AI Article Synopsis
- The review explored racial and ethnic bias in artificial intelligence health algorithms (AIHA) and their impact on health equity, following PRISMA-ScR guidelines while analyzing 23 sources from 2020 to 2024.
- It highlighted the need for stakeholder involvement in oversight and governance to address challenges related to patient privacy and data security.
- Despite advancements in diagnostic accuracy, the review concluded that AIHA may contribute to existing health disparities, emphasizing the need for global considerations in health equity.
Article Abstract
This scoping review examined racial and ethnic bias in artificial intelligence health algorithms (AIHA), the role of stakeholders in oversight, and the consequences of AIHA for health equity. Using the PRISMA-ScR guidelines, databases were searched between 2020 and 2024 using the terms racial and ethnic bias in health algorithms resulting in a final sample of 23 sources. Suggestions for how to mitigate algorithmic bias were compiled and evaluated, roles played by stakeholders were identified, and governance and stewardship plans for AIHA were examined. While AIHA represent a significant breakthrough in predictive analytics and treatment optimization, regularly outperforming humans in diagnostic precision and accuracy, they also present serious challenges to patient privacy, data security, institutional transparency, and health equity. Evidence from extant sources including those in this review showed that AIHA carry the potential to perpetuate health inequities. While the current study considered AIHA in the US, the use of AIHA carries implications for global health equity.
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| http://dx.doi.org/10.1080/13557858.2024.2422848 | DOI Listing |
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