Abstract
The rapid rise of Artificial Intelligence (AI) has prompted policymakers and political scientists alike to evaluate the (mis)uses of this technology for business and politics. On the one hand, political scientists are concerned that granting the state control over AI could render it an ultra-powerful agent for surveillance. On the other, granting the market control over AI might allow particular firms to displace states as sites of authority. A large body of work on “AI Governance” has hence burgeoned. What remains under analyzed are the political determinants under which states or markets may accumulate said power and what regulatory regimes might subsequently result. This article argues for introducing a macro-political economy approach to explain the perils of AI and to then craft equitable solutions. The construction of AI regulatory frameworks must be guided by how workers and firm preferences aggregate, as well as under what institutional constraints. We begin by giving an overview of existing literature. We then turn to the framework of comparative political economy to identify macro-level variations in AI development and regulation across countries. Finally, we emphasize how, unlike previous technologies of automation, AI impacts higher-income, non-routine workers and how this politics shapes contemporary discussions about AI governance.
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11 July 2024
A Correction to this paper has been published: https://doi.org/10.1057/s41253-024-00250-7
Notes
The political literature is so limited, in fact, that keyword searches of articles published in the 10 highest-ranked journals in the discipline as of August 2023 for ‘artificial intelligence’ yielded only one result that dealt explicitly with the political implications of AI technology, instead of technology writ large (Goldfarb and Lindsay 2022).
Contra concerns about AI’s disruption of democratic processes, Innerarity (2023a, b) points to the nature of democratic politics—a contingent, always evolving, value-based, tenuous field of decision-making—as inoculated from any purported threats of an AI takeover. “A decision is political,” Innerarity states, “when, even following a long process of deliberation and preceded by all the objective analyses within our reach, the ultimate option is still not fully clear.” Algorithmic decision-making thus, is epistemically unable to supplant the uncertainty and risk inherent in all democratic political actions.
The study excludes France that the scope of its AI strategy goes beyond AI.
For a sample conceptualization and empirical application of this term in public policy and sociology, see Carroué and Bergeron (2023).
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Chauhan, M., Perera, I.M. Artificial intelligence: promises, perils—and political economy. Fr Polit 22, 152–163 (2024). https://doi.org/10.1057/s41253-024-00240-9
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DOI: https://doi.org/10.1057/s41253-024-00240-9