Before joining Microsoft Research in 2022, Gagan completed his Ph.D. in Computer Science at the University of Washington, advised by Dan Weld. At UW, he was part of the Lab for Human-AI Interaction, where he studied how AI systems can complement human decision-making.
At Microsoft, Gagan has been a driving force behind several open-source agentic projects, including:
– AutoGen, a widely adopted framework for multi-agent applications
– AutoGen Studio, a low-code interface for creating agentic workflows
– Magentic-One, a state-of-the-art multi-agent team for solving complex tasks
– MarkitDown, a tool for converting large sets of files to markdown for LLMs
Abstract
Reflecting on his experience developing AutoGen—an open-source framework for building agents and AutoGen-based applications—this talk outlines three concrete challenges in creating human-centered agents: (1) reliably completing complex, multi-step tasks; (2) maintaining common ground between people and agents; and (3) auditing complex agent behaviors. Bansal will share demos and evaluations highlighting his progress on these challenges, as well as open opportunities for the HCI community.
Publications
ModelsCounterfactual Explanations and Algorithmic Recourses for Machine Learning: A Review
In ACM Computing Surveys, Volume 56, Issue 12 Article, No.: 312, Pages 1 – 42.
Sahil Verma, Varich Boonsanong, Minh Hoang, Keegan Hines, John Dickerson, Chirag Shah. 2024
Addressing Weak Decision Boundaries in Image Classification by Leveraging Web Search and Generative Models
In Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, August 2023. International Joint Conferences on Artificial Intelligence Organization, Macau, SAR China, 5941–5949.
Tal August, Lucy Lu Wang, Jonathan Bragg, Marti A. Hearst, Andrew Head, and Kyle Lo. 2023
Human and Technological Infrastructures of Fact-checking
In Proc. ACM Hum.-Comput. Interact. 6, CSCW2 (November 2022), 1–36.
Prerna Juneja and Tanushree Mitra
Partnerships
UW eScience Institute
UW Data Lab
Information Matters
InfoSeeking
Meet Our Executive Committee
Chirag Shah
Co-Founding Director
Chirag Shah is a Professor in the Information School. He is the Founding Director of InfoSeeking Lab, which focuses on issues related to information seeking, human-computer interaction (HCI), and social media.
Email: chirags@uw.edu
Bill Howe
Co-Founding Director
Bill Howe is an Associate Professor in the iSchool, Adjunct Associate Professor in Computer Science & Engineering, Founding Associate Director of the eScience institute and remains a Senior Data Science Fellow.
Email: billhowe@uw.edu
Tanu Mitra
Co-Founding Director
Tanu Mitra is an Assistant Professor at the Information School, where she leads the Social Computing research group. Her research focuses on studying and building large-scale social computing systems to understand and counter problematic information online.
Email: tmitra@uw.edu