Joint Activity Potential as a Resource for Socio-Economic Development in the Age of Large Language Models

Parinov, Sergey (2026): Joint Activity Potential as a Resource for Socio-Economic Development in the Age of Large Language Models.

Abstract

Firms, regions, and countries with a similar set of resources often demonstrate different performance outcomes, and a substantial part of this variation is related not to a deficit of participants' capabilities but to the non-optimal use of their productive complementarity. The paper introduces the concept of joint activity potential (JAPot) as the maximum surplus achievable through the optimal combination of participants' complementary capabilities and intentions, together with a realisation coefficient φ reflecting the degree to which this potential is actually used. A three-level conceptual model is proposed, linking the structure of complementarity, institutional mechanisms, and the cognitive-communicative infrastructure (as a shared mental model, SMM) that both constrains and enables the realisation of JAPot. It is argued that large language models provide technological means for purposefully working with the SMM, opening up the possibility of governing JAPot as a new type of development resources. On this basis, an updated version of the "technology demand signal" for the AI industry, originally proposed in other works, is presented. Assuming that the required AI solutions can be created, principles are formulated, oriented toward intensive rather than extensive growth: a) through the fuller disclosure of already existing complementarity rather than the accumulation of resources; b) by the expansion of JAPot itself. One of the results discusses the risk of cognitive homogenization, including as a result of the improper use of AI, as a threat to intergenerational cognitive heritage. This paper is considered a vision concept, laying out a conceptual framework and problem statement for a long-term research program, as well as defining landmarks for the development of AI technologies.

• Item Type: MPRA Paper
• Language: English
• Keywords: joint activity potential; realisation coefficient; shared cognitive infrastructure; large language models; intensive socio-economic development
• Subjects: D - Microeconomics > D0 - General > D02 - Institutions: Design, Formation, Operations, and Impact; D - Microeconomics > D2 - Production and Organizations > D23 - Organizational Behavior ; Transaction Costs ; Property Rights; D - Microeconomics > D8 - Information, Knowledge, and Uncertainty > D83 - Search ; Learning ; Information and Knowledge ; Communication ; Belief ; Unawareness; O - Economic Development, Innovation, Technological Change, and Growth > O3 - Innovation ; Research and Development ; Technological Change ; Intellectual Property Rights > O33 - Technological Change: Choices and Consequences ; Diffusion Processes

