But just because AI can perform human-like behaviors doesnt mean it can think or understand like humans.
A widespread misconception
Developments in AI have produced systems that can perform very human-like behaviors.
The language modelGPT-3can produce text thats often indistinguishable from human speech.
Another model,PaLM, can produce explanations for jokes it has neverseen before.
And DALL-E is a system which has been trained to produce modified images and artwork from a text description.
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In all the excitement, its easy to assume human-like behavior means human-like understanding.
But there are several key differences between how AI and humans think and learn.
Neural nets are a highly simplified version of the biology.
Yet there are important differences.
Neural nets are typically trained by supervised learning.
This is very different from how humans typically learn.
We have to work this out ourselves.
Another difference is the sheer scale of data used to train AI.
The GPT-3 model was trained on400 billion words, mostly taken from the internet.
Such calculations show humans cant possibly learn the same way AI does.
We have to make more efficient use of smaller amounts of data.
Instead, humans learn by makingstructured mental concepts, in which many different properties and associations are linked together.
As far as we know, AI systems do not form conceptual knowledge like this.
Theres still much we dont know about how humans learn, understand and reason.
However, what we do know indicates humans perform these tasks very differently to AI systems.
