Is Writing Computationally Easy?

Recently, a colleague asked if we agreed or disagreed with this quote from an article by Stephen Wolfram entitled What Is ChatGPT Doing...and Why Does It Work:

"And instead what we should conclude is that tasks—like writing essays—that we humans could do, but we didn’t think computers could do, are actually in some sense computationally easier than we thought."

 I would have to disagree because this pronouncement is vague and the terms and premises are ill-defined.

For one example, what is "computationally easier"?:

"Lambda labs estimated a hypothetical cost of around $4.6 million US dollars and 355 years to train GPT-3 on a single GPU in 2020, with lower actual training time by using more GPUs in parallel."

This extensive training was done by reading almost 500 BILLION words. Doesn't sound easy to me.

Also, the statement seems to imply the premise that if humans can do it, then it must be "easy". I doubt anyone who studies human cognition (e.g., psychologist, linguists, cognitive scientists) would agree with this. It took me at least 14 years of varied cognitive training to learn to write an essay, and my mother was an English teacher.

Also, are LLMs really "writing essays"? Perhaps...if you define "writing an essay", narrowly, as regurgitating words and phrases that humans have written and stringing them together using correct syntax and grammar. But when humans write an essay they are engaging in an act of linguistic communication with other humans. A good writer first thinks critically about a topic and then writes with a communicative goal; such as providing a unique perspective or convincing a reader of some particular point. LLMs are decidedly NOT doing that and therein lies the danger.

Because what LLMs generate looks like what humans produce, it is extremely easy for people to be misled into believing that they must be engaged in intelligent activities such as thinking, imagining, judging, arguing, and believing. Cognitive psychologists call this "over-attribution" and it has been a problem for psychology for a very long time.

See this blog by Gary Marcus about the (growing) over-attribution problem in AI.