Addressing racial and ethnic inequities in data-driven health technologies.
by O’Brien, N; Van Dael, J; Clarke, J; Gardner, C; O’Shaughnessy, J; Darzi, A; Ghafur, S.Imperial College London. Institute of Global Health Innovation (IGHI).
Publisher: Imperial College, London ; 2022.Description: 52p.Summary: This report highlights the opportunities and barriers for artificial intelligence to improve the health of the UK’s minority ethnic groups. Data-driven technologies like artificial intelligence (AI) are powerful tools demonstrating potential in the diagnosis and treatment of diseases such as skin cancer. Yet these could inadvertently worsen the health inequalities experienced by minority ethnic groups if current challenges such as biased algorithms, poor data collection and a lack of diversity in research and development are not urgently addressed. The report calls for further research and transparent discussion on the creation and use of these technologies in health care..Subject(s): artificial intelligence | digital health | health technology | health improvement | Black & ethnic minorities | clinical diagnosis | medical treatment | data collection | health inequalities | algorithms | evaluationDigital copyAvailability: Online access | Online access Note: ; Associated press release. List(s) this item appears in: Technology in health and social care [October 2023]
| Item type | Current library | Collection | Call number | Status | Date due | Barcode |
|---|---|---|---|---|---|---|
| Web publication | The King's Fund Library Online resource | Web publications and sites | Web publications (Browse shelf(Opens below)) | Not for loan |
This report highlights the opportunities and barriers for artificial intelligence to improve the health of the UK’s minority ethnic groups. Data-driven technologies like artificial intelligence (AI) are powerful tools demonstrating potential in the diagnosis and treatment of diseases such as skin cancer. Yet these could inadvertently worsen the health inequalities experienced by minority ethnic groups if current challenges such as biased algorithms, poor data collection and a lack of diversity in research and development are not urgently addressed. The report calls for further research and transparent discussion on the creation and use of these technologies in health care.
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