Hochfrequenzhandel

Gresser, Uwe

doi:10.1007/978-3-658-19911-1

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2018

DOI: 10.1007/978-3-658-19911-1

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Hochfrequenzhandel

Uwe Gresser¹

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

Besio,

Fedtke,

Grothe‐Hammer

et al. 2024

Syst Res Behav Sci

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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.

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

Besio,

Fedtke,

Grothe‐Hammer

et al. 2024

Syst Res Behav Sci

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Verantwortungsvolle Maschinen ohne Verantwortlichkeit? Datenintensive Algorithmen in Organisationen

et al. 2021

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Zusammenfassung Die Frage der Verschiebung von Verantwortung, die durch den vermehrten Einsatz von datenintensiven Algorithmen verursacht wird, beschäftigt seit einigen Jahren die sozialwissenschaftliche Forschung. Dabei geht es vor allem darum, welche Personen oder Instanzen dafür verantwortlich sein sollen, wenn sich Entscheidungen als diskriminierend, sachlich falsch oder ungerecht herausstellen. Aus soziologischer Perspektive fällt auf, dass in diesen Debatten nicht trennscharf zwischen Verantwortung und Verantwortlichkeit unterschieden wird. In unserem Beitrag greifen wir diese Unterscheidung so wie sie von Niklas Luhmann formuliert wurde auf, um Veränderungen und Kontinuitäten des Organisierens zu analysieren, die mit dem Einsatz datenintensiver Algorithmen verbunden sind. Wir zeigen, dass Algorithmen in organisationalen Entscheidungsprozessen Unsicherheit absorbieren und somit durchaus Verantwortung übernehmen, aber nicht für Fehler verantwortlich gemacht werden können. Durch den Einsatz von Algorithmen wird Verantwortung in Assemblagen von Personen und Technik zerlegt, während die Zuschreibung von Verantwortlichkeit hochgradig kontrovers wird. Daraus entstehen neue Diskrepanzen zwischen Verantwortung und Verantwortlichkeit, die insbesondere für das organisationsinterne Vertrauen und die Innovationsfähigkeit von Organisationen folgenreich sein können.

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Hochfrequenzhandel

Cited by 2 publications

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

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

Verantwortungsvolle Maschinen ohne Verantwortlichkeit? Datenintensive Algorithmen in Organisationen

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