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
Mitchell designs models, interactive systems, and evaluation approaches that bridge principles of human-computer interaction with the realities of machine learning. His work earned top AI and HCI awards, including a Best Paper at CHI and an Oral at NeurIPS. He holds a PhD in computer science from Stanford.
Abstract
Whose voices should AI learn to emulate? In tasks from toxicity detection to medical treatment, societal groups often disagree on what constitutes ground truth. This talk introduces Jury Learning, an interactive AI architecture that lets developers define whose perspectives shape a model’s decisions. It also presents The Disagreement Deconvolution, a metric transformation revealing how current evaluations overstate AI performance in user-facing tasks. Together, these components form a new framework for encoding human goals and values into AI, bridging HCI principles with machine learning realities.
Event Time Event Name
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Feb 07, 2025 RAISE Seminar ft. Mitchell Gordon
9AM-10AM PST Assistant Professor, MIT EECS/CSAIL
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Feb 14, 2025 RAISE Seminar ft. Diyi Yang
9AM-10AM PST Assistant Professor, Stanford CS
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Feb 21, 2025 RAISE Seminar ft. Asia Biega
9AM-10AM PST Tenure-Track Faculty Member, Max Planck Institute for Security and Privacy (MPI-SP)
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Feb 28, 2025 RAISE Poster / Unconference Event
9AM-1PM PST More details TBA
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Mar 07, 2025 RAISE Seminar ft. Ranjay Krishna
9AM-10AM PST Assistant Professor, UW CSE
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Mar 14, 2025 RAISE Seminar ft. Hari Subramonyam
9AM-10AM PST Assistant Professor, Graduate School of Education, Stanford
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