mlsanityData to 14 Oct 2026

Can Media Act as a Soft Regulator of Safe AI Development? A Game Theoretical Analysis

arXiv 2509.02650 ↗First posted 2 Sep 2025cs.AI cs.GT q-bio.PEcited by 3

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Abstract (arXiv)

When developers of artificial intelligence (AI) products need to decide between profit and safety for the users, they likely choose profit. Untrustworthy AI technology must come packaged with tangible negative consequences. Here, we envisage those consequences as the loss of reputation caused by media coverage of their misdeeds, disseminated to the public. We explore whether media coverage has the potential to push AI creators into the production of safe products, enabling widespread adoption of AI technology. We created artificial populations of self-interested creators and users and studied them through the lens of evolutionary game theory. Our results reveal that media is indeed able to foster cooperation between creators and users, but not always. Cooperation does not evolve if the quality of the information provided by the media is not reliable enough, or if the costs of either accessing media or ensuring safety are too high. By shaping public perception and holding developers accountable, media emerges as a powerful soft regulator -- guiding AI safety even in the absence of formal government oversight.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 10 of its 49 references that are in the map. First posted on arXiv 2 Sep 2025.

Builds on

10 of 49 references.

References · 10

  1. 2025Multi-Agent Risks from Advanced AIcited by 163
  2. 2025International AI Safety Reportcited by 67
  3. 2023Unveiling Security, Privacy, and Ethical Concerns of ChatGPTcited by 53
  4. 2017Statistical physics of human cooperationcited by 30
  5. 2025Media and responsible AI governance: a game-theoretic and LLM analysiscited by 12
  6. 2019Self-Organization and Artificial Lifecited by 11
  7. 2025Do LLMs trust AI regulation? Emerging behaviour of game-theoretic LLM agentscited by 11
  8. 2021Voluntary safety commitments provide an escape from over-regulation in AI developmentcited by 10
  9. 2020Artificial Intelligence Development Races in Heterogeneous Settingscited by 9
  10. 2024Trust AI Regulation? Discerning users are vital to build trust and effective AI regulationcited by 9

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 2.

3 papers.