With regards to the AGI timeline, it’s important to note that Metaculus’ resolution criteria are quite different from a ‘standard’ interpretation of what would constitute AGI[1], (or human-level AI[2], superintelligence[3], transformative AI, etc.). It’s also unclear what proportion of forecasters have read this fine print (interested to hear others’ views on this), which further complicates interpretation.
For these purposes we will thus define “an artificial general intelligence” as a single unified software system that can satisfy the following criteria, all easily completable by a typical college-educated human.
Able to reliably pass a Turing test of the type that would win the Loebner Silver Prize.
Able to score 90% or more on a robust version of the Winograd Schema Challenge, e.g. the “Winogrande” challenge or comparable data set for which human performance is at 90+%
Be able to score 75th percentile (as compared to the corresponding year’s human students; this was a score of 600 in 2016) on all the full mathematics section of a circa-2015-2020 standard SAT exam, using just images of the exam pages and having less than ten SAT exams as part of the training data. (Training on other corpuses of math problems is fair game as long as they are arguably distinct from SAT exams.)
Be able to learn the classic Atari game “Montezuma’s revenge” (based on just visual inputs and standard controls) and explore all 24 rooms based on the equivalent of less than 100 hours of real-time play (see closely-related question.)
By “unified” we mean that the system is integrated enough that it can, for example, explain its reasoning on an SAT problem or Winograd schema question, or verbally report its progress and identify objects during videogame play. (This is not really meant to be an additional capability of “introspection” so much as a provision that the system not simply be cobbled together as a set of sub-systems specialized to tasks like the above, but rather a single system applicable to many problems.)
Agreed, I’ve been trying to help out a bit with Matt Barnett’s new question here. Feedback period is still open, so chime in if you have ideas!
I suspect most Metaculites are accustomed to paying attention to how a question’s operationalization deviates from its intent FWIW. Personally, I find the Montezuma’s revenge criterion quite important without which the question would be far from AGI.
My intent with bringing up this question, was more to ask about how Linch thinks about the reliability of long-term predictions with no obvious frequentist-friendly track record to look at.
With regards to the AGI timeline, it’s important to note that Metaculus’ resolution criteria are quite different from a ‘standard’ interpretation of what would constitute AGI[1], (or human-level AI[2], superintelligence[3], transformative AI, etc.). It’s also unclear what proportion of forecasters have read this fine print (interested to hear others’ views on this), which further complicates interpretation.
OpenAI Charter
expert survey
Bostrom
Agreed, I’ve been trying to help out a bit with Matt Barnett’s new question here. Feedback period is still open, so chime in if you have ideas!
I suspect most Metaculites are accustomed to paying attention to how a question’s operationalization deviates from its intent FWIW. Personally, I find the Montezuma’s revenge criterion quite important without which the question would be far from AGI.
My intent with bringing up this question, was more to ask about how Linch thinks about the reliability of long-term predictions with no obvious frequentist-friendly track record to look at.