Literature DB >> 33084490

Population health AI researchers' perceptions of the public portrayal of AI: A pilot study.

Gabrielle Samuel, Heilien Diedericks1, Gemma Derrick2.   

Abstract

This article reports how 18 UK and Canadian population health artificial intelligence researchers in Higher Education Institutions perceive the use of artificial intelligence systems in their research, and how this compares with their perceptions about the media portrayal of artificial intelligence systems. This is triangulated with a small scoping analysis of how UK and Canadian news articles portray artificial intelligence systems associated with health research and care. Interviewees had concerns about what they perceived as sensationalist reporting of artificial intelligence systems - a finding reflected in the media analysis. In line with Pickersgill's concept of 'epistemic modesty', they considered artificial intelligence systems better perceived as non-exceptionalist methodological tools that were uncertain and unexciting. Adopting 'epistemic modesty' was sometimes hindered by stakeholders to whom the research is disseminated, who may be less interested in hearing about the uncertainties of scientific practice, having implications on both research and policy.

Entities:  

Keywords:  AI; artificial intelligence; digital data; expectations; health; health technology; hype; interviews; media; newspaper; qualitative research

Mesh:

Year:  2020        PMID: 33084490      PMCID: PMC7859568          DOI: 10.1177/0963662520965490

Source DB:  PubMed          Journal:  Public Underst Sci        ISSN: 0963-6625


  18 in total

1.  Avian flu: the creation of expectations in the interplay between science and the media.

Authors:  Brigitte Nerlich; Christopher Halliday
Journal:  Sociol Health Illn       Date:  2007-01

2.  Can digital data diagnose mental health problems? A sociological exploration of 'digital phenotyping'.

Authors:  Rasmus H Birk; Gabrielle Samuel
Journal:  Sociol Health Illn       Date:  2020-09-11

3.  Deep Ethical Learning: Taking the Interplay of Human and Artificial Intelligence Seriously.

Authors:  Anita Ho
Journal:  Hastings Cent Rep       Date:  2019-01       Impact factor: 2.683

4.  Algorithms for enhancing public health utility of national causes-of-death data.

Authors:  Mohsen Naghavi; Susanna Makela; Kyle Foreman; Janaki O'Brien; Farshad Pourmalek; Rafael Lozano
Journal:  Popul Health Metr       Date:  2010-05-10

5.  Just around the corner: rhetorics of progress and promise in genetic research.

Authors:  Robert Evans; Inna Kotchetkova; Susanne Langer
Journal:  Public Underst Sci       Date:  2009-01

6.  Identifying facial phenotypes of genetic disorders using deep learning.

Authors:  Yaron Gurovich; Yair Hanani; Omri Bar; Guy Nadav; Nicole Fleischer; Dekel Gelbman; Lina Basel-Salmon; Peter M Krawitz; Susanne B Kamphausen; Martin Zenker; Lynne M Bird; Karen W Gripp
Journal:  Nat Med       Date:  2019-01-07       Impact factor: 53.440

7.  Using Twitter to Identify and Respond to Food Poisoning: The Food Safety STL Project.

Authors:  Jenine K Harris; Jared B Hawkins; Leila Nguyen; Elaine O Nsoesie; Gaurav Tuli; Raed Mansour; John S Brownstein
Journal:  J Public Health Manag Pract       Date:  2017 Nov/Dec

8.  The UK's 100,000 Genomes Project: manifesting policymakers' expectations.

Authors:  Gabrielle Natalie Samuel; Bobbie Farsides
Journal:  New Genet Soc       Date:  2017-09-06

9.  UK science press officers, professional vision and the generation of expectations.

Authors:  Gabrielle Samuel; Clare Williams; John Gardner
Journal:  Public Underst Sci       Date:  2016-08-03

10.  Sociology of Low Expectations: Recalibration as Innovation Work in Biomedicine.

Authors:  John Gardner; Gabrielle Samuel; Clare Williams
Journal:  Sci Technol Human Values       Date:  2015-11
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  2 in total

1.  Boundaries Between Research Ethics and Ethical Research Use in Artificial Intelligence Health Research.

Authors:  Gabrielle Samuel; Jenn Chubb; Gemma Derrick
Journal:  J Empir Res Hum Res Ethics       Date:  2021-03-18       Impact factor: 1.742

2.  Expert views about missing AI narratives: is there an AI story crisis?

Authors:  Jennifer Chubb; Darren Reed; Peter Cowling
Journal:  AI Soc       Date:  2022-08-25
  2 in total

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