A general framework for scientifically inspired explanations in AI

2 March 2020

Papers citing "A general framework for scientifically inspired explanations in AI"

7 / 7 papers shown

Title
Stop Explaining Black Box Machine Learning Models for High Stakes Decisions and Use Interpretable Models Instead Cynthia Rudin ELM FaML 63 219 0 26 Nov 2018
Explaining Explanations in AI Brent Mittelstadt Chris Russell Sandra Wachter XAI 102 667 0 04 Nov 2018
Explaining Explanations: An Overview of Interpretability of Machine Learning Leilani H. Gilpin David Bau Ben Z. Yuan Ayesha Bajwa Michael A. Specter Lalana Kagal XAI 97 1,862 0 31 May 2018
A Survey Of Methods For Explaining Black Box Models Riccardo Guidotti A. Monreale Salvatore Ruggieri Franco Turini D. Pedreschi F. Giannotti XAI 143 3,970 0 06 Feb 2018
Explanation in Artificial Intelligence: Insights from the Social Sciences Tim Miller XAI 250 4,273 0 22 Jun 2017
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 405 3,813 0 28 Feb 2017
The Mythos of Model Interpretability Zachary Chase Lipton FaML 183 3,706 0 10 Jun 2016