Levels of AGI: Operationalizing Progress on the Path to AGI

For some, it's simply Artificial and Generally Intelligent(perform many tasks, adapt). For some, it might mean any that it needs to do everything a normal human can. For some, non-biological life axiomatically cannot become AGI. For some, it must be "conscious" and "sentient".

For some, it might require literal omniscience and omnipotence and accepting anything as AGI means, to them, that they are being told to worship it as a God. For some, it might mean something more like an AI that is more competent than the most competent human at literally every task.

For some, acknowledging it means that we must acknowledge it has person-like rights. For some it cannot be AGI if it lies. For some it cannot be AGI if it makes any mistake. For some it cannot be AGI until it has more power than humans. These are several definitions and implications that are partially or wholly mutually conflicting but I have seen different people say that AGI is each different one of those.

That sents the bar unreasonably high in my opinion. Almost all of humanity does not have skills 'better than 50% of skilled adults' by definition and those definitely qualify as generally intelligent.

It's clear that they mean human capabilities unaugmented by AI.

Wow, what a massive jump between Level 0 and Level 2. They state that their goal is to help facilitate conversation within the community but I feel like such a gap very obviously does not help. The arguments are specifically within these regions and we're less concerned about arguing if a 50th percentile general AI is AGI vs a 99th percentile. It's only the hype people (e.g. X-risk and Elon (who has no realistic qualifications here)) who are discussing those levels.

I know whatever you define things as people will be upset and argue, but the point of a work like this is to just make something we can all point to and be a place to refine from, even if messy. But with this large of a gap it makes such refinement difficult and I do not suspect we'll be using these terms as we move forward. After all, with most technology the approach is typically slow before accelerating (since there's a momentum factor). A lot of the disagreement in the community is if we're in the bottom part of the S curve or at the beginning of the exponential part. I have opinions but no one really knows, so that's where we need flags placed to reduce stupid fights (fights that can be significantly reduced by recognizing we're not using the same definitions but assuming the other person is).

I still find that a weird definition for two reasons:

1. All the narrow systems already have replaced humans in many real-word tasks.

2. I'm dubious there is much difference between a level 2 and level 4 general AI. And outperforming a % of humans seems like an odd metric, given that humans have diverse skill sets. A more sane metric would be Nth percentile for M% of tasks human workers perform in 2023.

That's a speculative claim because we don't really know what's involved. We could be one simple generalization trick away, which wouldn't be very significant in terms of effort, just effect.

Other than a system allowing play, they become superhuman purely through self play.

A benchmark for any AGI system is how fast it can learn from sparse unlabeled data and generalize.

https://kotaku.com/humans-triumph-over-machines-in-protein-f...

I mean, they put GPT-4 ("SOTA LLMs") for a subset of tasks at Level 2N, a spell checker at Level 3N, and chess and Go solvers at Levels 4N and 5N. It feels to me that any useful grading scheme would give the opposite ordering. Sure, the current classification meets their definitions - "outperforms X% humans" - but at least with chess and Go, the rating is dominated entirely by the fact that very few people play these games at non-joke level, and the activity itself is super specific, and super narrowly scoped, mathematically speaking. Feels almost like calling CPUs Level 5N at "adding numbers together", since they clearly outperform 100% of humans at that. Or, much less jokingly, one could convincingly argue a PID controller is Level 5 Narrow, because not only it's going to be outperforming 100% of humans at its task, it's also learning and adapting (within its operational envelope).

I think "general" needs to be more than a boolean though: The standard "wide range of non-physical tasks, including metacognitive abilities like learning new skills" is met by ChatGPT (as in the chart), which is much better in some languages than others, and at some tasks than others.

But how wide does it have to be to count as "wide"? A brain upload of any human ought to count, but most of us have much less breadth than any LLM.

Any levels of insanity that makes people believe such statements?

Historically, this has frequently included refusing to accept $outgroup are real people with any subjective experience (or at least, any that matters).

I'd like us to do better — not that I can actually suggest any test that would do this objectively, but I would like us to do better.

What methods? Are there any? Is there suddenly some consensus among philosophers about the p-zombie thought experiment?

AFAIK effectively the best we can do is (a) ascertain that you yourself are a conscious entity with subjective experience and then (b) assume - with no way to ascertain that - that the humans around you are like you.

It's rarely unethical to do something that is easily reversed or that causes no harm. That's pretty likely to be the case with any AI...we can checkpoint their memory, or whatever.

So, right or wrong, I think our current ethical standards will lead us to believe that we can do anything we like to an AI that is operating in a temporary-memory mode, and any harm caused could be easily reset like it never happened.