I think that part of why Eliezer’s early stuff sounds weird is:
He generally had a lower opinion of the competence of elites in business, science, etc. (Which he later updated about.)
He had a lower opinion of the field of AI in particular, as it existed in the 1990s and 2000s. Maybe more like nutrition science or continental philosophy than like chemistry, on the scale of ‘field rigor and intellectual output’.
If you think of A(G)I as a weird, neglected, pre-paradigmatic field that gets very little attention outside of science fiction writing, then it’s less surprising to think it’s possible to make big, fast strides in the field. Outperforming a competitive market is very different from outperforming a small, niche market where very little high-quality effort is going into trying new things.
Similarly, if you have a lower opinion of elites, you should be more willing to endorse weird, fringe ideas, because you should be less confident that the mainstream is efficient relative to you. (And I think Eliezer still has a low opinion of elites on some very important dimensions, compared to a lot of EAs. But not to the same degrees as teenaged Eliezer.)
I used to think—not from experience, but from the general memetic atmosphere I grew up in—that executives were just people who, by dint of superior charisma and butt-kissing, had managed to work their way to the top positions at the corporate hog trough.
No, that was just a more comfortable meme, at least when it comes to what people put down in writing and pass around. The story of the horrible boss gets passed around more than the story of the boss who is, not just competent, but more competent than you.
[...]
But the business world is not the only venue where I’ve encountered the upper echelons and discovered that, amazingly, they actually are better at what they do.
Case in point: Professor Rodney Brooks, CTO of iRobot and former director of the MIT AI Lab, who spoke at the 2007 Singularity Summit. I had previously known “Rodney Brooks” primarily as the promoter of yet another dreadful nouvelle paradigm in AI—the embodiment of AIs in robots, and the forsaking of deliberation for complicated reflexes that didn’t involve modeling. Definitely not a friend to the Bayesian faction. Yet somehow Brooks had managed to become a major mainstream name, a household brand in AI...
And by golly, Brooks sounded intelligent and original. He gave off a visible aura of competence.
At one of the first conferences organized around the tiny little subfield of Artificial General Intelligence, I met someone who was heading up a funded research project specifically declaring AGI as a goal, within a major corporation. I believe he had people under him on his project. He was probably paid at least three times as much as I was paid (at that time). His academic credentials were superior to mine (what a surprise) and he had many more years of experience. He had access to lots and lots of computing power.
And like nearly everyone in the field of AGI, he was rushing forward to write code immediately—not holding off and searching for a sufficiently precise theory to permit stable self-improvement.
In short, he was just the sort of fellow that… Well, many people, when they hear about Friendly AI, say: “Oh, it doesn’t matter what you do, because [someone like this guy] will create AI first.” He’s the sort of person about whom journalists ask me, “You say that this isn’t the time to be talking about regulation, but don’t we need laws to stop people like this from creating AI?”
“I suppose,” you say, your voice heavy with irony, “that you’re about to tell us, that this person doesn’t really have so much of an advantage over you as it might seem. Because your theory—whenever you actually come up with a theory—is going to be so much better than his. Or,” your voice becoming even more ironic, “that he’s too mired in boring mainstream methodology—”
No. I’m about to tell you that I happened to be seated at the same table as this guy at lunch, and I made some kind of comment about evolutionary psychology, and he turned out to be...
...a creationist.
This was the point at which I really got, on a gut level, that there was no test you needed to pass in order to start your own AGI project.
One of the failure modes I’ve come to better understand in myself since observing it in others, is what I call, “living in the should-universe”. The universe where everything works the way it common-sensically ought to, as opposed to the actual is-universe we live in. There’s more than one way to live in the should-universe, and outright delusional optimism is only the least subtle. Treating the should-universe as your point of departure—describing the real universe as the should-universe plus a diff—can also be dangerous.
Up until the moment when yonder AGI researcher explained to me that he didn’t believe in evolution because that’s not what the Bible said, I’d been living in the should-universe. In the sense that I was organizing my understanding of other AGI researchers as should-plus-diff. I saw them, not as themselves, not as their probable causal histories, but as their departures from what I thought they should be.
[...] When Scott Aaronson was 12 years old, he: “set myself the modest goal of writing a BASIC program that would pass the Turing Test by learning from experience and following Asimov’s Three Laws of Robotics. I coded up a really nice tokenizer and user interface, and only got stuck on the subroutine that was supposed to understand the user’s question and output an intelligent, Three-Laws-obeying response.” It would be pointless to try and construct a diff between Aaronson12 and what an AGI researcher should be. You’ve got to explain Aaronson12 in forward-extrapolation mode: He thought it would be cool to make an AI and didn’t quite understand why the problem was difficult.
It was yonder creationist who let me see AGI researchers for themselves, and not as departures from my ideal.
[...]
The really striking fact about the researchers who show up at AGI conferences, is that they’re so… I don’t know how else to put it...
