497 citations · 778 across the 23 of their papers we have counts for
8 papers · 1 filter
Explainability Pitfalls: Beyond Dark Patterns in Explainable AI
Upol Ehsan, Mark O. Riedl
To make Explainable AI (XAI) systems trustworthy, understanding harmful effects is just as important as producing well-designed explanations. In this paper, we address an important…
Expanding Explainability: Towards Social Transparency in AI systems
Upol Ehsan, Q. Vera Liao, Michael Muller +2
As AI-powered systems increasingly mediate consequential decision-making, their explainability is critical for end-users to take informed and accountable actions. Explanations in h…
The Transformation of Patient-Clinician Relationships With AI-Based Medical Advice: A "Bring Your Own Algorithm" Era in Healthcare
Oded Nov, Yindalon Aphinyanaphongs, Yvonne W. Lui +5
One of the dramatic trends at the intersection of computing and healthcare has been patients' increased access to medical information, ranging from self-tracked physiological data…
Human-centered Explainable AI: Towards a Reflective Sociotechnical Approach
Upol Ehsan, Mark O. Riedl
Explanations--a form of post-hoc interpretability--play an instrumental role in making systems accessible as AI continues to proliferate complex and sensitive sociotechnical system…
An Interaction Framework for Studying Co-Creative AI
Matthew Guzdial, Mark Riedl
Machine learning has been applied to a number of creative, design-oriented tasks. However, it remains unclear how to best empower human users with these machine learning approaches…
Friend, Collaborator, Student, Manager: How Design of an AI-Driven Game Level Editor Affects Creators
Matthew Guzdial, Nicholas Liao, Jonathan Chen +6
Machine learning advances have afforded an increase in algorithms capable of creating art, music, stories, games, and more. However, it is not yet well-understood how machine learn…