Direction: AI Explainability, Trust, and Calibration

Explanation Form Design and Comprehension Effects

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helpResearch questionExplanation Form Design and Comprehension Effects

What are the effects of AI prediction errors on users' long-term trust in complex decision tasks?

IUI '23It Seems Smart, but It Acts Stupid: Development of Trust in AI Advice in a Repeated Legal Decision-Making Task

lightbulbPractical problemExplanation Form Design and Comprehension Effects

Users struggle to build long-term trust when facing erroneous AI recommendations.

IUI '23It Seems Smart, but It Acts Stupid: Development of Trust in AI Advice in a Repeated Legal Decision-Making Task

helpResearch questionExplanation Form Design and Comprehension Effects

How can combining individual predictions with population-level statistical distribution explanations improve healthcare workers' understanding of diabetes risk?

IUI '23Directive Explanations for Monitoring the Risk of Diabetes Onset: Introducing Directive Data-Centric Explanations and Combinations to Support What-If Explorations

helpResearch questionExplanation Form Design and Comprehension Effects

Can improved counterfactual explanations (e.g., avoiding unreasonable recommendations) enhance user trust and adoption in real medical contexts?

IUI '23Directive Explanations for Monitoring the Risk of Diabetes Onset: Introducing Directive Data-Centric Explanations and Combinations to Support What-If Explorations

helpResearch questionExplanation Form Design and Comprehension Effects

How can interactive dashboard visualizations support patients and doctors in what-if exploration and health management optimization?

IUI '23Directive Explanations for Monitoring the Risk of Diabetes Onset: Introducing Directive Data-Centric Explanations and Combinations to Support What-If Explorations

lightbulbPractical problemExplanation Form Design and Comprehension Effects

Non-expert healthcare workers and patients struggle to understand the sources of machine learning-predicted diabetes risk.

IUI '23Directive Explanations for Monitoring the Risk of Diabetes Onset: Introducing Directive Data-Centric Explanations and Combinations to Support What-If Explorations

helpResearch questionExplanation Form Design and Comprehension Effects

When intelligent decision support systems (IDS) output suboptimal recommendations, how can subgoal explanations (ESB) help users more effectively identify and reject them?

IUI '23Application of Subgoal-Based Explanations in Unreliable Intelligent Decision Support Systems

helpResearch questionExplanation Form Design and Comprehension Effects

Can subgoal explanations (ESB) improve users' ability to complete tasks without system support (when IDS fails)?

IUI '23Application of Subgoal-Based Explanations in Unreliable Intelligent Decision Support Systems

helpResearch questionExplanation Form Design and Comprehension Effects

Which explanation method do users prefer: subgoal explanations (ESB), action-only recommendations (aIDS), or causal chain explanations (ECLC)?

IUI '23Application of Subgoal-Based Explanations in Unreliable Intelligent Decision Support Systems

lightbulbPractical problemExplanation Form Design and Comprehension Effects

Users struggle to evaluate whether intelligent system recommendations are reliable in complex tasks.

IUI '23Application of Subgoal-Based Explanations in Unreliable Intelligent Decision Support Systems

helpResearch questionExplanation Form Design and Comprehension Effects

Are multiple counterfactual examples easier for lay users to understand than single examples?

IUI '23Investigating the Intelligibility of Plural Counterfactual Examples for Non-Expert Users: an Explanation User Interface Proposition and User Study

helpResearch questionExplanation Form Design and Comprehension Effects

Can comparative analysis features help lay users better understand multiple counterfactual examples?

IUI '23Investigating the Intelligibility of Plural Counterfactual Examples for Non-Expert Users: an Explanation User Interface Proposition and User Study

helpResearch questionExplanation Form Design and Comprehension Effects

Can lay users effectively extract valuable information from multiple counterfactual examples?

IUI '23Investigating the Intelligibility of Plural Counterfactual Examples for Non-Expert Users: an Explanation User Interface Proposition and User Study

lightbulbPractical problemExplanation Form Design and Comprehension Effects

Lay users struggle to understand machine learning model decision logic.

IUI '23Investigating the Intelligibility of Plural Counterfactual Examples for Non-Expert Users: an Explanation User Interface Proposition and User Study

helpResearch questionExplanation Form Design and Comprehension Effects

What types of explanations improve users' error correction success when interacting with natural language generation systems?

IUI '23Follow the Successful Herd: Towards Explanations for Improved Use and Mental Models of Natural Language Systems

helpResearch questionExplanation Form Design and Comprehension Effects

How do system-based and social-based explanations differ in users' task accuracy and efficiency?

IUI '23Follow the Successful Herd: Towards Explanations for Improved Use and Mental Models of Natural Language Systems

helpResearch questionExplanation Form Design and Comprehension Effects

Can explanation design improve users' mental models of natural language generation systems?

IUI '23Follow the Successful Herd: Towards Explanations for Improved Use and Mental Models of Natural Language Systems

lightbulbPractical problemExplanation Form Design and Comprehension Effects

Users struggle to understand how natural language generation systems work, leading to interaction failures and wasted time.

IUI '23Follow the Successful Herd: Towards Explanations for Improved Use and Mental Models of Natural Language Systems