5 papers
A Framework for Measuring Appropriate Reliance on Set-Valued AI Advice
Ranjan Mishra, Jakob Schoeffer
Appropriate reliance on AI advice has become a central research theme in human-AI collaboration. Existing frameworks have focused exclusively on point predictions as AI advice. How…
"It Was a Magical Box": Understanding Practitioner Workflows and Needs in Optimization
Connor Lawless, Jakob Schoeffer, Madeleine Udell
Optimization underpins decision-making in domains from healthcare to logistics, yet for many practitioners it remains a "magical box": powerful but opaque, difficult to use, and re…
Perils of Label Indeterminacy: A Case Study on Prediction of Neurological Recovery After Cardiac Arrest
Jakob Schoeffer, Maria De-Arteaga, Jonathan Elmer
The design of AI systems to assist human decision-making typically requires the availability of labels to train and evaluate supervised models. Frequently, however, these labels ar…
AI Reliance and Decision Quality: Fundamentals, Interdependence, and the Effects of Interventions
Jakob Schoeffer, Johannes Jakubik, Michael Voessing +2
In AI-assisted decision-making, a central promise of having a human-in-the-loop is that they should be able to complement the AI system by overriding its wrong recommendations. In…
"I Want It That Way": Enabling Interactive Decision Support Using Large Language Models and Constraint Programming
Connor Lawless, Jakob Schoeffer, Lindy Le +5
A critical factor in the success of decision support systems is the accurate modeling of user preferences. Psychology research has demonstrated that users often develop their prefe…