ABSTRACT
Developing AI technologies has been a priority for governments worldwide, mobilizing actors to build strategies and policies to accelerate and deploy AI in industry, markets, and governments. With that in mind, this paper analyzes the causal mechanism between political regimes’ institutional dynamics and AI’s development. Specifically, it compares 30 developing countries to understand the political and governance dynamics that explain the outcomes achieved with AI policy. Delving into the relationship between politics and policy, this paper reflects on how different institutional frameworks produce different results in terms of AI development. The research was based on data from the Bertelsmann Stiftung’s Transformation Index (BTI) and the Organization for Economic Co-operation and Development (OECD), using fuzzy-set quantitative comparative analysis (QCA) to analyze cases. The findings point to authoritarian countries performing better in producing AI development outcomes.
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No potential conflict of interest was reported by the author(s).
Notes
1. For more details on the BTI’s methodology, see https://www.bti-project.org/en/methodology.html.
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Fernando Filgueiras
Fernando Filgueiras is an associate professor at the Department of Political Science, Federal University of Minas Gerais (UFMG), Brazil. Affiliate faculty at Ostrom Workshop on Political Theory and Policy Analysis, Indiana University, USA. Researcher at the National Institute of Science and Technology (INCT)–Digital Democracy, Federal University of Bahia (UFBA). Professor at the National School of Public Administration (ENAP), Brazil. Filgueiras has a Ph.D. in Political Science from the University Research Institute of Rio de Janeiro (Iuperj). Among his works, Governance for the Digital World - Neither More State Nor More Market (Palgrave, 2021)