Ai Safety

3 articles

Editorial illustration for AI Alignment, Explained Through the RICE Framework: Robustness, Interpretability, Controllability, and Ethicality

AI Alignment, Explained Through the RICE Framework: Robustness, Interpretability, Controllability, and Ethicality

AI alignment ensures AI systems' goals and behavior match human values and intentions, preventing harmful outcomes. The RICE framework (Robustness, Interpretability, Controllability, Ethicality) provides a structured approach to understanding and achieving this alignment.

Dr. Aris Thorne·October 17, 2026

Abstract representation of Anthropic's Claude 3.5 Sonnet AI, showcasing advanced coding capabilities and robust safety features in a futuristic digital environment.

Artificial Intelligence

Anthropic advances AI safety with Claude 3.5 Sonnet's new capabilities

In an internal agentic coding evaluation, Anthropic's new Claude 3.

Dr. Aris Thorne·June 26, 2026

Abstract visualization of interconnected AI agents, symbolizing the complex and emergent behaviors of multi-agent AI systems.

Artificial Intelligence

Google DeepMind Funds Research Amid Agent Interaction Concerns

Google DeepMind and its partners are pouring $10 million into an AI safety research field that, until now, didn't exist.

Dr. Aris Thorne·June 11, 2026