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AI researchers' wrong theory of cognition is making us worry about the wrong kind of AI apocalypse
_I originally wrote this (in 18 minutes!) as a stream-of-consciousnessMastodon thread. Thought it might be worth putting it all together here though._
“Cognitive task” is an ontological sleight-of-hand used to obscure the distinction between the way a human would perform the task, and the nature of the task itself. This mask is then used to conflate human cognition with what neural networks do, when in fact neural networks only work similarly to a small subset of animal cognition.
For example, doing arithmetic is a “cognitive task” for humans, but nobody (or very few) would argue that a calculator doing the same arithmetic is using cognition to do so.
The thing is, animal cognition is inextricably an embodied process. Affect is not a side-effect of cognition but its root.
The fact that we have computerised the production of plausibly similar outputs as those from animal cognition only means that we anthropomorphise the process that produces those plausible outputs. We wrongly assign intention and goals to AI models like LLMs because we incorrectly assume the nature of their insides based on their outsides.
It is meaningless to talk of AI goals or intent, or at least meaningless to think of them as in any way isomorphic to animal goals or intent, as the mechanism for the production of goals and intent fundamentally does not exist in AI models.
This false theory of cognition is extremely dangerous, because it leads us to waste time on fallacies like AGI/superintelligence wiping out humanity through some misplaced intent + agency. In reality the risk is both more proximate and more mundane than that, and is the same risk that has been playing out for at least hundreds of years.
We have repeatedly demonstrated our willingness to deploy technologies whose socioeconomic impact we do not understand and cannot forecast, in order to obtain a profit.
The AI apocalypse looks much more like an accelerated runaway-IT problem: replacing components of complex socioeconomic infrastructure (that might have previously been driven by people or technology) with AI will cause massive damage.
This damage will come from the unpredictable failure modes of systems that depend on certain kinds of AI, that in a context of complexity will cause harmful ripple effects.
The damage will be exacerbated by (1) the continued substitution of software for people in decision-making where there is an incentive to delegate accountability to a system that can't be questioned, and (2) the proliferation of software problems that are impossible to diagnose and impossible to fix.
The good news about this understanding of the AI apocalypse is that we are not fighting against an emergent superior machine intelligence. We are only fighting the dumbest, greediest instincts our human society produces. And that is something we know how to do.
Happy weekend!
