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Title: | Unmasking inequalities of the code: Disentangling the nexus of AI and inequality |
Authors: | Bircan, T Özbilgin, MF |
Keywords: | artificial intelligence;social realism;inequality;digital divide;algorithmic bias;privacy and surveillance |
Issue Date: | 2-Dec-2024 |
Publisher: | Elsevier |
Citation: | Bircan, T. and Özbilgin, M.F. (2025) 'Unmasking inequalities of the code: Disentangling the nexus of AI and inequality', Technological Forecasting and Social Change, 211 (February 2025), 123925, pp. 1 - 11. doi: 10.1016/j.techfore.2024.123925. |
Abstract: | This article provides an interdisciplinary exploration of the complex dynamics between artificial intelligence (AI) and inequality, drawing upon social sciences and technology studies. It scrutinises the power dynamics that shape the development, deployment, and utilisation of AI technologies, and how these dynamics influence access to and control over AI resources. To do so, we employ Margaret Archer's social realism framework to illuminate the ways in which AI systems can reinforce various forms of inequalities. This theoretical perspective underscores the dynamic interplay between social context, individual agency, and the processes of morphostasis and morphogenesis, offering a nuanced understanding of how inequalities are reproduced and potentially transformed within the AI context. We further discuss the challenges posed by the access and opportunity divide, privacy and surveillance concerns, and the digital divide in the context of AI. We propose co-ownership as a potential solution to economic inequalities induced by AI, suggesting that stakeholders contributing to AI development should have significant claims of ownership. We also advocate for the recognition of AI systems as legal entities, which could provide a mechanism for accountability and compensation in cases of privacy breaches. Finally, we conclude by emphasising the need for robust data governance frameworks, global governance, and a commitment to social justice in navigating the complex landscape of AI and inequality. |
Description: | Data availability: No data was used for the research described in the article. |
URI: | https://bura.brunel.ac.uk/handle/2438/30305 |
DOI: | https://doi.org/10.1016/j.techfore.2024.123925 |
ISSN: | 0040-1625 |
Other Identifiers: | ORCiD: Mustafa F. Özbilgin https://orcid.org/0000-0002-8672-9534 123925 |
Appears in Collections: | Brunel Business School Embargoed Research Papers |
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