And they improve at optimisation on the basis of past experience. That, he said with a smile, is intelligence. The audience nodded along approvingly.
Meanwhile, a philosophical alarm bell began sounding in my head. Not because the speaker’s claim was implausible. On the contrary, as a description of much contemporary artificial intelligence, it seemed apt.
AI systems are built around objectives, losses, rewards, predictions, preferences, benchmarks and feedback loops. They are trained to perform better relative to some standard of success. In one form or another, they optimise.
That is a great part of their technical power. What troubled me was the ease with which a definition appropriate to machines sounded like a definition of intelligence as such. That slide from engineering model to human anthropology is easy to miss.
We begin by saying: this is how machines work. Then, almost without noticing, we say: this is what intelligence is. And then, more dangerously still: perhaps this is what we are.
An old argument about human beings had entered the room without announcing itself. It sounded, instead, like a definition. The AI revolution has brought one of the Enlightenment’s deepest quarrels back to life – and made one side of it seem like plain common sense.
Extract — continue reading at the source.
