arXiv:2504.12476cs.CYcs.AI2025-04被引 2

比较德美公众对AI治理的期待,发现美国更支持AI应用,德国更谨慎。

What do people expect from Artificial Intelligence? Public opinion on alignment in AI moderation from Germany and the United States

  • 通过两国大规模问卷调查,分析公众对AI准确性、安全、公平与理想化目标的期待。
  • 德国和美国均最重视准确性与安全性,但德国对公平和理想化目标支持更弱。
  • 美国公众因使用多、言论自由支持高,形成更统一的AI期待,适合政策制定参考。

生成式人工智能的进展提升了公众意识,塑造了对社会影响的期望与担忧。核心议题是人工智能对齐问题——即AI系统在安全、公平与社会价值观方面是否符合公众期待。然而,人们对AI功能的期望及其跨国家差异尚不明确。本研究基于德国(n=1800)和美国(n=1756)的两项调查,考察公众对四种对齐维度的支持:准确性与可靠性、安全性、偏见缓解,以及促进理想化愿景。美国受访者在AI使用频率和对所有对齐特征的支持上均显著更高,反映其更开放的技术态度与更高的社会参与度。两国均以准确性和安全性最受支持,而公平性与理想化愿景等规范性更强的目标在德国获得更谨慎的响应。研究还分析了个体AI使用经验、言论自由态度、政治意识形态、党派归属与性别等因素的影响。在德国,AI使用与言论自由支持解释了更多变异;在美国,响应更具一致性,表明更高接触度可能固化公众预期。研究为人工智能治理提供了实证依据,强调将公众态度纳入理论与政策讨论的重要性。

原文摘要 · Abstract (English)

Recent advances in generative Artificial Intelligence have raised public awareness, shaping expectations and concerns about their societal implications. Central to these debates is the question of AI alignment -- how well AI systems meet public expectations regarding safety, fairness, and social values. However, little is known about what people expect from AI-enabled systems and how these expectations differ across national contexts. We present evidence from two surveys of public preferences for key functional features of AI-enabled systems in Germany (n = 1800) and the United States (n = 1756). We examine support for four types of alignment in AI moderation: accuracy and reliability, safety, bias mitigation, and the promotion of aspirational imaginaries. U.S. respondents report significantly higher AI use and consistently greater support for all alignment features, reflecting broader technological openness and higher societal involvement with AI. In both countries, accuracy and safety enjoy the strongest support, while more normatively charged goals -- like fairness and aspirational imaginaries -- receive more cautious backing, particularly in Germany. We also explore how individual experience with AI, attitudes toward free speech, political ideology, partisan affiliation, and gender shape these preferences. AI use and free speech support explain more variation in Germany. In contrast, U.S. responses show greater attitudinal uniformity, suggesting that higher exposure to AI may consolidate public expectations. These findings contribute to debates on AI governance and cross-national variation in public preferences. More broadly, our study demonstrates the value of empirically grounding AI alignment debates in public attitudes and of explicitly developing normatively grounded expectations into theoretical and policy discussions on the governance of AI-generated content.

AI对齐公众意见跨国家比较治理政策

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