There are so many examples of insanely demanding AGI definitions^[1] or criteria, typically involving, among other things, the ability to do something that only human geniuses can do. Usually, these criteria stem from a requirement that AGI be able to do anything any human can do. In extreme cases, people even require abilities that no humans have. I guess it's not AGMI (Artificial Gary Marcus Intelligence) unless it can multiply numbers of arbitrary size, solve the hard problem of consciousness, and more, all simultaneously.

Defining AGI as something capable of doing anything a human can do on a computer naively sounds like requiring normal human-level ability. This isn't true. The issue is that there's a huge range of variation within human ability; many things that Einstein could do are totally beyond the ability of the vast majority of people. Requiring AGI to have the abilities of any human inadvertently requires it to have the abilities of a genius, creating a definition that has almost nothing to do with typical human ability. This leads to an accidental sleight-of-hand: AGI gets to be framed as a human-level milestone, then claimed to be massively distant because current models are nowhere near a threshold that almost no humans meet either. 

This is insane: AGI has ballooned into a standard that has almost nothing to do with being a general intelligence, capable of approaching a wide variety of novel problems. Almost all (maybe all, since no one has world-class abilities in all regards) of the quintessential examples of general intelligence – people – woefully fail to qualify.

Any definition of general intelligence should include at least the average human, and arguably most humans. Indeed, there's a legitimate question of whether it should require the ability to do all cognitive tasks average humans can do, or just average human-level reasoning ability. To clarify, I use strong AGI to describe a system that can do everything the average person can do on a computer, in contrast to weak AGI, which only has human level-reasoning, and might lack things like long-term memory, perception, "online learning" ability, etc. I'd use baby AGI to describe a system with novel problem-solving ability well into the human range, even if below average; this clearly exists today.

Use-words-sensibly justifications aside, these more modest definitions help show the deeply worrying rate of recent progress. Instead of the first major milestone term being a long way off and allowing us to forget how close we are to both a very impactful (though likely not earth-shattering) capability and a somber omen, we are confronted with tangible developments: baby AGI is no older than two^[2], and weak AGI seems to be almost here.

There are also similar advantages for public awareness. As some of those examples linked in the first line show, absurdly demanding AGI definitions create equally absurd levels of confusion, even among people with a modest knowledge of the subject – they stand to do even more damage to the mostly uninformed public.

In response to all this, you might be thinking that a system capable of doing everything any (i.e. the smartest) humans can do is an even more important milestone, and deserves a clear label. We already have a term for this: ASI. If you prefer to differentiate between a system on par with the best humans and one far above them, use weak ASI and strong ASI respectively. My strong suspicion is that, if either of these ever exists (within a reasonable compute budget) and is misaligned, we're going to get wrecked, and it likely doesn't matter much which one. The two are a natural category.

 If we keep saying "it's not AGI" until it flattens us, things aren't likely to go well. This one's not that hard.

1. ^{^}

   Most of these links were found fairly quickly with the aid of o3. The article was otherwise totally human-written.

2. ^{^}

   I'm unsure whether the first baby AGI was GPT-4 or an early LRM, leaning slightly towards the latter.