2024/11/13 by Dino Pedreschi, Luca Pappalardo, Emanuele Ferragina +19 · 1 voice · 60 citations
Computer Science · Mathematics · Social Sciences · #Artificial intelligence #Biology #COVID-19 epidemiological studies #Coevolution #Computational biology #Computer science #Evolutionary Game Theory and Cooperation #Evolutionary biology #Reinforcement Learning in Robotics
paper · doi:10.1016/j.artint.2024.104244
published in Artificial Intelligence 339, 104244 (Elsevier BV)
openalex publication_date 2024/11/13 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/04
Human-AI coevolution, defined as a process in which humans and AI algorithms continuously influence each other, increasingly characterises our society, but is understudied in artificial intelligence and complexity science literature. Recommender systems and assistants play a prominent role in human-AI coevolution, as they permeate many facets of daily life and influence human choices through online platforms. The interaction between users and AI results in a potentially endless feedback loop, wherein users' choices generate data to train AI models, which, in turn, shape subsequent user preferences. This human-AI feedback loop has peculiar characteristics compared to traditional human-machine interaction and gives rise to complex and often “unintended” systemic outcomes. This paper introduces human-AI coevolution as the cornerstone for a new field of study at the intersection between AI and complexity science focused on the theoretical, empirical, and mathematical investigation of the human-AI feedback loop. In doing so, we: (i) outline the pros and cons of existing methodologies and highlight shortcomings and potential ways for capturing feedback loop mechanisms; (ii) propose a reflection at the intersection between complexity science, AI and society; (iii) provide real-world examples for different human-AI ecosystems; and (iv) illustrate challenges to the creation of such a field of study, conceptualising them at increasing levels of abstraction, i.e., scientific, legal and socio-political.