arXiv:2608. 14565v1 Announce Type: new Abstract: AI safety research has mainly focused on two areas: technical alignment (ensuring AI systems produce human-aligned outputs) and the regulation of generative AI's societal impacts (including unemployment risk and labor market disruption).
arXiv:2607. 19292v1 Announce Type: cross Abstract: Current AI safety discourse still focuses disproportionately on visible failures, including obvious harms, dramatic misuse, and hypothetical catastrophic scenarios.
arXiv:2609.05749v1 Announce Type: new Abstract: Work on the risks of artificial intelligence has focused predominantly on capability risk: the danger that systems become too powerful, too autonomous,...
arXiv:2607. 03215v1 Announce Type: cross Abstract: Artificial intelligence has spread across the whole of the security lifecycle.
The paper proposes AI Deployment Accountability Engineering (ADAE), a new subdiscipline focused on establishing measurable, continuous, and actionable accountability for AI systems once they are deployed. ADAE treats accountability as a deployment-layer property, aiming to ensure systems remain within acceptable risk limits, identify failure contexts, attribute failures across technical and human components, and translate technical failures into downstream consequences. The authors outline a research agenda built around four pillars—structured discovery of context-dependent failure modes, privacy-preserving accountability measurement, system-level risk analysis for agentic AI, and translation of technical failures into operational and institutional risks—to support timely intervention in safety-critical socio-technical environments.
arXiv:2608. 05173v1 Announce Type: cross Abstract: As AI capabilities advance, AI systems will pose greater risks to national security and potentially humanity as a whole.
arXiv:2606. 17286v1 Announce Type: cross Abstract: AI-enabled authoritarianism is not confined to autocracies.
arXiv:2607. 26069v1 Announce Type: cross Abstract: As AI systems are rapidly integrated into critical economic, governmental, and national security functions, the gap between AI adoption and AI security readiness continues to widen.
The paper argues that the rapid pace of AI-driven change creates an adaptation gap, making human resilience a crucial capability for the AI era. Resilience is defined as the ability to absorb disruption while maintaining effective action and agency, and is examined at psychological, social, and organizational levels. The authors link resilience research with AI-in-the-loop experiments, showing that AI assistance can boost productivity, empathy, and calibrated reliance, and propose a socio‑technical agenda for education, workplace design, governance, and evaluation.
The paper discusses the need to adapt incident reporting frameworks for AI agents, which are rapidly deployed and face unique security challenges. By comparing AI systems and agents and consulting 23 experts, the authors identify key reporting elements such as agent memory, autonomy levels, and tool usage. They also highlight open research questions, potential reporting weaknesses like data leakage, and outline privacy requirements for secure AI agent deployment.
arXiv:2607. 25648v1 Announce Type: cross Abstract: Public services face growing pressure to adopt artificial intelligence (AI) to close the gap between rising demand and falling resources.
The study evaluates 684 U.S. federal AI governance documents for how they address 14 sectors and 24 AI risks, measuring both breadth and depth of coverage. It finds that risks related to robustness, system security, and governance are more frequently and substantively discussed than socioeconomic, environmental, and emerging risks, and that sectors such as public administration, national security, information, and scientific services receive higher coverage than finance and healthcare. By comparing these coverage patterns with expert vulnerability assessments, the authors identify potential gaps in AI governance that could inform future policy and industry decisions.
arXiv:2609.14796v1 Announce Type: new Abstract: The threat that AI persuasion poses to human control has been acknowledged in the literature, but not yet systematically studied. Now that persuasion a...