--- title: "FAccT 2026 — all accepted papers, page 4 — the most cited first" description: "All 314 papers of FAccT 2026 · page 4 of 4, the most cited first; those with our summary link to it." canonical: "https://research.elamur.ai/free/en/venues/acm-conference-on-fairness-accountability-and-transparency-facct/2026/papers/page/4/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/venues/acm-conference-on-fairness-accountability-and-transparency-facct/2026/papers/page/4/) [home](https://md.research.elamur.ai/free/en/) / [venues](https://md.research.elamur.ai/free/en/venues/) / [FAccT](https://md.research.elamur.ai/free/en/venues/acm-conference-on-fairness-accountability-and-transparency-facct/) / [2026](https://md.research.elamur.ai/free/en/venues/acm-conference-on-fairness-accountability-and-transparency-facct/2026/) / [papers](https://md.research.elamur.ai/free/en/venues/acm-conference-on-fairness-accountability-and-transparency-facct/2026/papers/) / page 4 # FAccT 2026: all accepted papers 314 papers · page 4 of 4 · the most cited first · [← FAccT 2026](https://md.research.elamur.ai/free/en/venues/acm-conference-on-fairness-accountability-and-transparency-facct/2026/) [← prev](https://md.research.elamur.ai/free/en/venues/acm-conference-on-fairness-accountability-and-transparency-facct/2026/papers/page/3/) [1](https://md.research.elamur.ai/free/en/venues/acm-conference-on-fairness-accountability-and-transparency-facct/2026/papers/) [2](https://md.research.elamur.ai/free/en/venues/acm-conference-on-fairness-accountability-and-transparency-facct/2026/papers/page/2/) [3](https://md.research.elamur.ai/free/en/venues/acm-conference-on-fairness-accountability-and-transparency-facct/2026/papers/page/3/) **4** 301. **[Why AI Harms Can't Be Fixed One Identity at a Time: What 5300 Incident Reports Reveal About Intersectionality ↗](https://doi.org/10.1145/3805689.3812347)**Edyta P. Bogucka, Sanja Šćepanović, Daniele Quercia 302. **[With a Little Help From My Friends: Collective Manipulation in Risk-Controlling Recommender Systems ↗](https://doi.org/10.1145/3805689.3812352)**Giovanni De Toni, Cristian Consonni, Erasmo Purificato et al. 303. **[You can't solve democracy in Q3: A Critical Analysis of Corporate Initiatives to Democratize AI ↗](https://doi.org/10.1145/3805689.3812298)**Meg Young, Michael Madaio, Carl Francis DiSalvo 304. **[Your Recourse, My Loss? Algorithmic Recourse under Shared Constraints ↗](https://doi.org/10.1145/3805689.3812327)**Zahra Khotanlou, Kate S. Larson, Amir-Hossein Karimi 305. **[“A natural language interface for everyday life”: The social and political functions of AI capabilities discourses ↗](https://doi.org/10.1145/3805689.3806481)**J. Zhang, Su Lin Blodgett, Nina Markl 306. **[“Detective Work We Shouldn't Have to Do”: Practitioner Challenges in Regulatory-Aligned Data Quality in Machine Learning Systems ↗](https://doi.org/10.1145/3805689.3812313)**Y Y Wang, Kristina Irion, Paul Groth et al. 307. **[“Label from Somewhere”: Reflexive Annotating for Situated AI Alignment ↗](https://doi.org/10.1145/3805689.3812268)**Anne Arzberger, Céline Offerman, Ujwal Gadiraju et al. 308. **[“Pretty Much Free”: Perceived Costs and Value(s) in Academic LLM Research ↗](https://doi.org/10.1145/3805689.3812414)**Amanda Meng, Kayla Uleah, Betsy James DiSalvo 309. **[“Robotic answers”: Participatory Identification of Risks in AI-Assisted Interview Training by Job Seekers ↗](https://doi.org/10.1145/3805689.3812234)**Pooja S. B. Rao, Laxmi Narayen Nagarajan Venkatesan, Dinesh Babu Jayagopi et al. 310. **[“Taking Stock at FAccT”: Using Participatory Design to Co-Create a Vision for the Fairness, Accountability and Transparency Community ↗](https://doi.org/10.1145/3805689.3812270)**Shiran Dudy, Jan Simson, Yanan Long 311. **[“This Model Needs to Chill”: an Experimental Scoring Scale for Participatory Perceptions of Gender Bias and Harm in Large Language Model-Generated Text ↗](https://doi.org/10.1145/3805689.3806520)**Lara Dal Molin 312. **[“This Wasn't Made for Me”: Recentering User Experience and Emotional Impact in the Evaluation of ASR Bias ↗](https://doi.org/10.1145/3805689.3806448)**Siyu Liang, Alicia Beckford Wassink 313. **[“Where is this coming from?” Uncovering Trustworthiness Ideals in AI-powered Peripartum Information Seeking ↗](https://doi.org/10.1145/3805689.3812277)**Vaibhav Balloli, Julia Erickson, Xinyi Li et al. 314. **[“Woke AI is a big threat to free speech”: Red-Techno Scares in AI Risk Discourse on Fox News ↗](https://doi.org/10.1145/3805689.3812266)**Sakina Hansen [← prev](https://md.research.elamur.ai/free/en/venues/acm-conference-on-fairness-accountability-and-transparency-facct/2026/papers/page/3/) [1](https://md.research.elamur.ai/free/en/venues/acm-conference-on-fairness-accountability-and-transparency-facct/2026/papers/) [2](https://md.research.elamur.ai/free/en/venues/acm-conference-on-fairness-accountability-and-transparency-facct/2026/papers/page/2/) [3](https://md.research.elamur.ai/free/en/venues/acm-conference-on-fairness-accountability-and-transparency-facct/2026/papers/page/3/) **4** - [← back to](https://md.research.elamur.ai/free/en/venues/acm-conference-on-fairness-accountability-and-transparency-facct/2026/) — FAccT 2026