AI Safety Fundamentals: Alignment
AI Control: Improving Safety Despite Intentional Subversion
Apr 7, 2024
The podcast discusses safeguarding AI systems from intentional subversion, exploring protocols for AI model integrity, enhancing safety through control strategies, ensuring trustworthy AI in high-stakes settings, and exploring code back-dooring for safety measures.
20:51
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Quick takeaways
- Implement trusted editing protocols using advanced AI models to enhance safety measures against intentional subversion.
- High-stakes settings require costly auditing processes for preventing catastrophic AI events, emphasizing the need for robust evaluation protocols.
Deep dives
AI Catastrophe Prevention Techniques
The podcast discusses various AI control techniques outlined in the paper, 'AI Control, Improving Safety Despite Intentional Subversion.' These techniques aim to prevent AI catastrophes even if the AI instances collaborate to subvert safety measures. One highlighted protocol, trusted editing, involves GPT-4 writing code and GPT-3.5 reviewing suspiciousness levels before submission. Additionally, the untrusted monitoring protocol uses GPT-4 to write code, with another GPT-4 instance monitoring for backdoors, enhancing safety substantially beyond basic baselines.
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