One Explanation Does Not Fit All: The Promise of Interactive Explanations for Machine Learning Transparency

27 January 2020

Papers citing "One Explanation Does Not Fit All: The Promise of Interactive Explanations for Machine Learning Transparency"

6 / 6 papers shown

Title
Contrastive Explanations That Anticipate Human Misconceptions Can Improve Human Decision-Making Skills Zana Buçinca S. Swaroop Amanda E. Paluch Finale Doshi-Velez Krzysztof Z. Gajos 64 2 0 05 Oct 2024
Navigating Explanatory Multiverse Through Counterfactual Path Geometry Kacper Sokol E. Small Yueqing Xuan 47 5 0 05 Jun 2023
Explainable AI: Beware of Inmates Running the Asylum Or: How I Learnt to Stop Worrying and Love the Social and Behavioural Sciences Tim Miller Piers Howe L. Sonenberg AI4TS SyDa 28 373 0 02 Dec 2017
Counterfactual Explanations without Opening the Black Box: Automated Decisions and the GDPR Sandra Wachter Brent Mittelstadt Chris Russell MLAU 36 2,332 0 01 Nov 2017
Explanation in Artificial Intelligence: Insights from the Social Sciences Tim Miller XAI 200 4,229 0 22 Jun 2017
Using Visual Analytics to Interpret Predictive Machine Learning Models Josua Krause Adam Perer E. Bertini HAI 48 65 0 17 Jun 2016