This kind of elasticity in language use is the sort of thing that gives AI safety a bad name. You can't take AI research at face value if it's using strange re-definitions of common words.
This is not a redefinition, the harm results from the standard usage of the tool. If the AI is being used to predict the possible future behaviour of adversarial countries, then you need the AI to be honest or lots of people could die. If the AI concludes that your adversary would be more friendly towards its programmed objectives, then it could conclude lying to the president is the optimal outcome.
This can show up in numerous other contexts. For instance, should a medical diagnostic AI be able to lie to you if lying to you will statistically improve your outcomes, say via the placebo effect? If so, should it also lie to the doctor managing your care to preserve that outcome, in case the doctor might slip and reveal the truth?
There are no actual safety issues with LLMs, nor will there be any in the foreseeable future because nobody is using them in any context where such issues may arise. Hence why you're forced to rely on absurd hypotheticals like doctors blindly relying on LLMs for diagnostics without checking anything or thinking about the outputs.
There are honesty/accuracy issues. There are not safety issues. The conflation of "safety" with other unrelated language topics like whether people feel offended, whether something is misinformation or not is a very specific quirk of a very specific subculture in the USA, it's not a widely recognized or accepted redefinition.
AI safety is not a near-term project, it's a long-term project. The what-ifs are exactly the class of problems that need solving. Like it or not, current and next generation LLMs and similar systems will be used in safety critical contexts, like predictive policing which is already a thing.
Edit: and China is already using these things widely to monitor their citizens, identify them in surveillance footage and more. I find the claim that nobody is using LLMs or other AI systems in some safety critical contexts today pretty implausible actually.
None of what is remotely plausible?
And there's lots of actual, real scientists who think AI risk is a real thing we should be concerned with. Both within the field (e.g. Stuart Russel) and outside of the field (e.g. Stephen Hawking.) Are all of these scientists also talking with zero basis in actual science?
That's just wrong. This very paper we're discussing has AI safety factors built-in: the AI is not supposed to be able to lie, and yet it exhibited deceiving behaviours anyway. That falls squarely under AI safety, and is a pretty useful observation to inform future attempts.
> The current state of so-called "AI" is our fire. It's impressive and useful (and there are real dangers associated with it) but it has no bearing on intelligence, let alone superintelligence.
That's conjecture. We don't know what general intelligence really is, so you simply cannot gauge how close we are. For all you know we could be one simple tweak away from current architectures, and that should be terrifying.
> As it stands, we don't have the understanding or the tools to do anything useful wrt safety from a super-intelligent AI.
Even if that were true, which it's not, we certainly won't develop that understanding or those tools if we don't start researching them!
> We do have the understanding and tools to do something useful about asteroids and climate change.
Suppose you had a time machine and went back to the 19th century to explain the dangers of asteroids wiping out all of humanity. They didn't have the launch capability or the detection abilities we do now, but if they were sufficiently convinced of this real threat, does it not seem plausible that they could be motivated to more heavily fund research into telescopes and rockets? Couldn't we plausibly have reached space sooner and be even better prepared in the present to meet that threat than we are now?
Instead of a time machine, couldn't we just use our big brains to predict that something might actually be a serious problem in the future and that maybe we should devote a few smart people to thinking about these problems now and how to mitigate them?
This all just strikes me as incredibly obvious, and we do it in literally every other domain, but somehow say "AI" and basic logic goes out the window.