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"

8 / 8 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 79 2 0 05 Oct 2024
Navigating Explanatory Multiverse Through Counterfactual Path Geometry Kacper Sokol E. Small Yueqing Xuan 75 6 0 05 Jun 2023
A Grounded Interaction Protocol for Explainable Artificial Intelligence Prashan Madumal Tim Miller L. Sonenberg F. Vetere 74 98 0 05 Mar 2019
The Challenge of Crafting Intelligible Intelligence Daniel S. Weld Gagan Bansal 52 244 0 09 Mar 2018
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 53 373 0 02 Dec 2017
Counterfactual Explanations without Opening the Black Box: Automated Decisions and the GDPR Sandra Wachter Brent Mittelstadt Chris Russell MLAU 107 2,352 0 01 Nov 2017
Explanation in Artificial Intelligence: Insights from the Social Sciences Tim Miller XAI 242 4,262 0 22 Jun 2017
Using Visual Analytics to Interpret Predictive Machine Learning Models Josua Krause Adam Perer E. Bertini HAI 56 65 0 17 Jun 2016