Schedule of talks and events held from 9-10am PT each Friday this quarter

• 4/1/22: Ece Kamar, a Partner Research Area Manager at Microsoft Research Redmond, will present the talk: “In the Pursuit of Responsible AI: Developing AI Systems for People with People.” See flyer.
• 4/8/22: Subho Majumdar, a Senior Applied Scientist at Splunk, will present the talk: “An Applied Research Perspective on Algorithmic Fairness.” See flyer.
• 4/15 Ethan Zuckerman, Director of the Initiative for Digital Public Infrastructure at the University of Massachusetts Amherst, will present the talk: “AI Limits, Fixability and Refusal.” See flyer.
• 4/22: Anjalie Field, a PhD candidate at the Language Technologies Institute at Carnegie Mellon University, and a visiting student at the University of Washington. See flyer.
• 4/29: Hamed Zamani, Assistant Professor at the University of Massachusetts Amherst and Associate Director of the Center for Intelligent Information Retrieval, presenting the talk: “Towards Mixed-Initiative Conversational Information Seeking.” See flyer.
• 5/6: Olfa Nasraoui, Professor of Computer Engineering and Computer Science, Endowed Chair of E-commerce and the founding director of the Knowledge Discovery & Web Mining Lab at University of Louisville, presenting the talk: “Explainability by Design.” See flyer. 
• 5/13: John Dickerson, Assistant Professor in the Department of Computer Science at the University of Maryland, and Chief Scientist at ArthurAI, presenting the talk: “Designing Efficient, Fair, & Robust Platform Markets: Case Studies in Worldwide Blood Donation and Organ Exchange.” See flyer.

   

• 5/20: Saleema Amershi, Senior Principal Research Manager, Microsoft Research, presenting the talk, “Challenges in Creating Responsible and Human-Centered AI.” See flyer.
• 5/27: Student Research Highlights, with talks by Bin Han, Trischa Schramm, Yiwei Yang, and Sahil Verma. See flyer.  

Schedule of talks and events held from 9-10am PT each Friday this quarter

Zoom link: https://washington.zoom.us/j/94636255672

• 1/7/22: Kick-off meeting for winter quarter seminar series.
• 1/14/22: Batya Friedman and David Hendry will present: “Value Sensitive Design, in Brief”. See flyer and the Value Sensitive Design Lab website: https://vsdesign.org.
• 1/21/22: Sandhya Saisubramanian, Assistant Professor in the School of Electrical Engineering and Computer Science (EECS) at Oregon State University, will present: “AI in the Open World: Leveraging Human Guidance to Mitigate Undesirable Effects of Incomplete Specification.” See flyer.
• 1/28/22: Dr. Ramya Srinivasan, an AI researcher in Fujitsu Research of America, will present: “Biases in Generative Art.” See flyer
• 2/4/22: A showcase of student work, with presentations by Anjali Bhavan, Ruoxi Shang and Sahil Verma. See flyer.
• 2/11/22: A showcase of student work, with presentations by Shruti Phadke, Bingbing Wen and Bernease Herman. See flyer.
• 2/18/22: RAISE will hold a Faculty Highlights event from 9-10am PT Friday February 18. Emily M. Bender, Afra Mashhadi, Yulia Tsvetkov, Leilani Battle, and Dingwen Tao will speak about their work and research. Learn about the speakers here. See flyer. 
• 2/25/22: Casey Fiesler, Assistant Professor in the Department of Information Science at University of Colorado Boulder. See flyer.
• 3/4/22:  Ashique KhudaBukhsh, assistant professor at the Golisano College of Computing and Information Sciences, Rochester Institute of Technology. See flyer.
• 3/11/22: Zeerak Talat, a post doctoral fellow at the Digital Democracies Institute at Simon Fraser University, presenting the talk: “Paving the Road to Hell with Machine Learning: On Ethics, Bias, and Machine Learning.” See flyer.

• 10/8/21: Overview of Responsible AI / Trustworthy ML presented by Sahil Verma, Ph.D. Student in Computer Science and Engineering at at the University of Washington. Slides available here.
• 10/15/21: Emily M. Bender, Professor of Linguistics, and Chirag Shah, Associate Professor in the Information School at the University of Washington will share ideas on search engines and language models.
• 10/22/21: Liz O’ Sullivan, CEO of the newly formed Responsible AI startup Parity. See flyer.
• 10/29/21: Keegan Hines, Vice President of ML at ArthurAI. See flyer.
• 11/5/21: Group discussion on responsible AI with Microsoft Research. See flyer.
• 11/12/21: Mona Diab, Research Scientist at Facebook AI Research; Professor of CS at the George Washington University. See flyer.
• 11/19/21: Yunhe Feng, Postdoctoral Scholar, UW Information School. See flyer.
• 12/3/21: Kush R. Varshney, Distinguished Research Staff Member and Manager at IBM Research, and a member of the AI Fairness 360 research team. See flyer.

