AI Research is not Magic, it has to be Reproducible and Responsible:
Challenges in the AI field from the Perspective of its PhD Students

AI Research is not Magic, it has to be Reproducible and Responsible: Challenges in the AI field from the Perspective of its PhD Students

13 August 2024

Jennifer Renoux

Rafael Tolosana Calasanz

Papers citing "AI Research is not Magic, it has to be Reproducible and Responsible: Challenges in the AI field from the Perspective of its PhD Students"

9 / 9 papers shown

Title
Does the Market of Citations Reward Reproducible Work? Edward Raff HAI CML 22 12 0 08 Apr 2022
Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI Mahima Pushkarna Andrew Zaldivar Oddur Kjartansson AI4TS 64 209 0 03 Apr 2022
Reproducibility as a Mechanism for Teaching Fairness, Accountability, Confidentiality, and Transparency in Artificial Intelligence Ana Lucic Maurits J. R. Bleeker Sami Jullien Samarth Bhargav Maarten de Rijke 16 12 0 01 Nov 2021
Changing the World by Changing the Data Anna Rogers 42 71 0 28 May 2021
Data and its (dis)contents: A survey of dataset development and use in machine learning research Amandalynne Paullada Inioluwa Deborah Raji Emily M. Bender Emily L. Denton A. Hanna 84 518 0 09 Dec 2020
Improving Reproducibility in Machine Learning Research (A Report from the NeurIPS 2019 Reproducibility Program) Joelle Pineau Philippe Vincent-Lamarre Koustuv Sinha V. Larivière A. Beygelzimer Florence dÁlché-Buc E. Fox Hugo Larochelle 68 358 0 27 Mar 2020
Model Cards for Model Reporting Margaret Mitchell Simone Wu Andrew Zaldivar Parker Barnes Lucy Vasserman Ben Hutchinson Elena Spitzer Inioluwa Deborah Raji Timnit Gebru 96 1,869 0 05 Oct 2018
The Devil of Face Recognition is in the Noise Fei Wang Liren Chen Cheng Li Shiyao Huang Yanjie Chen Chao Qian Chen Change Loy NoLa 63 197 0 31 Jul 2018
Datasheets for Datasets Timnit Gebru Jamie Morgenstern Briana Vecchione Jennifer Wortman Vaughan Hanna M. Wallach Hal Daumé Kate Crawford 211 2,158 0 23 Mar 2018