LessWrong 2.0 Reader

Behavioural Safety is Insufficient

Past this point, we assume following Ajeya Cotra [LW · GW] that a strategically aware system which performs well enough to receive perfect human-provided external feedback has probably learned a deceptive human simulating model instead of the intended goal. The later techniques have the potential to address this failure mode [LW · GW]. (It is possible that this system would still under-perform on sufficiently superhuman behavioral evaluations)

There are (IMO) plausible threat models in which alignment is very difficult but we don't need to encounter deceptive alignment. Consider the following scenario:

Our alignment techinques (whatever they are) scale pretty well, as far as we can measure, even up to well-beyond-human-level AGI. However, in the year (say) 2100, the tails come apart [LW · GW]. It gradually becomes pretty clear that what we want out powerful AIs to do and what they actually do turns out not to generalize that well outside of the distribution on which we have been testing them so far. At this point, it is to late to roll them back, e.g. because the AIs have become uncorrigible and/or power-seeking. The scenario may also have more systemic character, with AI having already been so tightly integrated into the economy that there is no "undo button".

This doesn't assume either the sharp left turn or deceptive alignment, but I'd put it at least at level 8 in your taxonomy.

I'd put the scenario from Karl von Wendt's novel VIRTUA [LW · GW] into this category.

There are 2 topics mixed here.

1. Existence of the contrarians.
2. Side effects of their existence.

My own opinion on 1 is that they are necessary in moderation. They are doing the "exploration" part in the "exploration-exploitation dilemma". By the very fact of their existence they allow the society in general to check alternatives and find more optimal solutions to the problems comparing to already known "best practices". It's important to remember that almost everything that we know now started from some contrarian - once it was a well established truth that Monarchy is the best way to rule the people and democrats were dangerous radicals.

On the 2 - it is indeed a problem that contrarian opinions are more interesting on average, but the solution lies not in somehow making them less attractive - but by making more interesting and attractive conformist materials. That's why it is paramount to have highly professional science educators and communicators, not just academics. My own favorites are vlogbrothers (John and Hank Green) in particular and their team in Complexly in general.

My p(doom) was low when I was predicting the yudkowsky model was ridiculous, due to machine learning knowledge I've had for a while. Now that we have AGI [LW · GW] of the kind I was expecting, we have more people working on figuring out what the risks really are, and the previous concern of the only way to intelligence being RL seems to be only a small reassurance because non-imitation-learned RL agents who act in the real world is in fact scary. and recently, I've come to believe much of the risk is still real [LW · GW] and was simply never about the kind of AI that has been created first, a kind of AI they didn't believe was possible. If you previously fully believed yudkowsky, then yes, mispredicting what AI is possible should be an update down. But for me, having seen these unsupervised AIs coming from a mile away just like plenty of others did, I'm in fact still quite concerned about how desperate non-imitation-learned RL agents seem to tend to be by default, and I'm worried that hyperdesperate non-imitation-learned RL agents will be more evolutionarily fit, eat everything, and not even have the small consolation of having fun doing it.

upvote and disagree: your claim is well argued.

Possible bias, that when famous and rich people kill themselves, everyone is discussing it, but when poor people kill themselves, no one notices?

Also, I wonder what technically counts as "suicide"? Is drinking yourself to death, or a "suicide by cop", or just generally overly risky behavior included? I assume not. And these seem to me like methods a poor person would choose, while the rich one would prefer a "cleaner" solution, such as a bullet or pills. So the reported suicide rates are probably skewed towards the legible, and the self-caused death rate of the poor could be much higher.

Please don't write comments all in boldface. It feels like you're trying to get people to pay more attention to your comment than to others, and it actually makes your comment a little harder to read as well as making the whole thread uglier.

I asked ChatGPT 

Have there been any great discoveries made by someone who wasn't particularly smart? (i.e. average or below)

and it's difficult to get examples out of it. Even with additional drilling down and accusing it of being not inclusive of people with cognitive impairments, most of its examples are either pretty smart anyway, savants or only from poor backgrounds. The only ones I could verify that fit are:

• Richard Jones accidentally created the Slinky
• Frank Epperson, as a child, Epperson invented the popsicle
• George Crum inadvertently invented potato chips

I asked ChatGPT (in a separate chat) to estimate the IQ of all the inventors is listed and it is clearly biased to estimate them high, precisely because of their inventions. It is difficult to estimate the IQ of people retroactively. There is also selection and availability bias.

e/acc is not a coherent philosophy and treating it as one means you are fighting shadows.

Landian accelerationism at least is somewhat coherent. "e/acc" is a bundle of memes that support the self-interest of the people supporting and propagating it, both financially (VC money, dreams of making it big) and socially (the non-Beff e/acc vibe is one of optimism and hope and to do things -- to engage with the object level -- instead of just trying to steer social reality). A more charitable interpretation is that the philosophical roots of "e/acc" are founded upon a frustration with how bad things are, and a desire to improve things by yourself. This is a sentiment I share and empathize with.

I find the term "techno-optimism" to be a more accurate description of the latter, and perhaps "Beff Jezos philosophy" a more accurate description of what you have in your mind. And "e/acc" to mainly describe the community and its coordinated movements at steering the world towards outcomes that the people within the community perceive as benefiting them.

I think I might create a new post using information from this post [AF · GW] which covers the new AI alignment landscape.

I use GreaterWrong as my front-end to interface with LessWrong, AlignmentForum, and the EA Forum. It is significantly less distracting and also doesn't make my ~decade old laptop scream in agony when multiple LW tabs are open on my browser.

Thanks for this post. This is generally how I feel as well, but my (exaggerated) model of the AI aligment community would immediately attack me by saying "if you don't find AI scary, you either don't understand the arguments on AI safety or you don't know how advanced AI has gotten". In my opinion, a few years ago we were concerned about recursively self improving AIs, and that seemed genuinely plausible and scary. But somehow, they didn't really happen (or haven't happened yet) despite people trying all sorts of ways [LW · GW] to make it happen. And instead of a intelligence explosion, what we got was an extremely predictable improvement trend which was a function of only two things i.e. data + compute. This made me qualitatively update my p(doom) downwards, and I was genuinely surprised that many people went the other way instead, updating upwards as LLMs got better.