ORIGINAL RESEARCH article
Front. Artif. Intell.
Sec. AI in Business
Volume 8 - 2025 | doi: 10.3389/frai.2025.1671917
This article is part of the Research TopicAI-Human Co-Evolution: Feedback Loop Design, Organizational Innovation, Ethical Considerations, and Workforce DynamicsView all articles
Towards a new AI Winter? How diffusion of technological innovation on networks leads to chaotic boom-bust cycles
Provisionally accepted
- 1Jozef Stefan Institute, Department of Biotechnology, Ljubljana, Slovenia
- 2Universita Carlo Cattaneo, Castellanza, Italy
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Technological developments and the impact of artificial intelligence (AI) are omnipresent themes and concerns of the present day. Much has been written on these topics but applications of quantitative models to understand the techno-social landscape have been much more limited. We propose a mathematical model that can help understand in a unified manner the patterns underlying technological development and also identify the different regimes in which the technological landscape evolves. First, we develop a model of innovation diffusion between different technologies, the growth of each reinforcing the development of the others. The model has a variable that quantifies the level of development (or innovation, discovery) potential for a given technology. The potential, or market capacity, increases via diffusion from related technologies, reflecting the fact that a technology does not develop in isolation. Hence, the growth of each technology is influenced by how developed its neighboring (related) technologies are. This allows us to reproduce long-term trends seen in computing technology and large language models (LLMs). We then present a three-dimensional system of supply, demand, and investment which shows oscillations (business cycles) emerging if investment is too high into a given technology, product, or market. We finally combine the two models through a common variable and show that if investment or diffusion is too high in the network context, chaotic boom-bust cycles can emerge. These quantitative considerations allow us to reproduce the boom-bust patterns seen in non-fungible tokens (NFTs) transactions data and also have deep implications for the development of AI which we highlight, such as the arrival of a new AI winter.
Keywords: Diffusion of innovation, Technology, Chaos, networks, AI
Received: 23 Jul 2025; Accepted: 30 Sep 2025.
Copyright: © 2025 Roman and Bertolotti. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Sabin Roman, sabin.roman@ijs.si
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