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Intelligent Reasoning Cues: A Framework and Case Study of the Roles of AI Information in Complex Decisions
Venkatesh Sivaraman1, Eric Mason1, Mengfan Li1
1Carnegie Mellon University, Pittsburgh, PA, USA.
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. CHI Conference
|May 18, 2026
Summary
Artificial intelligence (AI) decision support systems need better design. Intelligent reasoning cues, discrete AI information pieces, can improve clinical decision-making by influencing user thought processes.
Area of Science:
- Human-Computer Interaction
- Clinical Decision Support
- Artificial Intelligence
Background:
- AI decision support systems (DSS) can be accurate but fail to aid users or improve decisions.
- Current theories focus on AI reliance calibration, neglecting system design's impact on reasoning.
- AI interfaces are re-envisioned as collections of intelligent reasoning cues.
Purpose of the Study:
- To explore how different types of intelligent reasoning cues influence decision-making processes.
- To understand the role of discrete AI information in high-stakes clinical contexts.
Main Methods:
- Contextual inquiries with six clinical teams.
- Think-aloud study involving 25 physicians.
- Analysis of eight types of reasoning cues in sepsis treatment decisions.
Main Results:
- Reasoning cues exhibit distinct patterns of influence on decision-making.
- Specific cue designs can directly inform AI system development.
- Prioritizing cues for high variability/discretion tasks is beneficial.
Conclusions:
- Intelligent reasoning cues offer a novel framework for AI-assisted decision-making design.
- AI interfaces should adapt to user needs and provide complementary insights.
- Optimizing reasoning cues can enhance AI support in complex clinical scenarios.
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