Bias in AIThe Bias in AI reading group meets to discuss various fairness issues that emerge in artificial intelligence. Anyone is welcome to present either their own work or other work in the space for the group to discuss.Please contact Kara Schechtman at [email protected] for further information. Sign up for our mailing list to get regular updates.This group will meet on Wednesdays from 11 a.m. to noon during the spring 2025 semester.CITP Book ClubThe CITP Book Club usually meets once per month. This group is restricted to Princeton University faculty, staff and students. Join the mailing list.For additional information please contact Mihir Kshirsagar at [email protected].Princeton TechSoc Reading GroupThe Princeton TechSoc Reading Group is dedicated to exploring the interrelationships between technology and society, with an emphasis on IT policy issues.Subscribe to the email list. Please contact Nitya Nadgir at [email protected] or Basi Imana [email protected] with any questions.Recommender Systems Reading GroupThe goal of the recommender systems (RS) reading group is to gain deeper understanding both of seminal work as well as emerging ideas in the field. Papers will include research on RS algorithm development and evaluation; user-centered design and user studies for RS; fairness, accountability, and explainability in recommendations; and societal impacts of RS.This reading group is on hiatus.Past papers include:Zhao, Q., Harper, F. M., Adomavicius, G., & Konstan, J. A. (2018, April). Explicit or implicit feedback? Engagement or satisfaction? A field experiment on machine-learning-based recommender systems. In Proceedings of the 33rd Annual ACM Symposium on Applied Computing (pp. 1331-1340).Hu, Y., Koren, Y., & Volinsky, C. (2008, December). Collaborative filtering for implicit feedback datasets. In 2008 Eighth IEEE International Conference on Data Mining (pp. 263-272). Ieee.Dacrema, M. F., Cremonesi, P., & Jannach, D. (2019, September). Are we really making much progress? A worrying analysis of recent neural recommendation approaches. In Proceedings of the 13th ACM Conference on Recommender Systems (pp. 101-109).Knijnenburg, B. P., Bostandjiev, S., O'Donovan, J., & Kobsa, A. (2012, September). Inspectability and control in social recommenders. In Proceedings of the sixth ACM conference on Recommender systems (pp. 43-50).Jannach, D., & Adomavicius, G. (2016, September). Recommendations with a purpose. In Proceedings of the 10th ACM conference on recommender systems (pp. 7-10).Cremonesi, P., Koren, Y., & Turrin, R. (2010, September). Performance of recommender algorithms on top-n recommendation tasks. In Proceedings of the fourth ACM conference on Recommender systems (pp. 39-46).This group is open to the Princeton University community.Security and Privacy Reading GroupCITP's Security & Privacy Reading Group is an informal chat for students, postdocs, and fellows to read recent conference papers in technical privacy and security topics.Meeting information will be posted here when available.Tech & LaborThe Tech & Labor reading group is a collection of folks who are interested in developing their fluency around topics pertaining to the intersection of labor and technology. We invite participants from all backgrounds to participate as we believe that the intersection of tech & labor needs to be analyzed from a multitude of perspectives. We hope to foster a space where we can learn from each other, share ideas, bring questions, and brainstorm possible new directions for research. We have a core value of respecting differing perspectives and believe that diversity in viewpoints is healthy for discussion.In the past, meetings were led by a discussant who selected the readings (two core readings and up to five supplemental readings) and proposed a list of discussion questions. The meeting itself was open ended & reading/discussion questions were intended to guide conversation.This reading group is on hiatus.Works in Progress (WiP) Reading GroupThe Works In Progress reading group (WiP) meets to discuss ongoing projects and to receive feedback from peers at the center. It is a great way to introduce what you're working on and to bounce ideas off others in a relatively relaxed setting. The group plans to meet in a hybrid format once or twice a month during the semester. Whether you’re based in Princeton or working remotely, you’re welcome to join us!This reading group is open to any Princeton affiliate, including faculty, staff and undergraduate and graduate students.For more information please contact Benedikt Stroebl at [email protected] or Luxi He at [email protected].