5 citations · 11 across the 7 of their papers we have counts for
7 papers
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…
Explaining Model Confidence Using Counterfactuals
Thao Le, Tim Miller, Ronal Singh +1
Displaying confidence scores in human-AI interaction has been shown to help build trust between humans and AI systems. However, most existing research uses only the confidence scor…
Improving Model Understanding and Trust with Counterfactual Explanations of Model Confidence
Thao Le, Tim Miller, Ronal Singh +1
In this paper, we show that counterfactual explanations of confidence scores help users better understand and better trust an AI model's prediction in human-subject studies. Showin…
Collaborative Human-Agent Planning for Resilience
Ronal Singh, Tim Miller, Darryn Reid
Intelligent agents powered by AI planning assist people in complex scenarios, such as managing teams of semi-autonomous vehicles. However, AI planning models may be incomplete, lea…
LEx: A Framework for Operationalising Layers of Machine Learning Explanations
Ronal Singh, Upol Ehsan, Marc Cheong +2
Several social factors impact how people respond to AI explanations used to justify AI decisions affecting them personally. In this position paper, we define a framework called the…
Directive Explanations for Actionable Explainability in Machine Learning Applications
Ronal Singh, Paul Dourish, Piers Howe +4
This paper investigates the prospects of using directive explanations to assist people in achieving recourse of machine learning decisions. Directive explanations list which specif…
Interaction Design for Explainable AI: Workshop Proceedings
Prashan Madumal, Ronal Singh, Joshua Newn +1
As artificial intelligence (AI) systems become increasingly complex and ubiquitous, these systems will be responsible for making decisions that directly affect individuals and soci…