Big Health Data Research and Group Harm: The Scope of IRB Review

ABSTRACT Much of precision medicine is driven by big health data research—the analysis of massive datasets representing the complex web of genetic, behavioral, environmental, and other factors that impact human well‐being. There are some who point to the Common Rule, the regulation governing federal...

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Bibliographic Details
Published inEthics & human research Vol. 44; no. 4; pp. 34 - 38
Main Authors Doerr, Megan, Meeder, Sara
Format Journal Article
LanguageEnglish
Published 01.07.2022
Subjects
artificial intelligence
big data
big health data
Common Rule
group harm
human research ethics
human subjects research
institutional review board (IRB)
machine learning
research risks
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Summary:ABSTRACT Much of precision medicine is driven by big health data research—the analysis of massive datasets representing the complex web of genetic, behavioral, environmental, and other factors that impact human well‐being. There are some who point to the Common Rule, the regulation governing federally funded human subjects research, as a regulatory panacea for all types of big health data research. But how well does the Common Rule fit the regulatory needs of this type of research? This article suggests that harms that may arise from artificial intelligence and machine‐learning technologies used in big health data research—and the increased likelihood that this research will affect public policy—mean it is time to consider whether the current human research regulations prohibit comprehensive, ethical review of big health data research that may result in group harm.
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ISSN:2578-2355
2578-2363
2578-2363
DOI:10.1002/eahr.500130