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Deep automation of inequality as a self-sustaining and self-fulfilling process: The example of binarism and sexism

Year: 2024

Type: article

Abstract: Datafication is simultaneously becoming a means and a goal of modern marketdriven uses of technologies. The optimisation of the “consumer experience” shapes a data-driven consumer subject, which does not encompass all practices and identities. The article aims to problematise datafication, which overlooks complex “citizen experiences” that also include gender and sexual identity. At the same time, former and existing gender inequalities remain fundamental learning data, based on which algorithms and artificial intelligence generate models of future sociality. We encounter at least three interconnected types of inequality (on the levels of culture, data and technologies) that can create a self-sustaining and self-learning process that reproduces future inequalities.

Source: DOAJ (DOAJ: Directory of Open Access Journals)

Author: Tadej Praprotnik

Institution: University of Primorska

Language: English

Topic: Ethics and Social Impacts of AI

Subfield: Safety Research

Field: Social Sciences

Domain: Social Sciences

SDGs: Reduced inequalities, Gender equality

Open Access status: green

OpenAlex ID: W7090061432

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