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Engineering framework for curiosity-driven and humble AI in clinical decision support.

Title: Engineering framework for curiosity-driven and humble AI in clinical decision support.
Authors: Arslan, Janan; Benke, Kurt; Cajas Ordones, Sebastian Andres; Castro, Rowell; Celi, Leo Anthony; Cruz Suarez, Gustavo Adolfo; Delos Reyes, Roben; Engelmann, Justin; Ercole, Ari; Hilel, Almog; Kinyera, Leo; Lange, Maximin; Lunde, Torleif Markussen; Meni, Mackenzie J; Ocampo Osorio, Felipe; Premo, Anna E; Sedlakova, Jana; Vig, Pritika
Publisher Information: BMJ; Department of Medicine; //doi.org/10.1136/bmjhci-2025-101877
Publication Year: 2026
Collection: Apollo - University of Cambridge Repository
Subject Terms: Artificial intelligence; BMJ Health Informatics; Computing Methodologies; Consumer health informatics; Continuity of Patient Care; Humans; Decision Support Systems; Clinical; Exploratory Behavior; Uncertainty
Description: We present BODHI (Balanced, Open-minded, Diagnostic, Humble, and Inquisitive), an engineering framework for curiosity driven and humble clinical decision support artificial intelligence (AI) systems. Despite growing capabilities, large language models (LLMs) often express inappropriate confidence, conflating statistical pattern recognition with genuine medical understanding. BODHI addresses this through a dual reflective architecture that: (1) decomposes epistemic uncertainty into task specific dimensions, and (2) constrains model responses using virtue based stance rules derived from a Virtue Activation Matrix. We validate the framework through controlled evaluation on 200 clinical vignettes from HealthBench Hard, assessing GPT-4o-mini and GPT-4.1-mini across 5 random seeds (2000 total observations). Statistical analysis included bootstrap resampling, paired t tests, and effect size computation. BODHI improved overall clinical response quality (GPT-4.1-mini: +16.6 pp, p
Document Type: article in journal/newspaper
File Description: application/pdf
Language: English
Relation: https://www.repository.cam.ac.uk/handle/1810/399760; https://doi.org/10.17863/CAM.128181
DOI: 10.17863/CAM.128181
Availability: https://www.repository.cam.ac.uk/handle/1810/399760; https://doi.org/10.17863/CAM.128181
Rights: Attribution 4.0 International ; https://creativecommons.org/licenses/by/4.0/
Accession Number: edsbas.F8342591
Database: BASE