Algorithmic responsibility without accountability: Understanding data‐intensive algorithms and decisions in organisations.

Social science research has been concerned for several years with the issue of shifting responsibilities in organisations due to the increased use of data‐intensive algorithms. Much of the research to date has focused on the question of who should be held accountable when 'algorithmic decisions' tur...

Descripción completa

Detalles Bibliográficos
Publicado en:Systems Research & Behavioral Science Vol. 42; no. 3; pp. 739 - 756
Autores principales: Besio, Cristina, Fedtke, Cornelia, Grothe‐Hammer, Michael, Karafillidis, Athanasios, Pronzini, Andrea
Formato: Artículo
Publicado: Wiley-Blackwell May/Jun2025
Materias:
Acceso en línea:Ver este registro en EBSCOhost
fields @attributes:
  recordID: 1
pdfLink:
plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=185257090&site=ehost-live
header:
  @attributes:
    shortDbName: ssf
    uiTerm: 185257090
    longDbName: Social Sciences Full Text (H.W. Wilson)
    uiTag: AN
  controlInfo:
    bkinfo:
    jinfo:
      jid:
        10927026
        2SN
      jtl: Systems Research & Behavioral Science
      issn: 10927026
      maglogo: Y
    pubinfo:
      dt: May/Jun2025
      vid: 42
      iid: 3
      pid: 480
      pub: Wiley-Blackwell
    artinfo:
      ui:
        185257090
        10.1002/sres.3028
      ppf: 739
      ppct: 17
      formats:
      tig:
        atl: Algorithmic responsibility without accountability: Understanding data‐intensive algorithms and decisions in organisations.
      aug:
        au:
          Besio, Cristina
          Fedtke, Cornelia
          Grothe‐Hammer, Michael
          Karafillidis, Athanasios
          Pronzini, Andrea
        affil:
          Institute of Social Sciences, Helmut Schmidt University Hamburg, Hamburg, Germany
          Department of Sociology and Political Science, Norwegian University of Science and Technology, Trondheim, Norway
          Evangelische Bank Institut für Ethisches Management, CVJM‐Hochschule, Kassel, Germany
          Centro Formazione di Polizia, Giubiasco, Switzerland
      su:
        Diffusion of innovations
        Responsibility
        Uncertainty
        Decision making
        Group decision making
        Trust
        Algorithms
      sug:
        subj:
          Diffusion of innovations
          Responsibility
          Uncertainty
          Decision making
          Group decision making
          Trust
          Algorithms
      keyword:
        accountability and responsibility
        algorithmic accountability
        algorithmic decisions
        Niklas Luhmann
        organisation theory
        accountability and responsibility
        algorithmic accountability
        algorithmic decisions
        Niklas Luhmann
        organisation theory
      ab: Social science research has been concerned for several years with the issue of shifting responsibilities in organisations due to the increased use of data‐intensive algorithms. Much of the research to date has focused on the question of who should be held accountable when 'algorithmic decisions' turn out to be discriminatory, erroneous or unfair. From a sociological perspective, it is striking that these debates do not make a clear distinction between responsibility and accountability. In our paper, we draw on this distinction as proposed by the German social systems theorist Niklas Luhmann. We use it to analyse the changes and continuities in organisations related to the use of data‐intensive algorithms. We argue that algorithms absorb uncertainty in organisational decision‐making and thus can indeed take responsibility but cannot be made accountable for errors. By using algorithms, responsibility is fragmented across people and technology, while assigning accountability becomes highly controversial. This creates new discrepancies between responsibility and accountability, which can be especially consequential for organisations' internal trust and innovation capacities.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
    refInfo:
    copyright:
      @attributes:
        flag: N
    holdings:
      @attributes:
        islocal: N