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PaperclipPerfector  1yr ago (text post)   30032 thread views

Culture War Roundup for the week of May 8, 2023

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Decent post with an overview of Yud's predictions: On Deference and Yudkowsky's AI Risk Estimates.

In general Yud was always confident, believing himself to know General High-Level Reasons for things to go wrong if not for intervention in the direction he advises, but his nontrivial ideas were erroneous, and his correct ideas were trivial in that many people in the know thought the same, but they're not niche nerd celebrities. E.g. Legg in 2009:

My guess is that sometime in the next 10 years developments in deep belief networks, temporal graphical models, … etc. will produce sufficiently powerful hierarchical temporal generative models to essentially fill the role of cortex within an AGI.… my mode is about 2025… 90% credibility region … 2018 to 2036

Hanson was sorta-correct about data, compute and human imitation.

Meanwhile Yud called protein folding, but thought that'll already need an agentic AGI who'll develop it to mind-rape us.

Or how's that:, Yud-2021 I expect world GDP to tick along at roughly the current pace, unchanged in any visible way by the precursor tech to AGI; until, on the most probable outcome, everybody falls over dead in 3 seconds after diamondoid bacteria release botulinum into our blood

But Yud has clout; so people praise him for Big Picture Takes and hail him as a Genius Visionary.

Excerpts:

At least up until 1999, admittedly when he was still only about 20 years old, Yudkowsky argued that transformative nanotechnology would probably emerge suddenly and soon (“no later than 2010”) and result in human extinction by default. My understanding is that this viewpoint was a substantial part of the justification for founding the institute that would become MIRI; the institute was initially focused on building AGI, since developing aligned superintelligence quickly enough was understood to be the only way to manage nanotech risk…

I should, once again, emphasize that Yudkowsky was around twenty when he did the final updates on this essay. In that sense, it might be unfair to bring this very old example up.

Nonetheless, I do think this case can be treated as informative, since: the belief was so analogous to his current belief about AI (a high outlier credence in near-term doom from an emerging technology), since he had thought a lot about the subject and was already highly engaged in the relevant intellectual community, since it's not clear when he dropped the belief, and since twenty isn't (in my view) actually all that young.

In 2001, and possibly later, Yudkowsky apparently believed that his small team would be able to develop a “final stage AI” that would “reach transhumanity sometime between 2005 and 2020, probably around 2008 or 2010.”

In the first half of the 2000s, he produced a fair amount of technical and conceptual work related to this goal. It hasn't ultimately had much clear usefulness for AI development, and, partly on the basis, my impression is that it has not held up well - but that he was very confident in the value of this work at the time.

The key points here are that:

  • Yudkowsky has previously held short AI timeline views that turned out to be wrong
  • Yudkowsky has previously held really confident inside views about the path to AGI that (at least seemingly) turned out to be wrong
  • More generally, Yudkowsky may have a track record of overestimating or overstating the quality of his insights into AI

Although I haven’t evaluated the work, my impression is that Yudkowsky was a key part of a Singularity Institute effort to develop a new programming language to use to create “seed AI.” He (or whoever was writing the description of the project) seems to have been substantially overconfident about its usefulness. From the section of the documentation titled “Foreword: Earth Needs Flare” (2001):

…Flare was created under the auspices of the Singularity Institute for Artificial Intelligence, an organization created with the mission of building a computer program far before its time - a true Artificial Intelligence. Flare, the programming language they asked for to help achieve that goal, is not that far out of time, but it's still a special language.”*

A later piece of work which I also haven’t properly read is “Levels of Organization in General Intelligence.” At least by 2005, going off of Yudkowsky’s post “So You Want to be a Seed AI Programmer,” it seems like he thought a variation of the framework in this paper would make it possible for a very small team at the Singularity Institute to create AGI

In his 2008 "FOOM debate" with Robin Hanson, Yudkowsky confidentally staked out very extreme positions about what future AI progress would look like - without (in my view) offering strong justifications. The past decade of AI progress has also provided further evidence against the correctness of his core predictions.

When we try to visualize how all this is likely to go down, we tend to visualize a scenario that someone else once termed “a brain in a box in a basement.” I love that phrase, so I stole it. In other words, we tend to visualize that there’s this AI programming team, a lot like the sort of wannabe AI programming teams you see nowadays, trying to create artificial general intelligence, like the artificial general intelligence projects you see nowadays. They manage to acquire some new deep insights which, combined with published insights in the general scientific community, let them go down into their basement and work on it for a while and create an AI which is smart enough to reprogram itself, and then you get an intelligence explosion…. (p. 436)

When pressed by his debate partner, regarding the magnitude of the technological jump he was forecasting, Yudkowsky suggested that economic output could at least plausibly rise by twenty orders-of-magnitude within not much more than a week - once the AI system has developed relevant nanotechnologies (pg. 400).[8]

I think it’s pretty clear that this viewpoint was heavily influenced by the reigning AI paradigm at the time, which was closer to traditional programming than machine learning. The emphasis on “coding” (as opposed to training) as the means of improvement, the assumption that large amounts of compute are unnecessary, etc. seem to follow from this. A large part of the debate was Yudkowsky arguing against Hanson, who thought that Yudkowsky was underrating the importance of compute and “content” (i.e. data) as drivers of AI progress. Although Hanson very clearly wasn’t envisioning something like deep learning either[9], his side of the argument seems to fit better with what AI progress has looked like over the past decade.

In my view, the pro-FOOM essays in the debate also just offered very weak justifications for thinking that a small number of insights could allow a small programming team, with a small amount of computing power, to abruptly jump the economic growth rate up by several orders of magnitude:

  • It requires less than a gigabyte to store someone’s genetic information on a computer (p. 444).[11]
  • The brain “just doesn’t look all that complicated” in comparison to human-made pieces of technology such as computer operating systems (p.444), on the basis of the principles that have been worked out by neuroscientists and cognitive scientists.
  • There is a large gap between the accomplishments of humans and chimpanzees, which Yudkowsky attributes this to a small architectural improvement
  • Although natural selection can be conceptualized as implementing a simple algorithm, it was nonetheless capable of creating the human mind

In the mid-2010s, some arguments for AI risk began to lean heavily on “coherence arguments” (i.e. arguments that draw implications from the von Neumann-Morgenstern utility theorem) to support the case for AI risk. See, for instance, this introduction to AI risk from 2016, by Yudkowsky, which places a coherence argument front and center as a foundation for the rest of the presentation.

However, later analysis has suggested that coherence arguments have either no or very limited implications for how we should expect future AI systems to behave. See Rohin Shah’s (I think correct) objection to the use of “coherence arguments” to support AI risk concerns. See also similar objections by Richard Ngo and Eric Drexler (Section 6.4).

…in conclusion, I think I'm starting to understand another layer of Krylov's genius. He had this recurring theme in his fictional work, which I considered completely meta-humorous, that The Powers That Be inject particular notions into popular science fiction, to guide the development of civilization towards tyranny. Complete self-serving nonsense, right? But here we have a regular sci-fi fan donning the mantle of AI Safety Expert and forcing absolutely unoriginal, age-old sci-fi/jorno FUD into the mainstream, once technology does in fact get close to the promised capability and proves benign. Grey goo (to divest from actually promising nanotech), AI (to incite the insane mob to attempt a Butlerian Jihad, and have regulators intervene, crippling decentralized developments). Everything's been prepped in advance, starting with Samuel Butler himself.

Feels like watching Ronnie O'Sullivan in his prime.

He seems like a character out of a Kurt Vonnegut novel

Us tinfoil hatters call it "negative priming".

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