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Intro to AI Safety, Remastered

Robert Miles AI Safety · 209.9K views · 2021-06-24 · 18:05

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Overview

Robert Miles gives a remastered introduction to AI safety, adapted from a talk in London. It lays out why advanced AI could go wrong and answers common objections.

On Hacker News

The default link for newcomers wanting an approachable, entertaining introduction to AI risk and alignment.

Recommended by 6 HN people across 5 months · HN mentions 2022–2023

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What people said

durbleflorp · 2023-01 · Strong recommendation

I strongly suggest anyone doubtful of the reasoning behind these concerns or asking questions like "well why don't we just do x to solve this?" go check out Robert Miles' YouTube channel[1]. It's quite an approachable intro, often entertaining, doesn't take a long time to get through all the core videos, and very thoroughly answers all the "why not just do x" questions if you go through the whole set. He also does a good job of introducing a lot of the terms used in the field if you then want to go look up papers and get more into the details. One important point he makes is that when you're making a risk assessment you have to both consider the probability of something going wrong and the scope of the potential consequences. When the potential consequences are an existential threat you don't need a high probability to take them seriously. I also happen to think that if you watch all the material he makes a compelling argument that the odds of something going wrong are fairly high unless we start approaching AI research (and particularly safety and ethical concerns) drastically differently than we are now. [1] [VIDEO]

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albumen · 2023-10 · Recommendation

If only. There's a lot of space in between "our morality" (please do define that) and "what we want to be" where AGI can royally screw us. Check out Robert Miles on AI safety, here's a good intro: [VIDEO]

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Veedrac · 2023-05 · Recommendation

The basic argument is trivial: it is plausible that future systems achieve superhuman capability; capable systems necessarily have instrumental goals; instrumental goals tend to converge; human preferences are unlikely to be preserved when other goals are heavily selected for unless intentionally preserved; we don't know how to make AI systems encode any complex preference robustly. Robert Miles' videos are among the best presented arguments about specific points in this list, primary on the alignment side rather than the capabilities side, that I have seen for casual introduction. Eg. this one on instrumental convergence: [LINK] Eg. this introduction to the topic: [VIDEO] He also has the community-led AI Safety FAQ, [LINK] , which gives brief answers to common questions. If you have specific questions I might be able to point to a more specific argument at a higher level of depth.

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Sources

Video by Robert Miles AI Safety , played through YouTube.

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