Medical artificial intelligence is as much social as it is technological

Annamaria Carusi; Peter Winter; Iain  Armstrong; Fabio Ciravegna; David G Kiely; Allan  Lawrie; Haiping Lu; Ian  Sabroe; Andy Swift

doi:10.1038/s42256-022-00603-3

Medical artificial intelligence is as much social as it is technological

Annamaria Carusi, Peter Winter, Iain Armstrong, Fabio Ciravegna, David G Kiely, Allan Lawrie, Haiping Lu, Ian Sabroe, Andy Swift

School of Sociology, Politics and International Studies

Research output: Contribution to journal › Article (Academic Journal) › peer-review

5 Citations (Scopus)

Abstract

Despite the promise of medical artificial intelligence applications, their acceptance in real-world clinical settings is low, with lack of transparency and trust being barriers that need to be overcome. We discuss the importance of the collaborative process in medical artificial intelligence, whereby experts from various fields work together and tackle transparency issues and build trust over time.

Original language	English
Pages (from-to)	98-100
Number of pages	3
Journal	Nature Machine Intelligence
Volume	5
Issue number	2
DOIs	https://doi.org/10.1038/s42256-022-00603-3
Publication status	Published - 26 Jan 2023

Bibliographical note

Funding Information:
We thank J. Anderson for helpful feedback. The research informing this Comment was supported by a Wellcome Grant for the project ‘AI in the Clinic’ (grant number WT/213606).

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title = "Medical artificial intelligence is as much social as it is technological",

abstract = "Despite the promise of medical artificial intelligence applications, their acceptance in real-world clinical settings is low, with lack of transparency and trust being barriers that need to be overcome. We discuss the importance of the collaborative process in medical artificial intelligence, whereby experts from various fields work together and tackle transparency issues and build trust over time.",

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AU - Carusi, Annamaria

AU - Winter, Peter

AU - Armstrong, Iain

AU - Ciravegna, Fabio

AU - Kiely, David G

AU - Lawrie, Allan

AU - Lu, Haiping

AU - Sabroe, Ian

AU - Swift, Andy

N1 - Funding Information: We thank J. Anderson for helpful feedback. The research informing this Comment was supported by a Wellcome Grant for the project ‘AI in the Clinic’ (grant number WT/213606).

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AB - Despite the promise of medical artificial intelligence applications, their acceptance in real-world clinical settings is low, with lack of transparency and trust being barriers that need to be overcome. We discuss the importance of the collaborative process in medical artificial intelligence, whereby experts from various fields work together and tackle transparency issues and build trust over time.

U2 - 10.1038/s42256-022-00603-3

DO - 10.1038/s42256-022-00603-3

M3 - Article (Academic Journal)

VL - 5

SP - 98

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JO - Nature Machine Intelligence

JF - Nature Machine Intelligence

IS - 2

ER -

Medical artificial intelligence is as much social as it is technological

Abstract

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