3 citations · 3 across the 6 of their papers we have counts for
6 papers
Towards an Argumentative Foundation for Evaluative AI
Xiang Yin, Tim Miller, Nico Potyka +2
Evaluative AI (EAI) has been recently proposed as a way to support human decision-making, not by producing a single recommendation, but by presenting competing hypotheses together…
Keeping an Eye on AI: A Framework for Effective Human Oversight of AI Systems
Susanne Gaube, Markus Langer, Tim Miller +17
The use of Artificial Intelligence (AI) in high-risk, decision-making scenarios presents technical, safety, and normative challenges; problems that may only be ameliorated by human…
Visual Evaluative AI: A Hypothesis-Driven Tool with Concept-Based Explanations and Weight of Evidence
Thao Le, Tim Miller, Ruihan Zhang +2
This paper presents Visual Evaluative AI, a decision aid that provides positive and negative evidence from image data for a given hypothesis. This tool finds high-level human conce…
An Actionability Assessment Tool for Explainable AI
Ronal Singh, Tim Miller, Liz Sonenberg +4
In this paper, we introduce and evaluate a tool for researchers and practitioners to assess the actionability of information provided to users to support algorithmic recourse. Whil…
Explainable agency: human preferences for simple or complex explanations
Michelle Blom, Ronal Singh, Tim Miller +3
Research in cognitive psychology has established that whether people prefer simpler explanations to complex ones is context dependent, but the question of `simple vs. complex' beco…
From Evidence to Decision: Exploring Evaluative AI
Thao Le, Tim Miller, Liz Sonenberg +2
This paper presents a hypothesis-driven approach to improve AI-supported decision-making that is based on the Evaluative AI paradigm - a conceptual framework that proposes providin…