Human-Centered AI · Human-AI Interaction · AI Evaluation
I am an undergraduate researcher in Applied Psychology working on human-AI decision calibration under epistemic uncertainty.
My research asks a simple question:
How should people rely on AI when the system's apparent confidence, precision, or reliability exceeds what its evidence can justify?
I study how AI systems communicate reliability, uncertainty, and numerical precision, and how these signals shape human reliance and decision quality.
I am currently designing a behavioral study on how displayed numerical precision × supporting-evidence resolution affects reliance on AI-generated advice.
The core question is whether people become more willing to rely on an AI when its output appears more numerically precise—even when the available evidence does not warrant that level of precision.
Status: Study design and experimental materials in progress. No human-participant findings are claimed yet.
My projects examine different parts of the same human-AI decision pipeline:
| Project | Role in the research program | Evidence status |
|---|---|---|
| FitCalib-Bench | Measuring calibration and uncertainty-expression failures in AI advice | Closed engineering audit |
| CheckMyCoach | Testing an intervention pipeline for correcting problematic AI advice | Offline-evaluated prototype |
| Knowledge Compiler | Structuring source evidence for auditable AI reasoning and evaluation | Evidence infrastructure |
| InteractionKit | Experimental infrastructure for structured Human-AI interaction studies | Frozen methodological asset · pending human validation |
| CalTrust | Exploring adaptive assistance based on observed trust and reliance signals | Frozen simulation-only prototype |
Together, these projects explore a broader problem:
measurement → intervention → evidence → behavioral evaluation → adaptive assistance
- Human-AI Interaction
- Human-AI Decision Making
- AI Evaluation & Calibration
- Uncertainty and Confidence Communication
- Trust, Reliance, and Overreliance
- Interactive / Human-Centered AI
I try to keep a strict boundary between different forms of evidence.
Software implementation, simulation, automated evaluation, and human behavioral evidence are not interchangeable.
Public project pages therefore distinguish engineering evidence from scientific evidence, and I do not claim human-participant findings where human studies have not yet been conducted.