Correspondence: fulvio.castellacci@tik.uio.no
Theme and objectives:
Artificial intelligence (AI) is a new and important general-purpose technology, that is expected to drive economic growth in the next decades (Agrawal et al., 2019; Agrawal et al., 2023a; Goos and Savona, 2024). Besides automating working tasks, AI can create new tasks and new occupations; it can enhance efficiency across business functions; it can increase firms’ flexibility and responsiveness to demand and market changes; it can foster companies’ ability to leverage advanced external knowledge; and it can boost R&D, combinatorial search and innovation (Agrawal et al., 2023b; Brynjolfsson and Raymond, 2023).
However, many fear that AI might also come with economic and social costs (Acemoglu, 2021). In economic terms, the negative impacts that are discussed in current research focus relate to an increasing concentration of knowledge and market power in AI-related industries. The adverse effects of this concentration occur in the distribution of income on the labor market as well as in terms of broader economic development. If AI will lead to more market concentration and further consolidate the power of superstar firms, technological unemployment, and an increase in wage inequalities and the profit share, these new general-purpose technologies will end up fostering income inequalities, with social implications too (Acemoglu, 2024). Moreover, increased technological dependencies between few producers and many users of AI may lead to a concentrated accumulation of intangible assets that threatens to lead to an uneven distribution of innovative benefits from AI (Rikap, 2023).
These emerging research issues are now attracting a great deal of scholarly attention across economics and management, yet they have highly relevant to tackle from a geographical perspective too. The GEOINNO academic community is only starting to investigate geographical patterns and the spatial dynamics of AI within and across regions. It is reasonable to expect that both the adoption and diffusion of AI innovations, as well as its economic effects will largely differ across territories, thus possibly reinforcing existing disparities in terms of digital capabilities and economic competitiveness and performance. A few studies have started to tackle these questions from a regional and spatial perspective (Xiao and Boschma, 2023, Dahlke et al., 2024), but many questions still remain open. There is therefore a need for theoretical and empirical research on the geography of AI, as well as the role of regional policies to foster positive impacts and tackle negative effects.
The objective of this special session is to bring together scholars working on the geography of artificial intelligence. We welcome conceptual papers that offer original and relevant framework of analysis, as well as empirical papers exploring novel indicators to map artificial intelligence in space.
List of topics:
References
Acemoglu, D. (2024): “The simple macroeconomics of AI”, Economic Policy, forthcoming.
Acemoglu, D. (2021): “Harms of AI”, NBER Working Paper Series, WP 29247.
Agrawal et al. (2023a): “Do we want less automation?”, Science, 381: 155-158.
Agrawal et al. (2023b): “Artificial intelligence and scientific discovery: a model of prioritized search”, Research Policy, 53: 104989.
Agrawal, A., Gans, J. and Goldfarb, A. (2019): “Artificial intelligence: The ambiguous labor market impact of automating prediction”, Journal of Economic Perspectives, 33 (2): 31-50.
Brynjolfsson, E., Li. D. and Raymond, L. (2023): “Generative AI at work”, NBER Working Papers, WP 31161.
Dahlke, J., Beck, M., Kinne, J., Lenz, D., Dehghan, R., Wörter, M., & Ebersberger, B. (2024): “Epidemic effects in the diffusion of emerging digital technologies: evidence from artificial intelligence adoption.” Research Policy, 53(2), 104917.
Goos, M. and Savona, M. (2024): “The governance of artificial intelligence: Harnessing opportunities and mitigating challenges”, Research Policy, 53: 104928.
Rikap, C. (2023). Intellectual monopolies as a new pattern of innovation and technological regime. Industrial and Corporate Change. 33(5): 1037-1062. doi: 10.1093/icc/dtad077.
Xiao, J., & Boschma, R. (2023). The emergence of artificial intelligence in European regions: the role of a local ICT base. The Annals of Regional Science, 71(3), 747-773.