How can media influence responsible AI development?
Media and responsible AI governance: a game-theoretic and LLM analysis
March 14, 2025
https://arxiv.org/pdf/2503.09858This paper explores how different players (AI developers, regulators, users, and media) interact to create trustworthy AI systems. It uses game theory and LLMs to model these interactions under different regulatory scenarios, focusing on how media (acting as informed commentators) can influence user trust and developer behavior.
Key points for LLM-based multi-agent systems:
- LLMs can simulate multi-agent interactions: The research uses LLMs as agents representing developers, regulators, users, and media to investigate the dynamics of AI governance.
- Media as a "soft" regulator: Investigative journalism by the media can influence developers to build safer AI, potentially reducing the need for strict formal regulations.
- User trust is key: How users react to information from media and regulators is crucial in shaping the development and adoption of trustworthy AI.
- Incentives matter: The cost of investigations for the media and the benefits they receive for accurate reporting influence their behavior and the overall outcome of AI governance. This highlights the need to ensure that media is properly incentivized to provide quality information.
- Transparency is vital: Transparency is important not just for AI systems themselves but also for the behavior of developers and regulators, allowing for accountability.
- LLM behavior aligns partially with game theory: While some LLM agent behaviors matched the predictions of game theory models, others differed, highlighting the need for more research into LLM reasoning in such contexts.