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The Collective Trust Game: An Online Group Adaptation of the Trust Game Based on the HoneyComb Paradigm
Published on: October 20, 2022
TRUST-AI
Remi Rothwell1, Adam Julius1, Robert Crichton1
1University College London, London, UK.
None:
Artificial intelligence is rapidly transforming healthcare, offering new opportunities to enhance clinical decision making, efficiency, and patient outcomes. However, ongoing concerns remain a barrier to widespread adoption. Current reporting guidelines provide valuable and detailed frameworks, but their focus on existing technologies limits their adaptability to emerging approaches. To address this gap, we propose TRUST-AI, a high-level guide designed by healthcare professionals for healthcare professionals. TRUST-AI distils seven domains: Transparency, Reliability, Use Case, Safety and Security, Treatment Equity, Affordability and Environmental Impact, and Integration. These are combined into an accessible guide to support the responsible evaluation of artificial intelligence systems in healthcare. The guide is intended to endure over time, maintaining its relevance as artificial intelligence technologies continue to advance and diversify. By embedding these principles, TRUST-AI seeks to equip healthcare professionals with the knowledge to act as informed gatekeepers, ensuring that trust in artificial intelligence can be established safely across evolving health sectors.
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