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Artificial Intelligence’s New Clothes? From General Purpose Technology to Large Technical System

Author

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  • Simone Vannuccini

    (Science Policy Research Unit, University of Sussex Business School, University of Sussex)

  • Ekaterina Prytkova

    (Friedrich Schiller University Jena, Department of Economics and Business Administration)

Abstract

Artificial Intelligence (AI) has been quickly labelled a General Purpose Technology (GPT) for its many uses and the high expectations built around a technology that can perform tasks associated with natural intelligence. However, for now, the claim “AI equals GPT" is premature, and eventually, taking into account potential future scenarios, it can turn out to be incorrect. In fact, though every GPT is an influential technology, not every influential technology is a GPT. Checking AI against the definitional criteria of GPT, we come to the conclusion that GPT is a misspecified model of AI: what was meant to be a concept for an individual technology in this case is stretched to cover a growing infrastructural, system technology. For example, the pervasiveness featured in the GPT concept seems to be qualitatively different from the largeness that modern AI demonstrates. In this paper, we suggest an alternative framework drawn from the literature on Large Technical Systems (LTS) as more fit to represent the nature of AI. We map the building blocks of LTS on AI and describe its state-of-the-art through this novel viewpoint. This is a timely exercise, as we witness the formation of an AI industry. A correct understanding of its core technology is needed to identify mechanisms at work, problems in place and eventually the dynamics of this new industry. The LTS framework offers a broader grasp of the infrastructural nature of AI as a technology, with more convenient categories to describe AI and measures to test empirically. We investigate how the implications of AI being an LTS entail the design of adequate public policies and firm strategies.

Suggested Citation

  • Simone Vannuccini & Ekaterina Prytkova, 2021. "Artificial Intelligence’s New Clothes? From General Purpose Technology to Large Technical System," SPRU Working Paper Series 2021-02, SPRU - Science Policy Research Unit, University of Sussex Business School.
  • Handle: RePEc:sru:ssewps:2021-02
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    Cited by:

    1. Bianchini, Stefano & Müller, Moritz & Pelletier, Pierre, 2022. "Artificial intelligence in science: An emerging general method of invention," Research Policy, Elsevier, vol. 51(10).
    2. Igna, Ioana & Venturini, Francesco, 2023. "The determinants of AI innovation across European firms," Research Policy, Elsevier, vol. 52(2).
    3. Ekaterina Prytkova, 2021. "ICT's Wide Web: a System-Level Analysis of ICT's Industrial Diffusion with Algorithmic Links," Jena Economics Research Papers 2021-005, Friedrich-Schiller-University Jena.
    4. Andrea Borsato & André Lorentz, 2023. "Data production and the coevolving AI trajectories: an attempted evolutionary model," Journal of Evolutionary Economics, Springer, vol. 33(5), pages 1427-1472, November.
    5. Stefano Bianchini & Moritz Müller & Pierre Pelletier, 2022. "Artificial intelligence in science: An emerging general method of invention," Post-Print hal-03958025, HAL.
    6. Heikkilä, Jussi & Rissanen, Julius & Ali-Vehmas, Timo, 2023. "Coopetition, standardization and general purpose technologies: A framework and an application," Telecommunications Policy, Elsevier, vol. 47(4).
    7. Tachia Chin & Muhammad Waleed Ayub Ghouri & Jiyang Jin & Muhammet Deveci, 2024. "AI technologies affording the orchestration of ecosystem-based business models: the moderating role of AI knowledge spillover," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-13, December.
    8. Mario Benassi & Elena Grinza & Francesco Rentocchini & Laura Rondi, 2022. "Patenting in 4IR technologies and firm performance [Robots and jobs: evidence from US labor markets]," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 31(1), pages 112-136.
    9. Matheus E. Leusin & Bjoern Jindra & Daniel S. Hain, 2021. "An evolutionary view on the emergence of Artificial Intelligence," Papers 2102.00233, arXiv.org.
    10. Nils Grashof & Alexander Kopka, 2023. "Artificial intelligence and radical innovation: an opportunity for all companies?," Small Business Economics, Springer, vol. 61(2), pages 771-797, August.
    11. Borsato, Andrea & Lorentz, André, 2023. "The Kaldor–Verdoorn law at the age of robots and AI," Research Policy, Elsevier, vol. 52(10).
    12. Rammer, Christian & Fernández, Gastón P. & Czarnitzki, Dirk, 2022. "Artificial intelligence and industrial innovation: Evidence from German firm-level data," Research Policy, Elsevier, vol. 51(7).

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    Keywords

    artificial intelligence; large technical system; general purpose technology; infrastructural technology;
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