Ensuring advanced AI is safe and beneficial for everyone.

Taking place in Seoul on Monday, July 6, this workshop is part of the ongoing Alignment Workshop series, following prior gatherings in San Diego, Singapore, Vienna, New Orleans, San Francisco, and London. Bringing together global leaders in academia and industry, our goal is to deepen our collective understanding of the potential risks from Artificial General Intelligence (AGI) and collaboratively explore effective strategies for mitigating these risks.

In partnership with the Center for AI Safety, FAR.AI convened a workshop on infrastructure for secure and verifiable AI, colocated with IEEE S&P in San Francisco on May 17, 2026. We brought together researchers, builders, and funders across ML, hardware security, systems, cryptography, and computer security to identify the most promising technical approaches and spark concrete collaborations.

ControlConf is a conference dedicated to the emerging field of AI control: the study of techniques that mitigate security risks from AI even if the AI itself is trying to subvert them.

Training against white-box deception detectors in a realistic coding environment reveals two obfuscation strategies models can develop: modifying internal representations to evade the detector, or producing deceptive text with justifications that bypass it. However, sufficiently strong KL regularization combined with a detector penalty can suppress both, validating deception detectors as viable training signals against reward hacking.

We tested the effectiveness of "defense-in-depth" AI safety strategies, where multiple layers of filters are used to prevent AI models from generating harmful content. Our a new attack method, STACK, bypasses defenses layer-by-layer and achieved a 71% success rate on catastrophic risk scenarios where conventional attacks achieved 0% success against these multi-layered defenses.

GPT-4o was as effective at increasing conspiracy beliefs ("bunking") as decreasing them ("debunking"), and OpenAI's guardrails did little to prevent this.