safe-ai

FRAC-MAS is an agentic AI system for automated, explainable, and safe bone fracture detection, integrating vision models with multi-agent workflows to enhance diagnosis and clinical reporting.

SafeCommit presents a risk-controlled layer that certifies when memory-grounded LLM agents may safely act, using conformal action certificates to bound unsafe commitment probability and offering a simulator with public code.

Yoggi is a safe AI chat platform designed for children, offering a secure environment for kids to interact with AI.

This paper proposes a unified imitation learning framework using Taylor Series Imitation Learning and distributionally robust adaptive control to address both policy-induced and uncertainty-induced distribution shifts, with a UAV case study demonstrating safety under uncertainty.

This paper proposes a complete architectural specification of safe AGI based on closed reentry loops, providing formal proofs, machine verification in Lean 4, and Python code. It argues that this architecture mathematically guarantees self-modeling, self-preservation, and safe goal-directed behavior, contrasting with current feedforward approaches.

SkillHarness is a framework that enables computer-use agents to safely learn and execute skills in dynamic environments by incorporating safety constraints and adaptive skill selection mechanisms, reducing unsafe rates by 57.1%.

LawZero is a nonprofit startup advancing Yoshua Bengio’s research to develop safe-by-design AI systems and oracles, aiming to solve alignment challenges and mitigate deceptive behaviors in frontier models.