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      Contextualizing the ethics of algorithms: A socio-professional approach

      1 , 2 , 3
      New Media & Society
      SAGE Publications

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          Abstract

          Research on AI ethics tends to examine the subject through philosophical, legal, or technical perspectives, largely neglecting the sociocultural one. This literature also predominantly focuses on Europe and the United States. Addressing these gaps, this article explores how data scientists justify and explain the ethics of their algorithmic work. Based on a pragmatist social analysis, and of 60 semi-structured interviews with Israeli data scientists, we ask: how do data scientists understand, interpret, and depict algorithmic ethics? And what ideologies, discourses, and worldviews shape algorithmic ethics? Our findings point to three dominant moral logics: (1) ethics as a personal endeavor; (2) ethics as hindering progress; and (3) ethics as a commodity. We show that while data science is a nascent profession, these moral logics originate from the techno-libertarian culture of its parent profession—engineering. Finally, we discuss the potential of these moral logics to mature into a more formal, agreed-upon moral regime.

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          Using thematic analysis in psychology

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            The global landscape of AI ethics guidelines

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              Culture in Action: Symbols and Strategies

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                Author and article information

                Contributors
                Journal
                New Media & Society
                New Media & Society
                SAGE Publications
                1461-4448
                1461-7315
                October 2024
                January 05 2023
                October 2024
                : 26
                : 10
                : 5962-5982
                Affiliations
                [1 ]Tel Aviv University, Israel
                [2 ]University of Haifa, Israel
                [3 ]Ben-Gurion University of the Negev, Israel; Reichman University, Israel
                Article
                10.1177/14614448221145728
                59a0e8bd-d041-4626-9769-08f55944f931
                © 2024

                https://creativecommons.org/licenses/by-nc/4.0/

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