The DeepMind debacle demands dialogue on data
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The UK National Health Service shared data of 1.6 million patients.
“the UK National Health Service shared data of 1.6 million patients”
From The growing ubiquity of algorithms in society: implications, impacts and innovations (2018) · cites this paper as [25]
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Cited by 25
- Authors
- Shah, H.
- Affiliations
- Royal Statistical Society (GB)
- Corresponding author
- Shah, Hetan
- ORCID
- Shah, Hetan
- Venue
- Nature
- Published
- 2017-07-20
- Volume
- 547
- Issue
- 7663
- Pages
- 259-259
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- OpenAlex
- W2738951031
- Cited by
- 25
- References
- 0
- Citations by year
- 2024: 5 · 2023: 1 · 2022: 1 · 2021: 7 · 2020: 3 · 2019: 1 · 2018: 7
- FWCI
- 6.90
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Social Sciences › Law › Digitalization, Law, and Regulation
- Keywords
- DeepMind, patient information, data privacy, government accountability, data misuse, health data protection
- MeSH terms
- Clinical Decision-Making, Mitochondrial Replacement Therapy, Algorithms, Female, United Kingdom, Humans, Informed Consent, Male, Public Opinion, Privacy, Information Dissemination, Trust, Acute Kidney Injury
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