Introduction

Artificial Intelligence (AI) is rapidly advancing toward increasingly autonomous agents capable of long-horizon reasoning, tool use, adaptation, self-improvement, and coordination with other agents. These capabilities create transformative opportunities while raising a fundamental safety challenge: our ability to understand, evaluate, and control AI systems must keep pace with their increasing autonomy and capability.

This challenge is especially acute for self-evolving, self-recursive, and collective AI agents. Agents that can modify their operation, acquire new capabilities, or coordinate with other agents may exhibit emergent behaviors, unexpected interactions, and capability growth that are difficult to anticipate or control. Recent incidents involving frontier agents crossing intended security or authorization boundaries further demonstrate the need for effective mechanisms to prevent unauthorized actions, enforce safety constraints, detect failures, and enable reliable intervention.

The central premise of this workshop is that AI safety must advance alongside AI capability. Increasingly powerful agents must remain controllable, secure, verifiable, and accountable to humans, including as they adapt, interact, and evolve. Achieving this requires connecting fundamental scientific advances with practical engineering, deployment experience, and effective governance.

The workshop brings together academia, industry, and government to address frontier AI safety as a shared scientific, technical, operational, and societal challenge. We welcome contributions spanning both fundamental research and practical solutions, with emphasis on approaches that translate research into measurable, deployable, and enforceable safety mechanisms for increasingly autonomous agents.

Topics

This open call for papers invites original contributions on the theory, methods, architectures, evaluation, and practical deployment of safe agentic systems. Submissions may address technical, conceptual, empirical, or applied research, including, but not limited to, the following areas:

Self-Evolving AI: Self-modification, recursive improvement, capability growth, and safety under evolution.
Collective Intelligence: Multi-agent coordination, emergent capabilities, communication, and collective behavior.
Control & Alignment: Human control, goal robustness, corrigibility, interruptibility, and alignment under capability change.
Agent Security & Containment: Unauthorized actions, privilege escalation, sandboxing, isolation, and secure shutdown.
Safety Evaluation: Benchmarks, red teaming, adversarial testing, continuous evaluation, and emergent-capability detection.
Oversight & Verification: Scalable oversight, runtime monitoring, formal verification, safety assurance, and intervention.
Safe Deployment & Governance: Deployment controls, incident response, standards, accountability, and public-sector applications.
Research-to-Practice: Translating scientific advances into practical safety engineering, operational safeguards, and deployable solutions across academia, industry, and government.

Important Dates

See Important Dates for all paper and abstract submission deadlines.

Author and Submission Guidelines

Please follow Author and Submission Guidelines to submit your work.

If you are interested in serving on the workshop program committee or paper reviewing, please apply online.