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

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 ConGaIT (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.

Publication Details

Journal
Gesellschaft für Informatik (GI)
Published
2025-01-01
DOI
https://doi.org/10.18420/muc2025-mci-src-305
Primary Topic
Geochemistry and Geologic Mapping
Type
article
Field-Weighted Citation Impact
0.00
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article

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

Gesellschaft für Informatik (GI)
Geochemistry and Geologic Mapping
article

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

article en

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 ConGaIT (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.

Gesellschaft für Informatik (GI)
Openalex Percentile: Top 69%
Geochemistry and Geologic Mapping
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