Cited by 511Artificial Intelligence in Healthcare and EducationEthics and Social Impacts of AIDigitalization, Law, and Regulation

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Google DeepMind and healthcare in an age of algorithms

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Powles, Julia, Hodson, Hal·2017·Health and Technology

DOI 10.1007/s12553-017-0179-1PMC PMC5741783

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Abstract

Data-driven tools and techniques, particularly machine learning methods that underpin artificial intelligence, offer promise in improving healthcare systems and services. One of the companies aspiring to pioneer these advances is DeepMind Technologies Limited, a wholly-owned subsidiary of the Google conglomerate, Alphabet Inc. In 2016, DeepMind announced its first major health project: a collaboration with the Royal Free London NHS Foundation Trust, to assist in the management of acute kidney injury. Initially received with great enthusiasm, the collaboration has suffered from a lack of clarity and openness, with issues of privacy and power emerging as potent challenges as the project has unfolded. Taking the DeepMind-Royal Free case study as its pivot, this article draws a number of lessons on the transfer of population-derived datasets to large private prospectors, identifying critical questions for policy-makers, industry and individuals as healthcare moves into an algorithmic age.

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Authors: Powles, J., & Hodson, H.
Affiliations: University of Cambridge (GB)
Corresponding author: Powles, Julia
ORCID: Powles, Julia
Venue: Health and Technology
Publisher: Springer Science and Business Media LLC
Published: 2017-03-16
Volume: 7
Issue: 4
Pages: 351-367
ISSN: 2190-7188 (ISSN-L)
2190-7196
DOI: 10.1007/s12553-017-0179-1
PMC: PMC5741783
OpenAlex: W2596192549
Cited by: 511
References: 28
Citations by year: 2026: 48 · 2025: 67 · 2024: 61 · 2023: 50 · 2022: 55 · 2021: 78 · 2020: 60 · 2019: 43 · 2018: 41 · 2017: 7
FWCI: 24.04
Type: journal article
Language: en
Open access: hybrid
doi.org
Licence: cc-by
creativecommons.org/licenses/by/4.0 (unspecified)
Locations: Health and Technology (publishedVersion, cc-by)
Europe PMC (PubMed Central) (publishedVersion, cc-by)
PubMed Central (publishedVersion, cc-by)
PubMed (publishedVersion)
Apollo (University of Cambridge) (submittedVersion, cc-by)
Apollo (cc-by)
Funders: University of Cambridge
Topics: Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
Social Sciences › Law › Digitalization, Law, and Regulation
Keywords: DeepMind, acute kidney injury, machine learning in healthcare, artificial intelligence in healthcare, data privacy, power imbalance, health data governance

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