Program

The workshop is on Monday, Oct. 14, 2024.

Session 1 (On-site; 09:00–10:30 CEST, 07:00–08:30 UTC)

• Opening {slide}

• Questioning AI: Preserving Decision-Making Autonomy Through Reflection {slide} (long)
  • Simon Fischer
• Bypassing the Popularity Bias: Repurposing Models for Better Long-Tail Recommendation {slide} (long)
  • Václav Blahut and Karel Koupil
• Towards Sustainability of Large Language Models for Recommender Systems (short)
  • Yuan Lin, Debasish Ghose, David Coates and Junyong You
• Data Generation via Latent Factor Simulation for Fairness-aware Re-ranking {slide, code} (short)
  • Elena Štefancová, Cassidy All, Joshua Paup, Martin Homola, Nicholas Mattei and Robin Burke

Session 2 (On-line; 11:15–12:45 CEST, 09:15–10:45 UTC)

• Towards Fairer Health Recommendations: finding informative unbiased samples via Word Sense Disambiguation {slide} (long)
  • Gavin Butts, Jethro R. Lee, Pegah Emdad, Shannon Song, Chiman Salavati, Willmar Sosa Diaz, Shiri Dori-Hacohen and Fabricio Murai
• Reducing Population-level Inequality Can Improve Demographic Group Fairness: a Twitter Case Study {slide} (short)
  • Avijit Ghosh, Tomo Lazovich, Kristian Lum and Christo Wilson
• Designing an Intervention Tool for End-User Algorithm Audits in Personalized Recommendation Systems (short)
  • Qunfang Wu and Lu Xian
• A Unified Causal Framework for Auditing Recommender Systems (short)
  • Vibhhu Sharma, Shantanu Gupta, Nil-Jana Akpinar, Zachary Lipton and Leqi Liu

Session 3 (On-site; 14:30–16:00 CEST, 12:30–14:00 UTC)

Keynote: Recommender systems research under the EU’s Digital Services Act and AI Act

João Vinagre (Joint Research Centre of the European Commission)

Session 4 (On-site; 16:45–18:15 CEST, 14:45–16:15 UTC)

• ARTAI: An Evaluation Platform to Assess Societal Risk of Recommender Algorithms (long)
  • Qin Ruan, Jin Xu, Ruihai Dong, Arjumand Younus, Tai Tan Mai, Barry O’Sullivan and Susan Leavy
• The trade-off between data minimization and fairness in collaborative filtering {slide} (long)
  • Nasim Sonboli, Sipei Li, Mehdi Elahi and Asia Biega
• On the challenges of studying bias in Recommender Systems: The effect of data characteristics and algorithm configuration {slide} (short)
  • Savvina Daniil, Manel Slokom, Mirjam Cuper, Cynthia C. S. Liem, Jacco van Ossenbruggen and Laura Hollink
• RTs ≠ Endorsements: Rethinking Exposure Fairness on Social Media Platforms (short)
  • Nathan Bartley and Kristina Lerman
• Bias Reduction in Social Networks through Agent-Based Simulations (short)
  • Nathan Bartley, Keith Burghardt and Kristina Lerman
• Closing