发表机构
SINTEF Digital; Bavarian Research Institute for Digital Transformation (bidt); University of Bamberg; OsloMet–Oslo Metropolitan University; Max Planck Institute for Security and Privacy; BI Norwegian Business School; Birmingham City University; University of Helsinki; University of Oslo; Simula Research Laboratory; Chr. Michelsen Institute; University of Agder; King’s College London; Makerere University（SINTEF数字研究所; 巴伐利亚数字化转型研究所; 班贝格大学; 奥斯陆都会大学; 马克斯·普朗克安全与隐私研究所; 挪威BI商学院; 伯明翰城市大学; 赫尔辛基大学; 奥斯陆大学; Simula研究实验室; C.M.米凯尔森研究所; 阿格德尔大学; 伦敦国王学院; 马凯雷雷大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
该研究聚焦非洲，定义恶意AI集群，分析其对当地民主与发展的风险，结合马里、埃塞俄比亚案例，提出将技术保障与多方协调结合的分层治理方案。
AI 中文摘要
生成式人工智能正在改变信息的生产、获取与传播方式，同时催生规模更大、复杂度更高的虚假信息行动。目前尚无明确证据表明完全自主的AI集群正在大规模开展影响力行动，但其支撑能力正在不断提升。我们将恶意AI集群定义为用于影响力行动的、协同性强、持续性高且具备适应性的多智能体系统，以此将其与AI辅助内容生产及集中管理的合成 persona 区分开来。我们研究了这类系统对非洲混合政权及受冲突影响国家的影响，这些国家的制度约束与脆弱媒体环境可能加剧其脆弱性。以马里和埃塞俄比亚为例，我们分析自动化影响力如何渗透社区、制造虚假共识并侵蚀对治理与发展的信任。这些案例展现了国家与非国家影响力的不同配置：马里碎片化信息环境中的竞争行为体，以及埃塞俄比亚更有组织的国家主导叙事管理策略。非洲语言与训练数据的不对称性可能会限制其影响力能力，同时削弱防御性应对措施。混合人机行动可结合自动化的规模与适应性，以及本地知识与可信度。这一前瞻性风险分析构建了AI驱动协调日益普及的场景，而非声称自主集群已在非洲大规模运作。我们提出分层治理方法，将技术保障措施与平台问责制、公民机构及区域协调相联系，以保护民主参与、和平建设与发展。
英文摘要
Generative artificial intelligence is reshaping how information is produced, accessed, and circulated, while enabling disinformation campaigns of increasing scale and sophistication. There is currently no clear evidence that fully autonomous AI swarms conduct influence operations at scale, but their enabling capabilities are advancing. We define malicious AI swarms as coordinated, persistent, and adaptive multi-agent systems designed for influence operations, distinguishing them from AI-assisted content production and centrally managed synthetic personas. We examine their implications for hybrid regimes and conflict-affected states in Africa, where institutional constraints and fragile media environments may heighten vulnerability. Drawing on Mali and Ethiopia, we consider how automated influence could infiltrate communities, fabricate consensus, and erode trust in governance and development. The cases illustrate different configurations of state and non-state influence: competing actors in Mali's fragmented information environment, and more organized state-led strategies of narrative management in Ethiopia. African-language and training-data asymmetries may constrain influence capabilities while weakening defensive responses. Hybrid human-AI operations could combine automated scale and adaptation with local knowledge and credibility. This forward-looking risk analysis develops a scenario of increasingly accessible AI-driven coordination, rather than claiming that autonomous swarms are already operating at scale in Africa. We propose a layered governance approach linking technical safeguards to platform accountability, civic institutions, and regional coordination to protect democratic participation, peacebuilding, and development.
Comments26 pages