References

Abramovitz, M. (1986). Catching up, forging ahead, and falling behind. Journal of Economic History, 46(2), 385–406. Acemoglu, D., & Restrepo, P. (2019). Automation and new tasks: How technology displaces and reinstates labor. Journal of Economic Perspectives, 33(2), 3–30. Acemoglu, D., & Robinson, J. A. (2006). Economic origins of dictatorship and democracy. Cambridge University Press. Autor, D. H. (2001). Wiring the labor market. Journal of Economic Perspectives, 15(1), 25–40. Becker, G. S. (1976). The economic approach to human behavior. University of Chicago Press. Bommasani, R., Creel, K. A., Kumar, A., Jurafsky, D., & Liang, P. (2022). Picking on the same person: Does algorithmic monoculture lead to outcome homogenization? Advances in Neural Information Processing Systems, 35. Brynjolfsson, E., Li, D., & Raymond, L. R. (2023). Generative AI at work. NBER Working Paper No. 31161. Cannon-Bowers, J. A., Salas, E., & Converse, S. (1993). Shared mental models in expert team decision making. In N. J. Castellan Jr. (Ed.), Individual and group decision making: Current issues (pp. 221–246). Lawrence Erlbaum. Coase, R. H. (1960). The problem of social cost. Journal of Law and Economics, 3, 1–44. Doshi, A. R., & Hauser, O. P. (2024). Generative AI enhances individual creativity but reduces the collective diversity of novel content. Science Advances, 10(28), eadn5290. Easterly, W. (2001). The elusive quest for growth: Economists' adventures and misadventures in the tropics. MIT Press. Ellison, G., Glaeser, E. L., & Kerr, W. R. (2010). What causes industry agglomeration? Evidence from coagglomeration patterns. American Economic Review, 100(3), 1195–1213. Gerschenkron, A. (1962). Economic backwardness in historical perspective. Harvard University Press. Girotra, K., Meincke, L., Terwiesch, C., & Ulrich, K. T. (2024). Ideas are dimes a dozen: Large language models for idea generation in innovation. Management Science. https://doi.org/10.2139/ssrn.4526071 Gruetzemacher, R., & Whittlestone, J. (2022). The transformative potential of artificial intelligence. Futures, 135, 102884. Gulati, R. (1998). Alliances and networks. Strategic Management Journal, 19(4), 293–317. Hong, L., & Page, S. E. (2004). Groups of diverse problem solvers can outperform groups of high-ability problem solvers. Proceedings of the National Academy of Sciences, 101(46), 16385–16389. Haltiwanger, J., Hyatt, H., & McEntarfer, E. (2018). Who moves up the job ladder? Journal of Labor Economics, 36(S1), S301–S336. Hidalgo, C. A., & Hausmann, R. (2009). The building blocks of economic complexity. PNAS, 106(26), 10570–10575. Ide, E., & Talamàs, E. (2024). Artificial intelligence in the knowledge economy. Journal of Political Economy, 133(12). (NBER Working Paper circulated 2023.). Jones, C. I. (2016). The facts of economic growth. In Handbook of Macroeconomics, Vol. 2 (pp. 3–69). Elsevier. Jovanovic, B. (1979). Job matching and the theory of turnover. Journal of Political Economy, 87(5), 972–990. Kleinberg, J., & Raghavan, M. (2021). Algorithmic monoculture and social welfare. PNAS, 118(22), e2018340118. Korinek, A. (2023). Generative AI for economic research: Use cases and implications for economists. Journal of Economic Literature, 61(4), 1281–1317. Krugman, P. (1994). The myth of Asia's miracle. Foreign Affairs, 73(6), 62–78. Kuchař, P. (2025). Competition as socially extended cognition: A Hayekian perspective on market knowledge and institutional evolution. The Review of Austrian Economics, 1-23. Lakatos, I. (1970). Falsification and the methodology of scientific research programmes. In I. Lakatos & A. Musgrave (Eds.), Criticism and the growth of knowledge (pp. 91–196). Cambridge University Press. Leibenstein, H. (1966). Allocative efficiency vs. "X-efficiency". American Economic Review, 56(3), 392–415. Lu, J. (2025). Tacit knowledge in large language models. The Review of Austrian Economics. https://doi.org/10.1007/s11138-025-00710-5 (GMU Working Paper in Economics No. 25-25.) Mankiw, N. G., Romer, D., & Weil, D. N. (1992). A contribution to the empirics of economic growth. Quarterly Journal of Economics, 107(2), 407–437. Mathieu, J. E., Heffner, T. S., Goodwin, G. F., Salas, E., & Cannon-Bowers, J. A. (2000). The influence of shared mental models on team process and performance. Journal of Applied Psychology, 85(2), 273–283. Milgrom, P., & Roberts, J. (1990). The economics of modern manufacturing: Technology, strategy, and organization. American Economic Review, 80(3), 511–528. North, D. C. (1990). Institutions, institutional change and economic performance. Cambridge University Press. North, D. C., Wallis, J. J., & Weingast, B. R. (2009). Violence and social orders. Cambridge University Press. Ostrom, E. (1990). Governing the commons: The evolution of institutions for collective action. Cambridge University Press. Ostrom, E. (2009). A general framework for analyzing sustainability of social-ecological systems. Science, 325(5939), 419–422. Page, S. E. (2007). The difference: How the power of diversity creates better groups, firms, schools, and societies. Princeton University Press. Parinov S.I. (2025a). Mechanisms of socio-economic activity based on the principles of institutional design: the search for a common model. Economic Sociology. Vol. 26, No. 5, pp. 53–86. (in Russian) DOI: 10.17323/1726-3247-2025-5-53-86 (English version is available as a MPRA preprint: Parinov, S. (2025). Building Resilient Mechanisms for Joint Socio-Economic Activities: Insights from Institutional Design Principles. https://mpra.ub.uni-muenchen.de/127335/1/MPRA_paper_127198.pdf) Parinov, S. I. (2025b). Systemic digitalization of economic mechanisms: a methodological approach. Business Informatics, 19(4), 54–67. https://doi.org/10.17323/2587-814X.2025.4.54.67 Pritchett, L. (2001). Where has all the education gone? World Bank Economic Review, 15(3), 367–391. Rodrik, D. (2007). One economics, many recipes: Globalization, institutions, and economic growth. Princeton University Press. Roth, A. E. (2018). Marketplaces, markets, and market design. American Economic Review, 108(7), 1609–1658. Samuelson, P. A. (1954). The pure theory of public expenditure. Review of Economics and Statistics, 36(4), 387–389. Solow, R. M. (1956). A contribution to the theory of economic growth. Quarterly Journal of Economics, 70(1), 65–94. Syverson, C. (2011). What determines productivity? Journal of Economic Literature, 49(2), 326–365. Tilman, D., et al. (2001). Diversity and productivity in a long-term grassland experiment. Science, 294(5543), 843–845. Weitzman, M. L. (1998). Recombinant growth. Quarterly Journal of Economics, 113(2), 331–360. Williamson, O. E. (1985). The economic institutions of capitalism. Free Press.