How much EA analysis of AI safety as a cause area exists?

Then the EA movement formed, and while it was originally focused on causes like global poverty, over time did a bunch of investigative work which led many EAs to become convinced that AI safety matters, and to start working on it directly or indirectly.

Is this a statement that you're endorsing, or is it part of what you're questioning? Are you aware of any surveys or any other evidence supporting this? (I'd accept "most people in AI safety that I know started working in it because EA investigative work convinced them that AI safety matters" or something of that nature.)

b) how much should I update when I learn that a given belief is a consensus in EA?

Why are you trying to answer this, instead of "How should I update, given the results of all available investigations into AI safety as a cause area?" In other words, what is the point of dividing such investigations into "EA" and "not EA", if in the end you just want to update on all of them to arrive at a posterior? Oh, is it because if a non-EA concludes that AI safety is not a worthwhile cause, it might just be because they don't care much about the far future, so EA investigations are more relevant? But if so, why only "partially count" Nick?

Here EAs who started off not being inclined towards transhumanism or rationalism at all count the most, and Nick counts very little.

For this question then, it seems that Paul Christiano also needs to be discounted (and possibly others as well but I'm not as familiar with them).

Interesting posts. Yet I don't see how they support that what I described is unlikely. In particular, I don't see how "easy coordination" is in tension with what I wrote.

To clarify, competition that determines outcomes can readily happen within a framework of shared goals, and as instrumental to some overarching final goal. If the final goal is, say, to maximize economic growth (or if that is an important instrumental goal), this would likely lead to specialization and competition among various agents that try out different things, and which, by the nature of specialization, have imperfect information about what other agents know (not having such specialization would be much less efficient). In this, a future AI economy would resemble ours more than far-mode thinking suggests (this does not necessarily contradict your claim about easier coordination, though).

A reason I consider what I described likely is not least that I find it more likely that future software systems will consist in a multitude of specialized systems with quite different designs, even in the presence of AGI, as opposed to most everything being done by copies of some singular AGI system. This "one system will take over everything" strikes me as far-mode thinking, and not least unlikely given the history of technology and economic growth. I've outlined my view on this in the following e-book (though it's a bit dated in some ways): https://www.smashwords.com/books/view/655938 (short summary and review by Kaj Sotala: https://kajsotala.fi/2017/01/disjunctive-ai-scenarios-individual-or-collective-takeoff/)

Thanks for the stab, Anthony. It's fairly fair. :-)

Some clarifying points:

First, I should note that my piece was written from the perspective of suffering-focused ethics.

Second, I would not say that "investment in AI safety work by the EA community today would only make sense if the probability of AI-catalyzed GCR were decently high". Even setting aside the question of what "decently high" means, I would note that:

1) Whether such investments in AI safety make sense depends in part on one's values. (Though another critique I would make is that "AI safety" is less well-defined than people often seem to think: https://magnusvinding.com/2018/12/14/is-ai-alignment-possible/, but more on this below.)

2) Even if "the probability of AI-catalyzed GCR" were decently high — say, >2 percent — this would not imply that one should focus on "AI safety" in a standard narrow sense (roughly: constructing the right software), nor that other risks are not greater in expectation (compared to the risks we commonly have in mind when we think of "AI-catalyzed catastrophic risks").

You write of "scenarios in which AGI becomes a catastrophic threat". But a question I would raise is: what does this mean? Do we all have a clear picture of this in our minds? This sounds to me like a rather broad class of scenarios, and a worry I have is that we all have "poorly written software" scenarios in mind, although such scenarios could well comprise a relatively narrow subset of the entire class that is "catastrophic scenarios involving AI".

Zooming out, my critique can be crudely summarized as a critique of two significant equivocations that I see doing an exceptional amount of work in many standard arguments for "prioritizing AI".

First, there is what we may call the AI safety equivocation (or motte and bailey): people commonly fail to distinguish between 1) a focus on future outcomes controlled by AI and 2) a focus on writing "safe" software. Accepting that we should adopt the former focus by no means implies we should adopt the latter. By (imperfect) analogy, to say that we should focus on future outcomes controlled by humans does not imply that we should focus primarily on writing safe human genomes.

The second is what we may call the intelligence equivocation, which is the one you described. We operate with two very different senses of the term "intelligence", namely 1) the ability to achieve goals in general (derived from Legg & Hutter, 2007), and 2) "intelligence" in the much narrower sense of "advanced cognitive abilities", roughly equivalent to IQ in humans.

These two are often treated as virtually identical, and we fail to appreciate the rather enormous difference between them, as argued in/evident from books such as The Knowledge Illusion: Why We Never Think Alone, The Ascent of Man, The Evolution of Everything, and The Secret of Our Success. This was also the main point in my Reflections on Intelligence.

Intelligence2 lies all in the brain, whereas intelligence1 includes the brain and so much more, including all the rest of our well-adapted body parts (vocal cords, hands, upright walk — remove just one of these completely in all humans and human civilization is likely gone for good). Not to mention our culture and technology as a whole, which is the level at which our ability to achieve goals at a significant level really emerges: it derives not from any single advanced machine but from our entire economy. A vastly greater toolbox than what intelligence2 covers.

Thus, to assume that we by boosting intelligence2 to vastly super-human levels necessarily get intelligence1 at a vastly super-human level is a mistake, not least since "human-level intelligence1" already includes vastly super-human intelligence2 in many cognitive domains.