Section 4 is completely over my head I have to confess. 

Edit: But the abstract gives me what I wanted to know  :)  : "To quantify the capabilities of AI systems in terms of human capabilities, we propose a new metric: 50%-task-completion time horizon. This is the time humans typically take to complete tasks that AI models can complete with 50% success rate"

I don't know of anything better right now. 

It's actually the majority view amongst academics who directly study the issue. (I'm probably an anti-realist though). https://survey2020.philpeople.org/survey/results/486

Thanks, that is reassuring. 

I don't quite get what that means. Do they really take exactly the same amount of time on all tasks for which they have the same success rate? Sorry, maybe I am being annoying here and this is all well-explained in the linked post. But I am trying to figure out how much this is creating the illusion that progress on it means a model will be able to handle all tasks that it takes normal human workers about that amount of time to do, when it really means something quite different.  

"I don't think that, for a given person, existing can be better or worse than not existing. " 

Presumably even given this, you wouldn't create a person who would spending their entire life in terrible agony, begging for death. If that can be a bad thing to do even though existing can't be worse than not existing, then why can't it be a good thing to create happy people, even though existing can't be better than not existing? 

Is the point when models hit a length of time on the x-axis of the graph meant to represent the point where models can do all tasks of that length that a normal knowledge worker could perform on a computer? The vast majority of knowledge worker tasks of that length? At least one task of that length? Some particular important subset of tasks of that length? 

Morally, I am impressed that you are doing an in many ways socially awkward and uncomfortable thing because you think it is right. 

BUT

I strongly object to you citing the Metaculus AGI question as significant evidence of AGI by 2030. I do not think that when people forecast that question, they are necessarily forecasting when AGI, as commonly understood or in the sense that's directly relevant to X-risk will arrive. Yes the title of the question mentions AGI. But if you look at the resolution criteria, all an AI model has to in order to resolve the question 'yes' is pass a couple of benchmarks involving coding and general knowledge, put together a complicated model car, and imitate. None of that constitutes being AGI in the sense of "can replace any human knowledge worker in any job". For one thing, it doesn't involve any task that is carried out over a time span of days or weeks, but we know that memory and coherence over long time scales is something current models seem to be relatively bad at, compared to passing exam-style benchmarks. It also doesn't include any component that tests the ability of models to learn new tasks at human-like speed, which again, seems to be an issue with current models. Now, maybe despite all this, it's actually the case that any model that can pass the benchmark will in fact be AGI in the sense of "can permanently replace almost any human knowledge worker", or at least will obviously only be a 1-2 years of normal research progress away from that. But that is a highly substantive assumption in my view. 

I know this is only one piece of evidence you cite, and maybe it isn't actually a significant driver of your timelines, but I still think it should have been left out. 

Yes. (Though I'm not saying this will happen, just that it could, and that is more significant than a short delay.) 

The more task lengths the 80% threshold has to run through before it gets to task length we'd regard as AGI complete though, the more different the tasks at the end of the sequence are from the beginning, and therefore the more likely it is that the doubling trend will break down somewhere along the length of the sequence. That seems to me like the main significance of titotal's point, not the time gained if we just assume the current 80% doubling trend will continue right to the end of the line. Plausibly 30 seconds to minute long tasks are more different from weeks long tasks than 15 minute tasks are.