📰 FAccT 2022 — accepted papers

FAccT 2022 is the 2022 edition of the ACM Conference on Fairness, Accountability, and Transparency (FAccT). OpenAlex lists 181 papers of it; our library holds 1 with our summaries. Below: the most cited papers, every accepted paper, and ours with their topics, authors and institutions.

Most cited papers

By their OpenAlex citations; a paper with our summary links to its page here, the others to the original.

1. Taxonomy of Risks posed by Language Models ↗Laura Weidinger, Jonathan Uesato, Maribeth Rauh et al.713 citations
2. A Review of Taxonomies of Explainable Artificial Intelligence (XAI) Methods ↗Timo Speith337 citations
3. The Values Encoded in Machine Learning Research ↗Abeba Birhane, Pratyusha Kalluri, Dallas Card et al.304 citations
4. The Fallacy of AI Functionality ↗Inioluwa Deborah Raji, I. Elizabeth Kumar, Aaron Horowitz et al.239 citations
5. Measuring the Carbon Intensity of AI in Cloud Instances ↗Jesse Dodge, Taylor Prewitt, Rémi Tachet des Combes et al.234 citations
6. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI ↗Mahima Pushkarna, Andrew Zaldivar, Oddur Kjartansson222 citations
7. Predictability and Surprise in Large Generative ModelsDeep Ganguli, Danny Hernandez, Liane Lovitt et al.198 citations · our summary
8. Who Audits the Auditors? Recommendations from a field scan of the algorithmic auditing ecosystem ↗Sasha Costanza‐Chock, Inioluwa Deborah Raji, Joy Buolamwini192 citations
9. Designing for Responsible Trust in AI Systems: A Communication Perspective ↗Q. Vera Liao, S. Shyam Sundar158 citations
10. What Does it Mean for a Language Model to Preserve Privacy? ↗Hannah Brown, Katherine Lee, Fatemehsadat Mireshghallah et al.158 citations

All accepted papers (181)

The most cited first; 1 with our summary link to their page here, the others to the original.

1. Taxonomy of Risks posed by Language Models ↗Laura Weidinger, Jonathan Uesato, Maribeth Rauh et al.713 citations
2. A Review of Taxonomies of Explainable Artificial Intelligence (XAI) Methods ↗Timo Speith337 citations
3. The Values Encoded in Machine Learning Research ↗Abeba Birhane, Pratyusha Kalluri, Dallas Card et al.304 citations
4. The Fallacy of AI Functionality ↗Inioluwa Deborah Raji, I. Elizabeth Kumar, Aaron Horowitz et al.239 citations
5. Measuring the Carbon Intensity of AI in Cloud Instances ↗Jesse Dodge, Taylor Prewitt, Rémi Tachet des Combes et al.234 citations
6. Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI ↗Mahima Pushkarna, Andrew Zaldivar, Oddur Kjartansson222 citations
7. Predictability and Surprise in Large Generative ModelsDeep Ganguli, Danny Hernandez, Liane Lovitt et al.198 citations · our summary
8. Who Audits the Auditors? Recommendations from a field scan of the algorithmic auditing ecosystem ↗Sasha Costanza‐Chock, Inioluwa Deborah Raji, Joy Buolamwini192 citations
9. Designing for Responsible Trust in AI Systems: A Communication Perspective ↗Q. Vera Liao, S. Shyam Sundar158 citations
10. What Does it Mean for a Language Model to Preserve Privacy? ↗Hannah Brown, Katherine Lee, Fatemehsadat Mireshghallah et al.158 citations
11. How Explainability Contributes to Trust in AI ↗Andrea Ferrario, Michele Loi153 citations
12. Learning to Break Deep Perceptual Hashing: The Use Case NeuralHash ↗Lukas Struppek, Dominik Hintersdorf, Daniel Neider et al.148 citations
13. Accountability in an Algorithmic Society: Relationality, Responsibility, and Robustness in Machine Learning ↗A. Feder Cooper, Emanuel Moss, Benjamin Laufer et al.129 citations
14. The Forgotten Margins of AI Ethics ↗Abeba Birhane, Elayne Ruane, Thomas Laurent et al.122 citations
15. News from Generative Artificial Intelligence Is Believed Less ↗Chiara Longoni, Andrey Fradkin, Luca Cian et al.120 citations
16. How Different Groups Prioritize Ethical Values for Responsible AI ↗Maurice Jakesch, Zana Buçinca, Saleema Amershi et al.112 citations
17. Interactive Model Cards: A Human-Centered Approach to Model Documentation ↗Anamaria Crisan, Margaret Drouhard, Jesse Vig et al.101 citations
18. Who Goes First? Influences of Human-AI Workflow on Decision Making in Clinical Imaging ↗Riccardo Fogliato, Shreya Chappidi, Matthew P. Lungren et al.100 citations
19. Exploring How Machine Learning Practitioners (Try To) Use Fairness Toolkits ↗Wesley Hanwen Deng, Manish Nagireddy, Michelle Seng Ah Lee et al.96 citations
20. It’s Just Not That Simple: An Empirical Study of the Accuracy-Explainability Trade-off in Machine Learning for Public Policy ↗Andrew S Bell, Ian René Solano-Kamaiko, Oded Nov et al.92 citations
21. Towards Intersectionality in Machine Learning: Including More Identities, Handling Underrepresentation, and Performing Evaluation ↗Angelina Wang, V. Ramaswamy, Olga Russakovsky87 citations
22. At the Tensions of South and North: Critical Roles of Global South Stakeholders in AI Governance ↗Marie-Thérèse Png85 citations
23. Goodbye Tracking? Impact of iOS App Tracking Transparency and Privacy Labels ↗Konrad Kollnig, Anastasia Shuba, Max G. Van Kleek et al.85 citations
24. Model Multiplicity: Opportunities, Concerns, and Solutions ↗Emily Black, Manish Raghavan, Solon Barocas80 citations
25. On the Existence of Simpler Machine Learning Models ↗Lesia Semenova, Cynthia D Rudin, Ronald Parr80 citations

See all 181 papers in FAccT 2022 — accepted papers →

📄 Papers with our summary in our library (1)

The most cited first (OpenAlex citations plus our library's).

1. Predictability and Surprise in Large Generative ModelsACM Conference on Fairness, Accountability, and Transparency (FAccT)Deep Ganguli, Danny Hernandez, Liane Lovitt, et al.2022 · 268 citations

📚 Fields

🖥️Computer Science (1)🤝Social Sciences (1)

🧑‍🔬 Top authors

Authors with a page who published here most often: their works here, and the citations of those works.

🏛️ Top institutions

Institutions on the bylines of its works here, by the number of works.

🏢AnthropicSan Francisco · United States1 work here

works and citations from OpenAlex and our library.

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