> these tools until AI had the common property of being enhancing of human cognition, because they couldn't do the thinking for you

I have a different take, centered around this idea: Not everyone was into thinking about everything all the time even before AI. I'd say most people most of the time outsourced actual thinking to someone else.

1) Reading non-fiction books:

Not all books, even the non-fiction ones, necessarily require any thinking by the reader. A book that narrates history, for example, requires much less thinking than something like "The Road to Reality" or "Godel Escher Bach."

Most of us outsourced the thinking and historical method to the authors of the history book and just passively consumed some facts or factoids. Some of us memorize and remember these factoids well, but that's not thinking, just knowledge storage.

Philosophically, what's the difference between consuming books this way and reading an LLM's output?

2) Reading research papers:

Most people don't read any research papers at all. No thinking there. Most people don't head to some forum to ask about latest research either. Also, researchers in most fields don't come out and do outreach regularly.

Indeed, an LLM may actually be the only pathway for a lot of people to get at least _some_ knowledge and awareness about latest research.

Those of us in scientific, engineering, humanities, healthcare fields may read some to many papers. But only a small subset reads very critically, looking for data errors, inconsistencies, etc. For most of us, the knowledge and techniques may be beyond our current understanding and possibly without any interest in understanding them in future either.

Most of us are just interested in the observations or conclusions or applications. Those may involve some thinking but also may not involve any thinking, just blind acceptance of the paper's claims and possible applications.

3) Coding:

Again, deep thinking is only done by a small set of programmers. Like the ones who write kernels, compilers, distributed algorithms, complex libraries.

But most are just passive consumers who read some examples online or ask stackoverflow or reddit for direct answers. Some even outsource all their coding entirely to gig sites. Not much thinking there except pricing and scheduling. What's the difference between that and asking an LLM or copying an LLM's answers? At least, the LLMs patiently explain their code, unlike salty SO users!

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IMO, most people weren't doing much thinking even pre-AI.

Post-AI, it's true that some people who did do some thinking may reduce it.

But it's equally true that those people who weren't doing much thinking due to access or language barriers can actually start doing some thinking now with the help of AI.