Can We Trust AI to Make Decisions?

The article focuses on the evolution of decision-making in artificial intelligence (AI), particularly the shift from traditional rule-based systems to data-driven machine learning algorithms. It explores the advantages and limitations of data-driven AI, highlighting concerns about its potential to s...

Descripción completa

Detalles Bibliográficos
Publicado en:Skeptic Vol. 29; no. 1; pp. 24 - 28
Autores principales: GASSER, URS, MAYER-SCHÖNBERGER, VIKTOR
Formato: Artículo
Publicado: Skeptics Society 2024
Materias:
Acceso en línea:Ver este registro en EBSCOhost
fields @attributes:
  recordID: 1
pdfLink:
plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=175510877&site=ehost-live
header:
  @attributes:
    shortDbName: hlh
    uiTerm: 175510877
    longDbName: Humanities International Complete
    uiTag: AN
  controlInfo:
    bkinfo:
    jinfo:
      jid:
        10639330
        SKP
      jtl: Skeptic
      issn: 10639330
      maglogo: N
    pubinfo:
      dt: 2024
      vid: 29
      iid: 1
      pid: 2484
      pub: Skeptics Society
    artinfo:
      ui: 175510877
      ppf: 24
      ppct: 4
      formats:
        fmt:
          @attributes:
            type: P
            size: 2.9MB
      tig:
        atl: Can We Trust AI to Make Decisions?
      aug:
        au:
          GASSER, URS
          MAYER-SCHÖNBERGER, VIKTOR
      su:
        Artificial intelligence
        Decision making
        Machine learning
        Algorithms
        Experiments
      sug:
        subj:
          Artificial intelligence
          Decision making
          Machine learning
          Algorithms
          Experiments
      ab: The article focuses on the evolution of decision-making in artificial intelligence (AI), particularly the shift from traditional rule-based systems to data-driven machine learning algorithms. It explores the advantages and limitations of data-driven AI, highlighting concerns about its potential to stifle innovation and adaptability by favoring consistency over experimentation.
      pubtype: Periodical
      doctype: Article
      src: R
    language: English
    refInfo:
    copyright:
      @attributes:
        flag: Y
      custom: Copyright of Skeptic is the property of Skeptics Society and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use.
      item: Skeptic
      holder: Skeptics Society
      dt:
        @attributes:
          year: 2024
    holdings:
      @attributes:
        islocal: N