The influence of artificial intelligence within health-related risk work: a critical framework and lines of empirical inquiry.
In this editorial we highlight the need for empirical studies into the growing use of artificial intelligence (AI) technology in healthcare and social work settings, especially studies which are theoretically informed by critical social science studies of risk and uncertainty. In setting out the imp...
| Publicado en: | Health, Risk & Society Vol. 26; no. 7/8; pp. 301 - 317 |
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| Autores principales: | , |
| Formato: | editorial review Journal Article |
| Publicado: |
Taylor & Francis Ltd
Oct/Nov2024
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=180554618&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 180554618 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 13698575 35X jtl: Health, Risk & Society issn: 13698575 maglogo: N pubinfo: dt: Oct/Nov2024 vid: 26 iid: 7/8 pid: 377 pub: Taylor & Francis Ltd place: Philadelphia, Pennsylvania artinfo: ui: 180554618 180247096 180554618 180554618 10.1080/13698575.2024.2412374 180554618 ppf: 301 ppct: 16 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: The influence of artificial intelligence within health-related risk work: a critical framework and lines of empirical inquiry. aug: au: Brown, Patrick van Voorst, Roanne affil: AISSR, University of Amsterdam, The Netherlands sug: subj: Artificial Intelligence Utilization Technology, Medical Social Work Health Services Empirical Research Algorithms Machine Learning Decision Making Risk Assessment Culture Economics ab: In this editorial we highlight the need for empirical studies into the growing use of artificial intelligence (AI) technology in healthcare and social work settings, especially studies which are theoretically informed by critical social science studies of risk and uncertainty. In setting out the importance of interpretative and critical traditions for research into such AI-oriented forms of risk work, we propose three important conceptual lines of inquiry which empirical studies might follow. First, we sketch ways in which the enactment of AI in healthcare work may be changing how risk is handled amid professional decision-making, and creating new categories of patient/service-user. Patients may be evaluated as being at lower or higher risk depending, respectively, upon their engagement or non-engagement with AI-technologies. These questions of (non-)engagement lead us to consider, second, the trust and distrust dynamics around AI-technologies, exploring the potential inequalities that can emerge as a result of (non) engagement. We then consider drivers of this technological embrace in terms of hope and magical thinking in technological-imaginaries, connecting these cultural tendencies to broader structures of ideology and political-economic interests. We conclude this editorial with a plea to social scientists to be cautious to avoid both techno-optimistic narratives and alarmist warnings regarding the implications of artificial intelligence (AI). Instead, we argue that our focus should be a theoretically informed and detailed examining of how expectations (pertaining to risk, trust, and hope) materialise in practice, particularly in the daily experiences of those who develop and enact AI technologies in care settings. pubtype: Academic Journal doctype: editorial review Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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