Article of the Week: December 8

What we talk about when we talk about trust: Theory of trust for AI in healthcare

Author

Marina Pulini-Franks MD
December 08, 2023

What we talk about when we talk about trust: Theory of trust for AI in healthcare

Artificial intelligence (AI) is at the forefront of innovation in medicine. Researchers and AI developers have often claimed that "trust" is a critica…

www.sciencedirect.com/science/article/pii/S2666521220300016

Main Point

When discussing trust in the context of AI in healthcare, it refers to the reliance patients, healthcare professionals, and society have on artificial intelligence systems to make accurate, ethical, and safe decisions in healthcare settings. Trust in AI in healthcare is crucial because it affects the acceptance and adoption of these technologies, which, in turn, impact patient outcomes and the overall healthcare system. Establishing trust involves ensuring transparency, accountability, and the ability to interpret and validate AI-driven decisions. Researchers and experts in the field have been working on developing theoretical frameworks to understand and enhance trust in AI applications within healthcare. These frameworks often involve aspects like algorithm explainability, reliability, privacy, and the alignment of AI decisions with human values and ethical standards.

5 Salient Points

  • Transparency and Explainability: AI systems in healthcare need to be transparent and provide understandable explanations for their decisions. Users, including both healthcare professionals and patients, must be able to comprehend how AI algorithms arrive at specific conclusions.

  • Reliability and Accuracy: Trust in AI is built upon its reliability and accuracy. AI algorithms must consistently produce correct and dependable results to gain the confidence of healthcare providers and patients. Rigorous testing and validation processes are essential.

  • Ethical Considerations: Ethical guidelines and principles must underpin AI applications in healthcare. Ensuring that AI respects patient privacy, maintains confidentiality, and aligns with established ethical standards is crucial for fostering trust among stakeholders.

  • Human-AI Collaboration: Trust can be enhanced by promoting collaboration between AI systems and healthcare professionals. AI should augment human decision-making, offering valuable insights and support rather than replacing the expertise of healthcare providers.

  • Accountability and Oversight: Establishing accountability mechanisms is essential. Clear responsibility frameworks, regulations, and oversight ensure that AI developers and users are accountable for the outcomes of AI applications. Regular monitoring and evaluation are necessary to maintain trust over time.

🎯Research Appendix

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