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AI as financial infrastructure?

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  • Paraná, Edemilson

Abstract

From an ‘infrastructural gaze,’ this chapter examines the penetration of artificial intelligence in capital markets as a blend of continuity and change in finance. The growing infrastructural dimension of AI stems firstly from the evolution of algorithmic trading and governance, and secondly from its rise as a ‘general-purpose technology’ within the financial domain. The text discusses the consequences of this ‘infrastructuralisation’ of financial AI, considering the micro-macro tension typical of capital accumulation and crisis dynamics. Challenging the commonly held notion of AI as a stabilising force, the analysis underscores its connections with volatile, crisis-prone financialised dynamics. It concludes by outlining potential consequences (unpredictability, operational inefficiency, complexity, further concentration) and (systemic) risks arising from the emergence of AI as a ‘new’ financial infrastructure, particularly those related to biases in data and data commodification, lack of transparency in underlying models, algorithmic collusion, and network effects. The text asserts that a thorough understanding of these hazards can be achieved by adopting a perspective that considers the macro-meso-micro connections inherent in infrastructures.

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  • Paraná, Edemilson, 2024. "AI as financial infrastructure?," SocArXiv ub92z, Center for Open Science.
  • Handle: RePEc:osf:socarx:ub92z
    DOI: 10.31219/osf.io/ub92z
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    References listed on IDEAS

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    1. Tomás N. Rotta & Edemilson Paraná, 2022. "Bitcoin as a digital commodity," New Political Economy, Taylor & Francis Journals, vol. 27(6), pages 1046-1061, November.
    2. Nick Bernards & Malcolm Campbell-Verduyn, 2019. "Understanding technological change in global finance through infrastructures," Review of International Political Economy, Taylor & Francis Journals, vol. 26(5), pages 773-789, September.
    3. Bracke, Philippe & Datta, Anupam & Jung, Carsten & Sen, Shayak, 2019. "Machine learning explainability in finance: an application to default risk analysis," Bank of England working papers 816, Bank of England.
    4. Cecilia Rikap & Bengt-Åke Lundvall, 2022. "Big tech, knowledge predation and the implications for development," Innovation and Development, Taylor & Francis Journals, vol. 12(3), pages 389-416, September.
    5. Dowling, Michael & Lucey, Brian, 2023. "ChatGPT for (Finance) research: The Bananarama Conjecture," Finance Research Letters, Elsevier, vol. 53(C).
    6. Borch, Christian, 2022. "Machine learning, knowledge risk, and principal-agent problems in automated trading," Technology in Society, Elsevier, vol. 68(C).
    7. Fabian Muniesa, 2007. "Market technologies and the pragmatics of prices," Post-Print halshs-00160893, HAL.
    8. Maria de Lourdes Rollemberg Mollo & Fernando Fellows Dourado & Edemilson Paraná, 2022. "Financialisation as the development of fictitious capital in developing and developed economies," Cambridge Journal of Economics, Cambridge Political Economy Society, vol. 46(5), pages 955-976.
    9. Jon Danielsson & Andreas Uthemann, 2023. "On the use of artificial intelligence in financial regulations and the impact on financial stability," Papers 2310.11293, arXiv.org, revised Jun 2024.
    10. Malcolm Campbell-Verduyn & Marcel Goguen & Tony Porter, 2017. "Big Data and algorithmic governance: the case of financial practices," New Political Economy, Taylor & Francis Journals, vol. 22(2), pages 219-236, March.
    11. Malcolm Campbell-Verduyn & Marc Lenglet, 2023. "Imaginary failure: RegTech in finance," New Political Economy, Taylor & Francis Journals, vol. 28(3), pages 468-482, May.
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