We’re launching Lyria 3.5 in Google Flow Music, with advances across musicality, lyrics, vocals, and creative control
deepmind.google·6d ago
AI Engineering
DeepMind Blog·Jun 16·5 min read
Securing the future of AI agents
TL;DR
As AI agents become more capable, they pose risks due to potential misalignment with human values. To address this, DeepMind developed the AI Control Roadmap, a framework that enhances security through a layered approach.
✦ Why It Matters
Engineers can adopt layered security approaches to manage AI risks effectively in their projects.
Key Takeaways
- Adopt a defense-in-depth approach for AI security.
- Utilize trusted AI systems for constant monitoring.
- Implement tiered response strategies based on threat severity.
- Measure performance using metrics like coverage and recall.
How It Works
The AI Control Roadmap employs a dual-layered security approach, combining traditional cybersecurity practices with advanced monitoring techniques. By treating AI agents as potential insider threats, it uses a threat-modelling framework to systematically identify risks.
Trusted AI systems act as supervisors, continuously reviewing agent behavior to detect and prevent harmful actions before they occur.