Artificial Intelligence and Human Trust in Healthcare: Focus on Clinicians

Onur Asan; Alparslan Emrah Bayrak; Avishek Choudhury

doi:10.2196/15154

journal article Jun 19, 2020

Artificial Intelligence and Human Trust in Healthcare: Focus on Clinicians

Onur Asan

Alparslan Emrah Bayrak

Avishek Choudhury

Journal of Medical Internet Research Vol. 22 No. 6 pp. e15154 · JMIR Publications Inc.

View at Publisher Save 10.2196/15154

Abstract

Artificial intelligence (AI) can transform health care practices with its increasing ability to translate the uncertainty and complexity in data into actionable—though imperfect—clinical decisions or suggestions. In the evolving relationship between humans and AI, trust is the one mechanism that shapes clinicians’ use and adoption of AI. Trust is a psychological mechanism to deal with the uncertainty between what is known and unknown. Several research studies have highlighted the need for improving AI-based systems and enhancing their capabilities to help clinicians. However, assessing the magnitude and impact of human trust on AI technology demands substantial attention. Will a clinician trust an AI-based system? What are the factors that influence human trust in AI? Can trust in AI be optimized to improve decision-making processes? In this paper, we focus on clinicians as the primary users of AI systems in health care and present factors shaping trust between clinicians and AI. We highlight critical challenges related to trust that should be considered during the development of any AI system for clinical use.

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References

48

[1]

10.1136/svn-2017-000101

[2]

10.14744/anatoljcardiol.2019.28661

[3]

10.1007/s10111-011-0188-1

[4]

Fitts, P Human engineering for an effective air-navigationtraffic-control system. Fitts PM. editor (1951)

[5]

Humans and Automation: Use, Misuse, Disuse, Abuse

Raja Parasuraman, Victor Riley

Human Factors: The Journal of the Human Factors an... 10.1518/001872097778543886

[6]

Siau, K Cutter Business Technology Journal (2018)

[7]

McCarthy, J Some philosophical problems from the standpoint of artificial intelligence (1987)

[8]

10.1001/jama.2018.20563

[9]

10.1038/s41591-018-0316-z

[10]

10.1093/bib/bbx044

[11]

10.1093/cid/cix731

[12]

Trust in Automation: Designing for Appropriate Reliance

John D. Lee, Katrina A. See

Human Factors: The Journal of the Human Factors an... 10.1518/hfes.46.1.50.30392

[13]

An Integrative Model of Organizational Trust

Roger C. Mayer, James H. Davis, F. David Schoorman

The Academy of Management Review 10.2307/258792

[14]

10.1109/access.2013.2259892

[15]

10.1371/journal.pmed.1001940

[16]

Davenport, TH Harv Bus Rev (2002)

[17]

The potential for artificial intelligence in healthcare

Thomas Davenport, Ravi Kalakota

Future Healthcare Journal 10.7861/futurehosp.6-2-94

[18]

10.1016/j.artmed.2004.01.017

[19]

10.1200/cci.19.00079

[20]

10.1016/j.csbj.2019.07.001

[21]

10.1038/s41433-019-0629-2

[22]

10.1201/9780367821654-8

[23]

10.22381/ajmr6220195

[24]

White House American artificial intelligence initiative year one annual report (2020)

[25]

FDA2020-04-01Proposed regulatory framework for modifications to artificial intelligence/machine learning (AI/ML)-based Software as a Medical Device (SaMD)https://www.regulations.gov/document?D=FDA-2019-N-1185-0001

[26]

FDAFood and Drug Administration20172020-04-01What are examples of Software as a Medical Device? : Uhttps://www.fda.gov/medical-devices/software-medical-device-samd/what-are-examples-software-medical-device

[27]

10.31525/fda2-ucm635083.htm

[28]

10.4103/jfmpc.jfmpc_440_19

[29]

DeepMind2020-05-05AlphaStar: Mastering the Real-Time Strategy Game StarCraft IIhttps://deepmind.com/blog/article/alphastar-mastering-real-time-strategy-game-starcraft-ii

[30]

10.5858/arpa.2018-0147-oa

[31]

GoodfellowIShlensJSzegedyCExplaining and harnessing adversarial examples20150507Proceeding of 3rd International Conference on Learning Representations; May ; San Diego2015San Diego79

[32]

10.1146/annurev.psych.59.103006.093629

[33]

10.1109/mis.2013.24

[34]

10.1145/1985347.1985353

[35]

10.1126/science.aaw0029

[36]

10.3390/technologies6030064

[37]

10.1093/ijlit/eaz004

[38]

Dermatologist-level classification of skin cancer with deep neural networks

Andre Esteva, Brett Kuprel, Roberto A. Novoa et al.

Nature 10.1038/nature21056

[39]

10.1038/d41586-018-05707-8

[40]

OfficeIICO20192020-04-04Guide to data protectionhttps://ico.org.uk/media/for-organisations/guide-to-data-protection-1-1.pdf

[41]

10.1016/j.clsr.2018.01.004

[42]

10.1145/2090236.2090255

[43]

10.1145/2783258.2783311

[44]

Ferreira, A Springer (2015)

[45]

10.1002/inst.12278

[46]

10.1080/00140139.2013.838643

[47]

FDA2020-05-01Artificial Intelligence and Machine Learning in Software as a Medical Devicehttps://www.fda.gov/medical-devices/software-medical-device-samd/artificial-intelligence-and-machine-learning-software-medical-devicefiles/7614/artificial-intelligence-and-machine-learning-software-medical-device.html

[48]

Potential Liability for Physicians Using Artificial Intelligence

W. Nicholson Price, Sara Gerke, I. Glenn Cohen

JAMA 10.1001/jama.2019.15064

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Metrics

648

Citations

48

References

Details

Published: Jun 19, 2020
Vol/Issue: 22(6)
Pages: e15154

Authors

O

Onur Asan

A

Alparslan Emrah Bayrak

A

Avishek Choudhury

Cite This Article

Onur Asan, Alparslan Emrah Bayrak, Avishek Choudhury (2020). Artificial Intelligence and Human Trust in Healthcare: Focus on Clinicians. Journal of Medical Internet Research, 22(6), e15154. https://doi.org/10.2196/15154

Artificial Intelligence and Human Trust in Healthcare: Focus on Clinicians

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