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A normative framework for artificial intelligence as a sociotechnical system in healthcare

Melissa D. McCradden, Shalmali Joshi, James A. Anderson, Alex John London

2023Patterns30 citationsDOIOpen Access PDF

Abstract

Artificial intelligence (AI) tools are of great interest to healthcare organizations for their potential to improve patient care, yet their translation into clinical settings remains inconsistent. One of the reasons for this gap is that good technical performance does not inevitably result in patient benefit. We advocate for a conceptual shift wherein AI tools are seen as components of an intervention ensemble. The intervention ensemble describes the constellation of practices that, together, bring about benefit to patients or health systems. Shifting from a narrow focus on the tool itself toward the intervention ensemble prioritizes a "sociotechnical" vision for translation of AI that values all components of use that support beneficial patient outcomes. The intervention ensemble approach can be used for regulation, institutional oversight, and for AI adopters to responsibly and ethically appraise, evaluate, and use AI tools.

Topics & Concepts

Sociotechnical systemNormativeIntervention (counseling)Health careArtificial intelligenceKnowledge managementComputer sciencePsychologyConceptual frameworkHealthcare systemManagement scienceRisk analysis (engineering)MedicineEngineeringSociologyPolitical sciencePsychiatrySocial scienceLawArtificial Intelligence in Healthcare and EducationEthics in Clinical ResearchHealthcare cost, quality, practices
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