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#431 – Roman Yampolskiy: Dangers of Superintelligent AI
Lex Fridman Podcast
The Limitation of Formal Verification in AI Safety Engineering
Formal verification through mathematical proofs in AI safety engineering is a significant advancement, but it is not a permanent solution to the problem. Achieving 100% accuracy in verifying AI systems is practically unattainable due to the sheer number of decisions AI systems make and the complexity of real-world scenarios. While creating an AI verifier to ensure adherence to specified guardrails and functionality is crucial, verifying every aspect of the system, including hardware, communication channels, and world models, presents immense challenges. Mapping the world into the system's model and accounting for uncertainties such as interpreting human emotions further complicate the verification process. Although formal proofs can verify deterministic algorithms, achieving complete assurance in real-world applications remains a challenging and potentially unattainable goal.
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