In my reading so far, some academics view AI capitalism as an opportunity for innovation and growth with responsible practices, while others raise profound concerns about its alignment with capitalist interests, potential harms on labour and society, and the need for robust governance to address ethical and societal challenges posed by AI commercialisation. The discourse underscores a complex interplay between technological advancement, economic systems, and ethical considerations within the AI landscape. I have summarised the articles and chapters I have read thus far below.
Bundy, A. and Clutterbuck, R. (1985) ‘Raising the Standard of AI Products’, Proceedings of the Ninth International Joint Conference on Artificial Intelligence – 1985. Available at: https://www.research.ed.ac.uk/en/publications/raising-the-standard-of-ai-products.
Bundy and Clutterbuck generally support AI capitalism but emphasize responsible practices. They argue for establishing a professional association to uphold high standards and ensure transparency in AI products, promoting trust and sustainability in the industry.
De Gregorio, G. (2023) ‘The Normative Power of Artificial Intelligence’, Indiana Journal of Global Legal Studies, 30(2), pp. 55-80. Available at: https://muse-jhu-edu.eux.idm.oclc.org/pub/3/article/916451.
De Gregorio questions the normative power and impact of AI systems on fundamental rights and the rule of law, suggesting that AI’s pervasive integration challenges traditional legal frameworks, raising concerns about the boundaries of the rule of law in an increasingly algorithmic society.
Dignum, V. (2019) ‘Ensuring Responsible AI in Practice’ in B. O’Sullivan and M. Wooldridge (eds.) Responsible Artificial Intelligence: How to Develop and Use AI in a Responsible Way. Cham, Switzerland: Springer.
Dignum underscores the importance of governance frameworks to ensure accountability for AI’s societal impacts. The chapter advocates for regulations, certification processes, and a shift towards responsible AI development prioritizing transparency, human values, and inclusive participation.
Dixon-Román, E. and Parisi, L. (2020) ‘Data capitalism and the counter futures of ethics in artificial intelligence’, Communication and the Public, 5(3-4), pp. 116-121. Available at: https://doi-org.eux.idm.oclc.org/10.1177/2057047320972029.
Dixon-Román and Parisi critique the prevailing discourse on technological determinism within predictive intelligence, arguing that AI’s intersection with capitalist structures raises complex ethical and sociopolitical issues requiring nuanced examination.
Engster, F. and Moore, P. V. (2020) ‘The search for (artificial) intelligence, in capitalism’, Capital & Class, 44(2), pp. 201-218. Available at: https://doi-org.eux.idm.oclc.org/10.1177/0309816820902055.
Moore, P. V. (2020) ‘The mirror for (artificial) intelligence in capitalism’, Capital & Class, 44(2), pp. 191-200. Available at: https://doi-org.eux.idm.oclc.org/10.1177/0309816820902040.
Engster and Moore (2020) and Moore (2020) take critical stances against AI capitalism/commercialization. They critique the alignment of AI with capitalist interests and raise concerns about its implications on labor, societal structures, and agency within a capitalist framework.
Slee, T. (2020) ‘The Incompatible Incentives of Private-Sector AI’ in M. D. Dubber (ed.) The Oxford Handbook of Ethics of AI. New York, NY: Oxford University Press. Available at: https://doi.org/10.1093/oxfordhb/9780190067397.013.6.
Slee criticizes the dominant role of major tech companies in private-sector AI, emphasizing the need for external governance to mitigate potential harms stemming from profit-driven AI commercialization.
Smith, Y. (2023) ‘Artificial Intelligence: Profit Versus Freedom’, Naked Capitalism, 23 September. Available at: https://www.nakedcapitalism.com/2023/09/artificial-intelligence-profit-versus-freedom.html.
Smith, as summarized by Richard Wolff, takes an anti-AI capitalism stance, highlighting how AI adoption under capitalism prioritizes profits over societal well-being and perpetuates inequalities. Wolff advocates for alternative economic models prioritizing broader societal interests.
Verdegem, P. (2022) ‘Dismantling AI capitalism: the commons as an alternative to the power concentration of Big Tech’, AI & Society, 39, pp.727-737. Available at: https://doi.org/10.1007/s00146-022-01437-8.
Verdegem presents a critical perspective on AI capitalism, highlighting disparities between the optimistic narrative of AI benefiting society and the reality of its commercialization dominated by tech giants. The article advocates reevaluating ownership and governance structures to challenge Big Tech’s dominance, proposing a commons-based framework for more equitable distribution of AI benefits.
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I haven’t yet finished fully reviewing the literature as I’m struggling to find sources which relate directly to my thesis, but I look forward to continuing my research in this area.
Curated using ChatGPT 3.5 by OpenAI. For more information visit chat.openai.com.
