Understanding Trust and Reliance Development in AI Advice: Assessing Model Accuracy, Model Explanations, and Experiences from Previous Interactions.
People are increasingly interacting with AI systems, but successful interactions depend on people trusting these systems only when appropriate. Since neither gaining trust in AI advice nor restoring lost trust after AI mistakes is warranted, we seek to ...
“I Want It That Way”: Enabling Interactive Decision Support Using Large Language Models and Constraint Programming
- Connor Lawless,
- Jakob Schoeffer,
- Lindy Le,
- Kael Rowan,
- Shilad Sen,
- Cristina St. Hill,
- Jina Suh,
- Bahareh Sarrafzadeh
A critical factor in the success of many decision support systems is the accurate modeling of user preferences. Psychology research has demonstrated that users often develop their preferences during the elicitation process, highlighting the pivotal role ...
Categorical and Continuous Features in Counterfactual Explanations of AI Systems
Recently, eXplainable AI (XAI) research has focused on the use of counterfactual explanations to address interpretability, algorithmic recourse, and bias in AI system decision-making. The developers of these algorithms claim they meet user requirements in ...
Accelerating Scientific Paper Skimming with Augmented Intelligence Through Customizable Faceted Highlights
- Raymond Fok,
- Luca Soldaini,
- Cassidy Trier,
- Erin Bransom,
- Kelsey MacMillan,
- Evie Cheng,
- Hita Kambhamettu,
- Jonathan Bragg,
- Kyle Lo,
- Marti A. Hearst,
- Andrew Head,
- Daniel S. Weld
Scholars need to keep up with an exponentially increasing flood of scientific papers. To aid this challenge, we introduce Scim, a novel intelligent interface that helps scholars skim papers to rapidly review and gain a cursory understanding of its ...
Measuring User Experience Inclusivity in Human-AI Interaction via Five User Problem-Solving Styles
Motivations: Recent research has emerged on generally how to improve AI products’ Human-AI Interaction (HAI) User Experience (UX), but relatively little is known about HAI-UX inclusivity. For example, what kinds of users are supported, and who are left ...
Insights into Natural Language Database Query Errors: From Attention Misalignment to User Handling Strategies
Querying structured databases with natural language (NL2SQL) has remained a difficult problem for years. Recently, the advancement of machine learning (ML), natural language processing (NLP), and large language models (LLM) have led to significant ...