From Model Performance to Claim: How a Change of Focus in Machine Learning Replicability Can Help Bridge the Responsibility Gap

19 April 2024

Papers citing "From Model Performance to Claim: How a Change of Focus in Machine Learning Replicability Can Help Bridge the Responsibility Gap"

20 / 20 papers shown

Title
WEIRD FAccTs: How Western, Educated, Industrialized, Rich, and Democratic is FAccT? Ali Akbar Septiandri Marios Constantinides Mohammad Tahaei Daniele Quercia 60 36 0 10 May 2023
Dislocated Accountabilities in the AI Supply Chain: Modularity and Developers' Notions of Responsibility D. Widder D. Nafus 52 73 0 20 Sep 2022
The Fallacy of AI Functionality Inioluwa Deborah Raji Indra Elizabeth Kumar Aaron Horowitz Andrew D. Selbst 56 184 0 20 Jun 2022
The Conflict Between Explainable and Accountable Decision-Making Algorithms Gabriel Lima Nina Grgić-Hlavca Jin Keun Jeong M. Cha 40 37 0 11 May 2022
Towards a multi-stakeholder value-based assessment framework for algorithmic systems Mireia Yurrita Dave Murray-Rust Agathe Balayn A. Bozzon MLAU 55 29 0 09 May 2022
The Road to Explainability is Paved with Bias: Measuring the Fairness of Explanations Aparna Balagopalan Haoran Zhang Kimia Hamidieh Thomas Hartvigsen Frank Rudzicz Marzyeh Ghassemi 64 78 0 06 May 2022
Goodbye Tracking? Impact of iOS App Tracking Transparency and Privacy Labels Konrad Kollnig A. Shuba Max Van Kleek Reuben Binns N. Shadbolt MQ 45 66 0 07 Apr 2022
Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI Mahima Pushkarna Andrew Zaldivar Oddur Kjartansson AI4TS 81 212 0 03 Apr 2022
Human Interpretation of Saliency-based Explanation Over Text Hendrik Schuff Alon Jacovi Heike Adel Yoav Goldberg Ngoc Thang Vu MILM XAI FAtt 180 40 0 27 Jan 2022
AI and the Everything in the Whole Wide World Benchmark Inioluwa Deborah Raji Emily M. Bender Amandalynne Paullada Emily L. Denton A. Hanna 77 305 0 26 Nov 2021
AI Ethics Statements -- Analysis and lessons learnt from NeurIPS Broader Impact Statements Carolyn Ashurst Emmie Hine Paul Sedille A. Carlier 64 30 0 02 Nov 2021
The Values Encoded in Machine Learning Research Abeba Birhane Pratyusha Kalluri Dallas Card William Agnew Ravit Dotan Michelle Bao 64 285 0 29 Jun 2021
The Fundamental Principles of Reproducibility Odd Erik Gundersen 52 62 0 19 Nov 2020
Underspecification Presents Challenges for Credibility in Modern Machine Learning Alexander DÁmour Katherine A. Heller D. Moldovan Ben Adlam B. Alipanahi ... Kellie Webster Steve Yadlowsky T. Yun Xiaohua Zhai D. Sculley OffRL 109 687 0 06 Nov 2020
From Optimizing Engagement to Measuring Value S. Milli Luca Belli Moritz Hardt 28 47 0 21 Aug 2020
Replication Markets: Results, Lessons, Challenges and Opportunities in AI Replication Yang Liu Michael Gordon Juntao Wang Michael Bishop Yiling Chen T. Pfeiffer C. Twardy Domenico Viganola 26 7 0 10 May 2020
On the Apparent Conflict Between Individual and Group Fairness Reuben Binns FaML 66 310 0 14 Dec 2019
Measurement and Fairness Abigail Z. Jacobs Hanna M. Wallach 78 388 0 11 Dec 2019
A Step Toward Quantifying Independently Reproducible Machine Learning Research Edward Raff 40 131 0 14 Sep 2019
Machine Learning that Matters K. Wagstaff 116 313 0 18 Jun 2012