More like… around, say, the level of above-average scientists, which I yesterday compared to the level of partners at a non-big-name venture capital firm. Some of whom might well be Christians, or even creationists if they don’t work in evolutionary biology.
The attendees at AGI conferences aren’t literally average mortals, or even average scientists. The average attendee at an AGI conference is visibly one level up from the average attendee at that random mainstream AI conference I talked about yesterday.
[...] But even if you just poke around on Norvig or McCarthy’s website, and you’ve achieved sufficient level yourself to discriminate what you see, you’ll get a sense of a formidable mind. Not in terms of accomplishments—that’s not a fair comparison with someone younger or tackling a more difficult problem—but just in terms of the way they talk. If you then look at the website of a typical AGI-seeker, even one heading up their own project, you won’t get an equivalent sense of formidability.
[...] If you forget the should-universe, and think of the selection effect in the is-universe, it’s not difficult to understand. Today, AGI attracts people who fail to comprehend the difficulty of AGI. Back in the earliest days, a bright mind like John McCarthy would tackle AGI because no one knew the problem was difficult. In time and with regret, he realized he couldn’t do it. Today, someone on the level of Peter Norvig knows their own competencies, what they can do and what they can’t; and they go on to achieve fame and fortune (and Research Directorship of Google) within mainstream AI.
And then...
Then there are the completely hopeless ordinary programmers who wander onto the AGI mailing list wanting to build a really big semantic net.
Or the postdocs moved by some (non-Singularity) dream of themselves presenting the first “human-level” AI to the world, who also dream an AI design, and can’t let go of that.
Just normal people with no notion that it’s wrong for an AGI researcher to be normal.
Indeed, like most normal people who don’t spend their lives making a desperate effort to reach up toward an impossible ideal, they will be offended if you suggest to them that someone in their position needs to be a little less imperfect.
This misled the living daylights out of me when I was young, because I compared myself to other people who declared their intentions to build AGI, and ended up way too impressed with myself; when I should have been comparing myself to Peter Norvig, or reaching up toward E. T. Jaynes. (For I did not then perceive the sheer, blank, towering wall of Nature.)
I don’t mean to bash normal AGI researchers into the ground. They are not evil. They are not ill-intentioned. They are not even dangerous, as individuals. Only the mob of them is dangerous, that can learn from each other’s partial successes and accumulate hacks as a community.
And that’s why I’m discussing all this—because it is a fact without which it is not possible to understand the overall strategic situation in which humanity finds itself, the present state of the gameboard. It is, for example, the reason why I don’t panic when yet another AGI project announces they’re going to have general intelligence in five years. It also says that you can’t necessarily extrapolate the FAI-theory comprehension of future researchers from present researchers, if a breakthrough occurs that repopulates the field with Norvig-class minds.
Even an average human engineer is at least six levels higher than the blind idiot god, natural selection, that managed to cough up the Artificial Intelligence called humans, by retaining its lucky successes and compounding them. And the mob, if it retains its lucky successes and shares them, may also cough up an Artificial Intelligence, with around the same degree of precise control. But it is only the collective that I worry about as dangerous—the individuals don’t seem that formidable.
If you yourself speak fluent Bayesian, and you distinguish a person-concerned-with-AGI as speaking fluent Bayesian, then you should consider that person as excepted from this whole discussion.
Of course, among people who declare that they want to solve the AGI problem, the supermajority don’t speak fluent Bayesian.
Why would they? Most people don’t.
I think this, plus Eliezer’s general ‘fuck it, I’m gonna call it like I see it rather than be reflexively respectful to authority’ attitude, explains most of Ben’s ‘holy shit, your views were so weird!!’ thing.
I think that part of why Eliezer’s early stuff sounds weird is:
He generally had a lower opinion of the competence of elites in business, science, etc. (Which he later updated about.)
He had a lower opinion of the field of AI in particular, as it existed in the 1990s and 2000s. Maybe more like nutrition science or continental philosophy than like chemistry, on the scale of ‘field rigor and intellectual output’.
If you think of A(G)I as a weird, neglected, pre-paradigmatic field that gets very little attention outside of science fiction writing, then it’s less surprising to think it’s possible to make big, fast strides in the field. Outperforming a competitive market is very different from outperforming a small, niche market where very little high-quality effort is going into trying new things.
Similarly, if you have a lower opinion of elites, you should be more willing to endorse weird, fringe ideas, because you should be less confident that the mainstream is efficient relative to you. (And I think Eliezer still has a low opinion of elites on some very important dimensions, compared to a lot of EAs. But not to the same degrees as teenaged Eliezer.)
From Competent Elites:
And from Above-Average AI Scientists:
I think this, plus Eliezer’s general ‘fuck it, I’m gonna call it like I see it rather than be reflexively respectful to authority’ attitude, explains most of Ben’s ‘holy shit, your views were so weird!!’ thing.