Beyond Diversity and Transparency

Screenshot of Slide 11 in the talk; see the slides link for further details.

On May 30, 2023, I gave a talk “Beyond Diversity and Transparency: Normative Recommendation Goals in Human Context” at the ICA 2023 post-conference “Beyond Nudging, Towards Diversity: Understanding Transparent Algorithmic Recommendation Practices for Media and Communications”.

Work Cited

CIKM20-ee
2020
Fernando Diaz, Bhaskar Mitra, Michael D. Ekstrand, Asia J. Biega, and Ben Carterette. 2020. Evaluating Stochastic Rankings with Expected Exposure. In Proceedings of the 29th ACM International Conference on Information and Knowledge Management (CIKM ’20). ACM, pp. 275–284. DOI 10.1145/3340531.3411962. arXiv:2004.13157 [cs.IR]. NSF PAR 10199451. Acceptance rate: 20%. Nominated for Best Long Paper. Cited 188 times. Cited 166 times.
FnT22
2022
Michael D. Ekstrand, Anubrata Das, Robin Burke, and Fernando Diaz. 2022. Fairness in Information Access Systems. Foundations and Trends® in Information Retrieval 16(1–2) (July 11th, 2022), 1–177. DOI 10.1561/1500000079. arXiv:2105.05779 [cs.IR]. NSF PAR 10347630. Impact factor: 8. Cited 182 times. Cited 83 times.
Excuse me. Can you tell me who lied about the rain? by Zachary Baiel.
The Newsroom S1E1.
Seaver, “Captivating Algorithms: Recommender Systems as Traps.” Journal of Material Culture 24(4). doi:10.1177/1359183518820366.
Selbst, Andrew D., Danah Boyd, Sorelle A. Friedler, Suresh Venkatasubramanian, and Janet Vertesi. 2019. “Fairness and Abstraction in Sociotechnical Systems.” In Proceedings of the Conference on Fairness, Accountability, and Transparency, 59–68. FAT* ’19. doi:10.1145/3287560.3287598.
Green and Viljoen, “Algorithmic Realism: Expanding the Boundaries of Algorithmic Thought.” In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (FAccT 2020). doi:10.1145/3351095.3372840.