At Aeon, Berkeley philosophy prof Alva Noë outlines one of the key differences between human thinking and computation. He takes issue with the approach advocated by Alan Turing (1912–1954), where certain steps must be followed if we are to have a computer that talks and thinks like a human. Noë doesn’t think such steps are possible, where language is concerned:

Consider language. We don’t just talk, as it were, following the rules blindly. Talking is an issue for us, and the rules, such as they are, are up for grabs and in dispute. We always, inevitably, and from the beginning, are made to cope with how hard talking is, how liable we are to misunderstand each other, although most of the time this is undertaken matter-of-factly and without undue stress. To talk, almost inevitably, is to question word choice, to demand reformulation, repetition and repair. What do you mean? How can you say that? In this way, talking contains within it, from the start, and as one of its basic modes, the activities of criticism and reflection about talking, which end up changing the way we talk. We don’t just act, as it were, in the flow. Flow eludes us and, in its place, we know striving, argument and negotiation. And so we change language in using language; and that’s what a language is, a place of capture and release, engagement and criticism, a process. We can never factor out mere doing, skilfulness, habit – the sort of things machines are used effectively to simulate – from the ways these doings, engagements and skills are made new, transformed, through our very acts of doing them. These are entangled. This is a crucial lesson about the very shape of human cognition.

If we keep language, the piano, and games in view, and if we don’t lose sight of what I am calling entanglement – the ways in which carrying on is entangled with everything required to deal with just how hard it is to carry on! – then it becomes clear that the AI discussion tends unthinkingly to presuppose a one-sided, peaches-and-cream simplification of human skilfulness and cognitive life. As if speaking were the straightforward application of rules, or playing the piano was just a matter of doing what the manual instructs. But to imagine language users who were not also actively struggling with the problems of talk would be to imagine something that is, at most, the shell or semblance of human life with language. It would, in fact, be to imagine the language of machines (such as LLMs).

“Rage against the machine,” October 25, 2024

Noë is the author of a number of books, including The Entanglement: How Art and Philosophy Make Us What We Are (Princeton University Press 2023). So, not surprisingly, he finishes with “We are not merely word-generators. We are makers of meaning.”

On the topic of the language of machines: Model collapse: AI chatbots are eating their own tails. The problem is fundamental to how they operate. Without new human input, their output starts to decay. Meanwhile, organizations that laid off writers and editors to save money are finding that they can’t just program creativity or common sense into machines.