ReSI: Recursive Safety Improvement toward Resistant and Resilient AI
Recursive self-improvement, the participation of AI systems in improving their own capabilities, is beginning to move from theoretical prospect to practice, posing both challenges and opportunities for safety alignment.
Key points
- Models evolve through frequent updates, and their safety alignment requires continual adaptation to each new checkpoint.
- Following R$^2$AI, we term these goals resistance to known threats and resilience to unforeseen risks.
- We therefore introduce ReSI, a recursive safety improvement framework that implements this approach through automated research.
- These findings support recursive safety improvement as a practical path toward resistant and resilient AI.
Sources (1)
- [1]ReSI: Recursive Safety Improvement toward Resistant and Resilient AIarXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 8, 04:17 PM
Recursive self-improvement, the participation of AI systems in improving their own capabilities, is beginning to move from theoretical prospect to practice, posing both challenges and opportunities for safety alignment.
Models evolve through frequent updates, and their safety alignment requires continual adaptation to each new checkpoint.
Extractive summary: sentences quoted from the sources.