A Practical Approach Towards Ethical A.I. Implementation in the Healthcare Community.

The application of Artificial Intelligence (AI) enabled tools is growing rapidly. These systems are being used to support complex decisions that can add value to society. In healthcare settings, AI assists in detecting, predicting, and monitoring health status, conditions, and behavior and assists i...

Descripción completa

Detalles Bibliográficos
Publicado en:Journal of Hospital Ethics Vol. 10; no. 3; pp. 189 - 201
Autores principales: Jarrett, Lindsey, Pjecha, Matthew, Carter, Brian, Wyckoff, Gerald, Hoffman, Mark
Formato: tables/charts Journal Article
Publicado: MedStar Washington Hospital Center, Center for Ethics Dec2024
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=182338723&site=ehost-live
header:
  @attributes:
    shortDbName: ccm
    uiTerm: 182338723
    longDbName: CINAHL Complete
    uiTag: AN
  controlInfo:
    bkinfo:
    dissinfo:
    jinfo:
      jid:
        19384955
        FNKI
      jtl: Journal of Hospital Ethics
      issn: 19384955
      maglogo: N
    pubinfo:
      dt: Dec2024
      vid: 10
      iid: 3
      pid: 82867
      pub: MedStar Washington Hospital Center, Center for Ethics
      place: Washington, District of Columbia
    artinfo:
      ui:
        182338723
        182338723
        182338723
        182338723
      ppf: 189
      ppct: 12
      formats:
        fmt:
          @attributes:
            type: P
      tig:
        atl: A Practical Approach Towards Ethical A.I. Implementation in the Healthcare Community.
      aug:
        au:
          Jarrett, Lindsey
          Pjecha, Matthew
          Carter, Brian
          Wyckoff, Gerald
          Hoffman, Mark
      sug:
        subj:
          Artificial Intelligence Ethical Issues
          Community Health Services
          Program Implementation
          Information Technology
          Ethics, Organizational
          Health Status
          Health Care Delivery
      ab: The application of Artificial Intelligence (AI) enabled tools is growing rapidly. These systems are being used to support complex decisions that can add value to society. In healthcare settings, AI assists in detecting, predicting, and monitoring health status, conditions, and behavior and assists in processes related to direct healthcare delivery. Amidst excitement, there is also growing concern around how AI can pose significant potential risk and harm across healthcare systems. How ought organizations, regulators, software vendors, and individual practitioners respond to these risks while still utilizing and appreciating the benefits of these technologies? This is the key ethical problem addressed by this paper. A solution is urgently needed in the AI space because practitioners and healthcare leaders are determined to realize the benefits and efficiencies of these technologies right now. Yet, standard processes that ensure human touchpoints, thoughtful consideration, and application of ethical principles to algorithm utilization are often underutilized or completely absent. This paper outlines an approach that brings communities together across healthcare IT, academia, ethics, and community advocacy to establish common foundations, articulate a framework for considering AI-enabled technologies, and train developers and purchasers of AI-enabled technologies to reflect on the ethical dimensions of these capabilities more thoroughly. We propose that a process and standards to guide the application of ethical considerations will offer guardrails in the use of this technology, heighten beneficence and nonmaleficence, introduce much-needed respect for autonomy, and enable paths for justice, especially among patients and families who will be most impacted by the inaccurate, inconclusive, or biased results.
      pubtype: Academic Journal
      doctype:
        tables/charts
        Journal Article
      ougenre: Article
    language: English
    refInfo:
    holdings:
      @attributes:
        islocal: N