Abstract
Objectives
Fairness is a core concept meant to grapple with different forms of
discrimination and bias that emerge with advances in Artificial
Intelligence (eg, machine learning, ML). Yet, claims to fairness in ML
discourses are often vague and contradictory. The response to these
issues within the scientific community has been technocratic. Studies
either measure (mathematically) competing definitions of fairness,
and/or recommend a range of governance tools (eg, fairness checklists or
guiding principles). To advance efforts to operationalise fairness in
medicine, we synthesised a broad range of literature.
Methods
We conducted an environmental scan of English language literature on
fairness from 1960-July 31, 2021. Electronic databases Medline, PubMed
and Google Scholar were searched, supplemented by additional hand
searches. Data from 213 selected publications were analysed using rapid
framework analysis. Search and analysis were completed in two rounds: to
explore previously identified issues (a priori), as well as those
emerging from the analysis (de novo).
Results
Our synthesis identified ‘Three Pillars for Fairness’: transparency,
impartiality and inclusion. We draw on these insights to propose a
multidimensional conceptual framework to guide empirical research on the
operationalisation of fairness in healthcare.
Discussion
We apply the conceptual framework generated by our synthesis to risk
assessment in psychiatry as a case study. We argue that any claim to
fairness must reflect critical assessment and ongoing social and
political deliberation around these three pillars with a range of
stakeholders, including patients.
Conclusion
We conclude by outlining areas for further research that would
bolster ongoing commitments to fairness and health equity in
healthcare.
Funder
Social
Sciences and Humanities Research Council of
Canada
Dalla Lana School of Public Health
Interdisciplinary Data Science Seed Funding
Canadian
Institutes of Health Research
AMS Fellowship in Compassion and
Artificial Intelligence
Subject
Health Information Management,Health Informatics,Computer Science Applications
Cited by
20 articles.
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