A Worrying Proposition
AI doomerism is all the rage these days.1 Automated authoritarian systems of oppression, self-replicating killer intelligences, and widespread economic collapse seem to be top of mind in particular. Beloved researchers like Geoffrey Hinton now argue that artificial neural networks—their life’s work—can mean the end of humanity, unless their risks are carefully and properly managed.
These conversations are worth having. But, I worry that rampant sensationalism might be detracting from a more mundane, more likely, and, in many ways, more worrying reality. What it means to be human is in a state of flux.
With high confidence, every person born today onwards will spend their entire life dumber2 than a large language model (LLM). At no point in their life will they outperform a state-of-the-art LLM in any cognitive task. As they grow up and learn, so too will the models.
Generously, humans have been around for no more than 300,000 years. We’re a young species. Assuming we stick around for as long as species usually do, most humans haven’t actually been born yet. By extension, most humans that will ever live will spend their entire lives dumber than an LLM.
What effects does this have on society? On a real-world, individual level, what effects does this have on the human experience?
Featherless Bipeds that Play Chess or Something
I’ll put on my optimist hat for a moment.
What it means to be human has never been static. Many millennia ago, perhaps the most human humans were the best subsistence hunters. Some time in the past, chess playing was a defining characteristic—machines got good at it, and we decided to move to tool use. We realized chimpanzees and corvids were good at that, and now we proudly proclaim that sophisticated language and “cognition” is our human bastion.
It’s always been a moving goal post, affected by new areas where we’ve begun to uniquely excel as a species and old abilities that we’ve realized aren’t so special anymore. Although “cognition” feels uniquely human, I suspect we’re suffering from recency bias. Maybe we’ll run out of special things to cling to eventually, but, for the time being, I propose the following infinitely viable goalpost:
The defining human trait is constructing cognitive agents. Should those cognitive agents construct cognitive agents of their own, the defining human trait is constructing cognitive agents that construct cognitive agents of their own. Repeat ad infinitum.
Hooray! We’re special, forever. Now I can sleep at night. Back to my pessimist hat.
Caution! Local Minima.
I’m not intrinsically worried about the shifting goal post of what it means to be human. Most members of our species aren’t arm chair philosophers, and I suspect such “human-ness” revelations will not have material implications at a societal level.
That said, I am worried. Humans generally don’t like doing things that they’re bad at, or that machines do better than them. Just like many young students wonder “why do I need to learn math if the calculator can do it for me,”3 I worry that new generations of students will now wonder “why do I need to learn [insert literally any cognitive task] if the LLM can do it for me?”
Of course, these are ridiculous statements to make. Calculators are better are rote arithmetic than humans, but you need to understand rote arithmetic before you can understand all the beautiful higher level math that humans are better than calculators at. Nonetheless, it’s a local minima that catches many students early on and makes them discontinue their math education, unable to see the point.
LLMs spawn a massive minefield of local minima, threatening to demotivate the next generation of students in a drastic, incomprehensible way. I find the LLM local minima uniquely large in both breadth and depth.
How many thinkers, writers, programmers, and mathematicians will we lose?
Granted, the conversation hasn’t been totally one-sided. Plenty have rushed to silence the naysayers, arguing that important technological developments often engender complicated, worrying feelings but uniformly end up being hugely beneficial.
By any standard measure of intelligence.
I don’t want to neglect the fact that many people also discontinue their math education due to the extremely unpalatable and poor ways in which the material is generally communicated.
"LLMs spawn a massive minefield of local minima"
Hypothesizing on the "extrema" -- If you take a child with boundless curiosity and give them an AI teddy bear "trained" in the socratic method, you probably also produce some geniuses.