University of Michigan School of Information
FAcct 2024 and ICWSM: UMSI Research Roundup
Monday, 06/03/2024
The ACM FAccT conference (Rio de Janeiro, Brazil) and the 18th International AAAI Conference on Web and Social Media (Buffalo, New York) will be held from June 3rd to June 6th. Several University of Michigan School of Information researchers will be presenting their work.
PAPERS (ACM FAccT Conference)
Misgendered During Moderation: How Transgender Bodies Make Visible Cisnormative Content Moderation Policies and Enforcement in a Meta Oversight Board Case
Samuel Mayworm, Kendra Albert, Oliver L. Haimson
Trans-centered moderation: Trans technology creators and centering transness in platform and community governance
Hibby Thach, Samuel Mayworm, Michaelanne Thomas, Oliver L. Haimson
The Fall of an Algorithm: Characterizing the Dynamics Toward Abandonment
Nari Johnson, Sanika Moharana, Christina Harrington, Nazanin Andalibi, Hoda Heidari, Motahhare Eslami,
Algorithmic Transparency and Participation through the Handoff Lens: Lessons Learned from the U.S. Census Bureau’s Adoption of Differential Privacy
Amina A. Abdu, Lauren M. Chambers, Deirdre K. Mulligan, Abigail Z. Jacobs
Constructing Capabilities: The Politics of Testing Infrastructures for Generative AI
Akal Badi ya Bias: An Exploratory Study of Gender Bias in Hindi Language Technology
Rishav Hada, Safiya Husain, Varun Gumma, Harshita Diddee, Aditya Yadavalli, Agrima Seth, Nidhi Kulkarni, Ujwal Gadiraju, Aditya Vashistha, Vivek Seshadri, Kalika Bali
Perceptions of Policing Surveillance Technologies in Detroit: Moving Beyond "Better than Nothing"
Alex Jiahong Lu, Cameron Moy, Mark S. Ackerman, Jeffrey Morenoff, Tawanna R. Dillahunt
One vs. Many: Comprehending Accurate Information from Multiple Erroneous and Inconsistent AI Generations
Yoonjoo Lee, Kihoon Son, Tae Soo Kim, Jisu Kim, John Joon Young Chung, Eytan Adar, Juho Kim
Tutorials (ACM FAccT Conference)
What is Sociotechnical AI Safety? A participatory workshop about defining and expanding responses to sociotechnical risk in AI Safety
Dialogue/Implications Tutorial Andrew Smart, Shazeda Ahmed, Jake Metcalf, Atoosa Kasirzadeh, Luca Belli, Shalaleh Rismani Roel Dobbe, Abbie Jacobs, Joshua A. Kroll, Donald Martin Jr, Renee Shelby, Heidy Khlaaf, Genevieve Smith
Our goal is to invite discussion and critique of the currently dominant ideas around AI safety, and to shed light on alternative research. The purpose of this Tutorial session is to give space to well established research fields such as systems safety engineering, sociotechnical work in labor studies, that have received less attention than work on alignment or the control of existential risks. At the same time, the session aims to critique and expand the current understanding of AI Safety in order to offer a path forward for research and practice that centers equity, participatory approaches, expanding the kinds of expertise that are relevant, and community inclusion. This research program focuses on current, actual, societal harms from the development and deployment of AI systems, and adapts safety and systems science and engineering approaches to the problem of mitigating risk from these systems, relating existing and emerging technical tools to sociotechnical risks in structured and scientific ways. These approaches are in turn informed by critical social science research so that a synthesis between societal understanding and organizational/technical risk mitigation actually reduces harm to society. Finally, this research program sees the problem of AI Safety not as a technical or mathematical problem, but rather as a social, organizational, political and cultural problem in guiding the development and use of technology. This problem takes on particular urgency as policy responses such as the creation of the U.S. AI Safety Institute and the passage of the EU AI Act demand operationalizing AI Safety in ways that capture sociotechnical risks.
PAPERS (AAAI ICWSM Conference on Web and Social Media)
Calibrate-Extrapolate: Rethinking Prevalence Estimation with Black Box Classifiers
Digital town square? Nextdoor's offline contexts and online discourse
Megan A. Brown, Zeve Sanderson, Sarah Graham, Minjoo Kim, Joshua A. Tucker, Solomon Messing
How to Train Your YouTube Recommender to Avoid Unwanted Videos
Alexander Liu, Siqi Wu, Paul Resnick
Landscape of Large Language Models in Global English News: Topics, Sentiments, and Spatiotemporal Analysis
Lu Xian, Lingyao Li, Yiwei Xu, Ben Zefeng Zhang, Libby Hemphill
With Flying Colors: Predicting Community Success in Large-Scale Collaborative Campaigns
Abraham Israeli, Oren Tsur
Emoji Promotes Developer Participation and Issue Resolution on GitHub
Yuhang Zhou, Xuan Lu, Ge Gao, Qiaozhu Mei, Wei Ai
Emergent Influence Networks in Good-Faith Online Discussions
Henry Kudzanai Dambanemuya, Daniel Romero, Emoke Agnes Horvat
Intermedia Agenda Setting during the 2016 and 2020 U.S. Presidential Elections
Yijing Chen; Yaguang Liu; Lisa Singh; Ceren Budak
Dataset Track Posters (AAAI Conference on Web and Social Media)
A Multilingual Similarity Dataset for News Article Frame
Xi Chen, Mattia Samory, Scott A. Hale, David Jurgens, Przemyslaw Grabowicz
Lightning Talks (AAAI ICWSM Conference on Web and Social Media)
Framing Social Movements on Social Media
Julia Mendelsohn, Maya Vijan, Dallas Card, Ceren Budak