LLMs as Reading Assistants

Bill Wakik in the NY Times:

Like most people who work with words for a living, I’ve watched the rise of large-language models with a combination of fascination and horror, and it makes my skin crawl to imagine one of them writing on my behalf. But there is, I confess, something seductive about the idea of letting A.I. read for me — considering how cruelly the internet-era explosion of digitized text now mocks nonfiction writers with access to more voluminous sources on any given subject than we can possibly process. This is true not just of present-day subjects but past ones as well: Any history buff knows that a few hours of searching online, amid the tens of millions of books digitized by Google, the endless trove of academic papers available on JSTOR, the newspaper databases that let you keyword-search hundreds of publications on any given day in history, can cough up months’ or even years’ worth of reading material. It’s impossible to read it all, but once you know it exists, it feels irresponsible not to read it.

What if you could entrust most of that reading to someone else … or something else? As A.I. becomes more capable of parsing large data sets, it seems inevitable that historians and other nonfiction writers will turn to it for assistance; in fact, as I discovered in surveying a wide variety of historians over the last few months, experiments with it are already far more common than I expected. But it also seems inevitable that this power to help search and synthesize historical texts will change the kinds of history books that are written. If history, per the adage, is written by the winners, then it’s not premature to wonder how the winners of the A.I. race might soon shape the stories that historians tell about the past.

Maybe I'll start my retirement by trying this to jumpstart my long-imagined book on poison in history. I always imagined I would have to team with a chemist who understood that side, but maybe I could get an AI to do it for me.