I’ve seen a fair amount of skepticism about the “Provably Safe AI” paradigm, but I think detractors give it too little credit. I suspect this is largely because of idea inoculation - people have heard an undeveloped or weak man version of the idea, for example, that we can use formal methods to state our goals and prove that an AI will do that, and have already dismissed it. (Not to pick on him at all, but see my question for Scott Aaronson here.)

I will not argue that Guaranteed Safe AI solves AI safety generally, or that it could do so - I will leave that to others. Instead, I want to provide a concrete example of a near-term application, to respond to critics who say that proveability isn’t useful because it can’t be feasibly used in real world cases when it involves the physical world, and when [...]

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Outline:

(01:14) A path to provably safe autonomous vehicles

(02:37) Proven Input Reliability

(04:21) Proven Safe Driving

(06:39) Provably Safe ML

(08:02) Adversarial Concerns

(10:04) Defining Broader Sociotechnological Proveably Safe AI

(11:29) Conclusion

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Narrated by TYPE III AUDIO.