Weber Lab
Our lab uses computational methods to study science & technology policy. We are currently working on topics related to labor, regulation, and policy diffusion. We are based at the University of Washington, Seattle, and part of the Data + Science Cooperative (DSCO) at the Information School.
Lab Members
Principal Investigator
Computational methods for studying political economy in platform-mediated environments.
PhD Student
Investigating the impacts of emerging technologies in the service sector.
Alumni
PhD Candidate
Using causal audits to explore the societal impact of algorithms and what might happen differently.
Publications
Understanding Privacy Norms Around LLM-Based Chatbots: A Contextual Integrity Perspective
Tran, Weber, Wolfe · 2025
Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society
Code Contribution and Credit in Science
Brown, Slaughter, Weber · 2025
arXiv preprint arXiv:2510.16242
Designing AI Systems that Augment Human Performed vs. Demonstrated Critical Thinking
Mei, Weber · 2025
arXiv preprint arXiv:2504.14689
Slaughter, Brown, Weber · 2024
Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency
Soft-Search: Two Datasets to Study the Identification and Production of Research Software
Brown, Schwartz, Huang, Weber · 2023
2023 ACM/IEEE Joint Conference on Digital Libraries (JCDL)
Schwartz, Brown, Weber · 2023
Unknown Venue
Speakerbox: Few-Shot Learning for Speaker Identification with Transformers
Brown, Huynh, Weber · 2023
Journal of Open Source Software
Asymmetric by Design: How and Why Labor Policy Impacts Gig Workers
Schwartz, Weber · 2023
Unknown Venue
Councils in Action: Automating the Curation of Municipal Governance Data for Research
Brown, Weber · 2022
Proceedings of the Association for Information Science and Technology
Council Data Project: Software for Municipal Data Collection, Analysis, and Publication
Brown, Huynh, Na, Ledbetter, Ticehurst, Liu, Gilles, Greene, Cho, Ragoler, Weber · 2021
Journal of Open Source Software