分析媒体如何通过报道影响AI治理，推动可信AI发展
Media and responsible AI governance: a game-theoretic and LLM analysis
- 用演化博弈与大模型模拟多方互动机制
- 媒体曝光可替代缺失的制度监管，提升用户信任
- 适合关注AI伦理、政策设计的研究者阅读
本文研究了人工智能开发者、监管机构、用户与媒体在构建可信AI系统中的复杂互动。结合演化博弈论与大语言模型（LLM），分析不同监管环境下各主体的战略行为。研究聚焦两大关键机制：通过媒体报告激励有效监管，以及将用户信任与评论推荐挂钩。结果表明，媒体在向用户提供信息方面起关键作用，可作为“软性”监管手段，弥补许多地区缺乏正式制度监管的空白。博弈分析与LLM模拟共同揭示了有效监管与可信AI发展的条件，强调应从演化博弈视角考量不同监管模式的影响。研究结论指出，有效治理需合理管理高质量评论内容的激励与成本。
原文摘要 · Abstract (English)
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.
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