The following papers were discussed in the seminar. Student reflections are published here.

• 4/16/21: Questioning the AI: Informing Design Practices for Explainable AI User Experiences, Q. Vera Liao, Daniel Gruen, and Sarah Miller. CHI 20.
• 4/23/21: Roles for computing in social change,  Rediet Abebe, Solon Barocas, Jon Kleinberg, Karen Levy, Manish Raghavan, David G. Robinson. FaCCT, 20.
• 4/30/21: Measurement and Fairness, Abigail Z. Jacobs, Hanna Wallach.  FAccT 21.
• 5/7/21: On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? . Bender, Emily M., Timnit Gebru, Angelina McMillan-Major, and Shmargaret Shmitchell. FAccT 2021.
• 5/14/21: Towards Fair and Privacy-Preserving Federated Deep Models, Lingjuan Lyu, Jiangshan Yu, Karthik Nandakumar, Yitong Li, Xingjun Ma, Jiong Jin, Han Yu, Kee Siong Ng, TPDS 2019.
• 5/21/21: Fair Clustering via Equitable Group Representations, Mohsen Abbasi, Aditya Bhaskara, Suresh Venkatasubramanian. FAccT 21.
• 5/28/21: Manipulating and Measuring Model Interpretability, Forough Poursabzi-Sangdeh, Daniel G. Goldstein, Jake M. Hofman, Jennifer Wortman Vaughan, Hanna Wallach. CHI 21.
• 6/4/21: The Sanction of Authority: Promoting Public Trust in AI, Bran Knowles, John T. Richards. FAccT 21.

• Prerna Juneja and Tanushree Mitra. Auditing E-Commerce Platforms for Algorithmically Curated Vaccine Misinformation. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems (CHI ’21). Association for Computing Machinery. Best Paper Honorable Mention.

• Chirag Shah, Theresa Anderson, Loni Hagen, Yin Zhang. An iSchool approach to data science: Human‐centered, socially responsible, and context‐driven. Journal of the Association for Information Science and Technology (JASIST). 2021.

• Nicholas Vincent, Hanlin Li, Nicole Tilly, Stevie Chancellor, and Brent Hecht.  Data Leverage: A Framework for Empowering the Public in its Relationship with Technology Companies. In Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency (FAccT ’21). Association for Computing Machinery, New York, NY, USA, 215–227.

• Jessica Hullman. Why Authors Don’t Visualize Uncertainty. Published in: IEEE Transactions on Visualization and Computer Graphics (Volume: 26, Issue: 1, Jan. 2020).

• Deven Santosh Shah, H. Andrew Schwartz, Dirk Hovy. Predictive Biases in Natural Language Processing Models: A Conceptual Framework and Overview. Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. 2020.

• Allison Koenecke, Andrew Nam, Emily Lake, Joe Nudell, Minnie Quartey, Zion Mengesha, Connor Toups, John R. Rickford, Dan Jurafsky, Shard Goel. Racial disparities in automated speech recognition. Proceedings of the National Academy of Sciences Apr 2020, 117 (14) 7684-7689.

• Nathan Ensmenger. The Environmental History of Computing.”Technology and Culture, vol. 59 no. 4, 2018, p. S7-S33. Project MUSE.

• Andrew Hard, Kanishka Rao, Rajiv Mathews, Swaroop Ramaswamy, Françoise Beaufays, Sean Augenstein, Hubert Eichner, Chloé Kiddon, Daniel Ramage. Federated Learning for Mobile Keyboard Prediction. 2018. ArXiv, abs/1811.03604.

• Hirsch, T., Merced, K., Narayanan, S., Imel, Z. E., & Atkins, D. C. Designing Contestability: Interaction Design, Machine Learning, and Mental Health. DIS. Designing Interactive Systems (Conference), 2017, 95–99.

• Peter J. Denning. Is computer science science? Commun. ACM 48, 4 (April 2005), 27–31

   

• The Google People + AI Research (PAIR) team has created a Guidebook, and the What-If Tool, available as an extension in Jupyter, Colaboratory, and Cloud AI Platform notebooks.

• The TensorFlow Playground allows for experimentation with a neural network.

• The Mechanism Design for Social Good (MD4SG) is a multi-institutional initiative working to improve access to opportunity using algorithms, optimization and mechanism design.

• The Human-Centered AI website contains a collection of resources.

• ACM CHI Workshop on Operationalizing Human-Centered Perspectives in Explainable AI.