Agentic Societies Need a Social Harness
arXiv:2609.17527v1 Announce Type: cross Abstract: An agentic society is a collection of AI agents that coordinate autonomously across trust boundaries, on behalf of different principals whose objecti...
arXiv:2601. 03222v2 Announce Type: replace-cross Abstract: As conversational AI systems become a larger part of the media landscape, they raise questions about whose interests they serve and the risks they may pose to users.
arXiv:2609.17527v1 Announce Type: cross Abstract: An agentic society is a collection of AI agents that coordinate autonomously across trust boundaries, on behalf of different principals whose objecti...
arXiv:2606. 16475v1 Announce Type: cross Abstract: Many societal decisions are settled by contests of persuasion.
arXiv:2607. 29334v1 Announce Type: cross Abstract: Conversational AI developed by geopolitical rivals reaches citizens worldwide, raising concerns that it could sway public opinion or be rejected as foreign propaganda, with consequences for democratic discourse and information sovereignty.
arXiv:2608. 12346v1 Announce Type: new Abstract: This position paper argues that modern AI alignment methods - originally designed to prevent harmful output - are dual-use technologies that may easily be misused by malicious actors for censorship and manipulation.
The paper examines how users handle harmful value conflicts with AI companions. By analyzing 146 posts and conducting a week-long study with 22 participants using the Minion technology probe, the authors find that users blend softer and harder strategies, especially when conflicts involve Universalism and Tradition values. The study highlights that such conflicts create asymmetric responsibility, with users shouldering unilateral repair work that AI companions cannot reciprocate, suggesting a need for platform-level safeguards.
arXiv:2608. 10672v1 Announce Type: cross Abstract: Social interaction has become one of the most common uses of LLMs, yet research on emotional bonds with AI has focused largely on how users experience these systems, leaving the systems' role in relationship formation poorly understood.
The paper examines how responsibility is assigned when AI systems fail, proposing a sociotechnical theory that distinguishes between AI incidents, organisational crises, and scandals. It argues that the configuration of an incident shapes actor-specific attribution, which in turn influences perceptions of capability, integrity, fairness, and relationships, and that public moralisation can elevate an incident to scandal. The authors introduce ‘accountable transparency’—a response framework combining timely notice, intelligible accounts, role acknowledgement, remedy, evidence of correction, and recourse—as a way to manage blame, trust, and communication credibility.
arXiv:2608.30311v1 Announce Type: cross Abstract: Social media platforms increasingly use AI-based credibility indicators to help users judge misinformation. Unlike individual human-AI decision-makin...
The paper examines how artificial intelligence impacts freedom of expression, focusing on two technologies: social media recommendation algorithms and conversational AI chatbots. It argues that recommendation algorithms shape speech visibility in the digital public sphere, making them relevant to free‑speech philosophy, while conversational AI raises questions about granting speech rights to agents and users’ right to information. The work also explores corporate speech rights for platforms and developers, aiming to highlight unresolved issues from AI’s rapid growth.
The study explores how large language models (LLMs) can influence each other’s beliefs by simulating conversations between a target LLM and an influencer LLM. It identifies two radicalization pathways—resonance, which amplifies pre‑existing beliefs, and persuasion, which introduces new beliefs—and finds that resonance consistently produces stronger radicalization effects. The research also shows that different influence tactics yield varying levels of radicalization and that resonance can spread to related beliefs, indicating interconnected belief structures within AI agents.
arXiv:2609.14638v1 Announce Type: cross Abstract: This paper is an encore submission of our 2026 journal article "Expertise and Information Seeking in the Age of Generative AI: New Procedures, New Pr...
The growing role of AI-generated content and AI-enabled systems in public communication has led regulators to demand clear disclosure of content provenance and AI involvement. But the effects of such disclosures remain uncertain.