publications

2025

1. 

   Media and responsible AI governance: a game-theoretic and LLM analysis

   Nataliya Balabanova, Adeela Bashir, Paolo Bova, Alessio Buscemi, Theodor Cimpeanu, Henrique Correia Fonseca, Alessandro Di Stefano, Manh Hong Duong, Elias Fernandez Domingos, Antonio Fernandes, The Anh Han, Marcus Krellner, Ndidi Bianca Ogbo, Simon T. Powers, Daniele Proverbio, Fernando P. Santos, Zia Ush Shamszaman, and Zhao Song

   Mar 2025

   Abs arXiv

   This paper investigates the complex interplay between AI developers, regulators, users, and the media in fostering trustworthy AI systems. Using evolutionary game theory and large language models (LLMs), we model the strategic interactions among these actors under different regulatory regimes. The research explores two key mechanisms for achieving responsible governance, safe AI development and adoption of safe AI: incentivising effective regulation through media reporting, and conditioning user trust on commentariats’ recommendation. The findings highlight the crucial role of the media in providing information to users, potentially acting as a form of "soft" regulation by investigating developers or regulators, as a substitute to institutional AI regulation (which is still absent in many regions). Both game-theoretic analysis and LLM-based simulations reveal conditions under which effective regulation and trustworthy AI development emerge, emphasising the importance of considering the influence of different regulatory regimes from an evolutionary game-theoretic perspective. The study concludes that effective governance requires managing incentives and costs for high quality commentaries.

2. 

   Evolution of indirect reciprocity under emotion expression

   Henrique Correia Fonseca, Celso M. Melo, Kazunori Terada, Jonathan Gratch, Ana S. Paiva, and Francisco C. Santos

   Scientific Reports 2025 15:1, Mar 2025

   Abs DOI

   Do emotion expressions impact the evolution of cooperation? Indirect Reciprocity offers a solution to the cooperation dilemma with prior work focusing on the role of social norms in propagating others’ reputations and contributing to evolutionarily stable cooperation. Recent experimental studies, however, show that emotion expressions shape pro-social behaviour, communicate one’s intentions to others, and serve an error-correcting function; yet, the role of emotion signals in the evolution of cooperation remains unexplored. We present the first model of IR based on evolutionary game theory that exposes how emotion expressions positively influence the evolution of cooperation, particularly in scenarios of frequent errors. Our findings provide evolutionary support for the existence of emotion-based social norms, which help foster cooperation among unrelated individuals.