揭示智能代理系统在社会向善中的地理责任缺失与实践脱节问题
Whose Good, Whose Place? The Moral Geography of Agentic AI for Social Good
- 分析112篇论文，发现73%未说明地理背景
- 制度类目标论文仅13%明确地域，远低于健康与生态类
- 仅25%有实际部署，提出最小报告标准以增强问责
智能代理系统被越来越多地应用于社会向善领域，常以联合国可持续发展目标（SDGs）作为全球福祉的表述框架。然而，声称社会向善并不等于对服务社区负责。我们对2015至2026年间发表的112篇智能代理系统用于社会向善的论文进行了结构化调查。发现存在道德-地理不对称：在政治、法律与文化语境至关重要的领域，论文最缺乏地理信息。全样本中82篇（73%）未指定地理背景。与健康或生态类目标相关的论文报告地理信息比例为37%-40%，而制度与社会政策类目标仅13%。其中，覆盖最广的SDG 16（和平、正义与强大机构）也是地理信息最少的。这反映出一种道德抽象现象：制度向善被当作普遍价值，而健康与生态向善则更强调本地性。第二项发现是：仅有28篇（25%）论文报告了真实世界部署或小规模测试。我们识别出五大问责缺口，并提出一个最小报告标准，以推动更具情境性、参与性和负责任的智能代理系统社会应用。
原文摘要 · Abstract (English)
Agentic AI systems are increasingly proposed for social-good domains, often invoking the United Nations Sustainable Development Goals (SDGs) as a vocabulary of global benefit. Yet claims of social good do not establish accountability to the communities a system claims to serve. We present a structured survey of 112 papers on agentic AI for social good published between 2015 and 2026. We find a moral-geographic asymmetry: papers are least likely to specify geographic context in precisely the domains where local political, legal, and cultural context matters most. Across the corpus, 82 of 112 papers (73%) specify no geographic context. Papers aligned with health or physical/ecological SDGs specify geography 37-40% of the time, while papers aligned with institutional and social-policy SDGs do so only 13%. SDG 16, peace, justice, and strong institutions, is both the most-covered goal in the corpus and the one with the lowest geographic-specification rate. We interpret this as moral abstraction: agentic AI for social good often treats institutional good as universal in ways it does not treat health or ecological good. A second finding compounds this: only 28 of 112 papers (25%) report any real-world deployment or small-scale test. We identify five accountability gaps and propose a minimal reporting standard for more context-specific, participatory, and accountable agentic AI for social good.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。