ConGaIT: A Clinician-Centered Dashboard for Contestable AI in Parkinson's Disease Care

TL;DR

ConGaIT is a clinician-centered dashboard that enhances AI transparency and contestability in Parkinson's Disease gait analysis through interpretability, oversight, and structured disagreement features.

Contribution

It introduces a novel human-centered interface for contestable AI in healthcare, integrating visual explanations and feedback mechanisms to improve transparency and clinician control.

Findings

Achieved a high Contestability Assessment Score of 0.970.

Enabled structured disagreement and justification logging for AI decisions.

Demonstrated compliance with emerging regulatory standards.

Abstract

AI-assisted gait analysis holds promise for improving Parkinson's Disease (PD) care, but current clinical dashboards lack transparency and offer no meaningful way for clinicians to interrogate or contest AI decisions. We present Con-GaIT (Contestable Gait Interpretation & Tracking), a clinician-centered system that advances Contestable AI through a tightly integrated interface designed for interpretability, oversight, and procedural recourse. Grounded in HCI principles, ConGaIT enables structured disagreement via a novel Contest & Justify interaction pattern, supported by visual explanations, role-based feedback, and traceable justification logs. Evaluated using the Contestability Assessment Score (CAS), the framework achieves a score of 0.970, demonstrating that contestability can be operationalized through human-centered design in compliance with emerging regulatory standards. A demonstration of the framework is available at https://github.com/hungdothanh/Con-GaIT.