Work

Human–algorithm hybrids as (quasi‐)organizations? On the accountability of digital collective actors

Year: 2023

Type: article

Abstract: Models of individual accountability for algorithms’ actions fail when a human–algorithm association comes to be viewed as a collective actor. In some situations, human and algorithmic actions are so closely intertwined that there is no longer a linear connection between the emergent collectivity and the complex interactions of humans and algorithms. In such collective decision‐making sequences, individual accountability can no longer be attributed. Therefore, a new perspective on human–algorithm associations that captures their emergent properties and organizational qualities is needed to develop appropriate models of collective accountability. This article seeks to answer a number of questions. How can the encounter between humans and algorithms within such a socio‐technical configuration be adequately theorized? Can the configuration itself be understood as a hybrid collectivity? Can actions be attributed to the configuration as a personified collective actor? How will accountability be institutionalized for human–algorithm associations – in centralized or distributed collective forms?

Source: Journal of Law and Society

DOI: 10.1111/jols.12412

Authors: ANNA BECKERS, GUNTHER TEUBNER

Institutions: Maastricht University, Goethe University Frankfurt

Language: English

Topic: Ethics and Social Impacts of AI

Subfield: Safety Research

Field: Social Sciences

Domain: Social Sciences

SDG: Peace, justice, and strong institutions

Open Access status: hybrid

Estimated APC paid: $2,880