TV’s War With the Robots Is Already Here

A.I. screenwriting, a point of contention in the Writers Guild strike, may not yet be ready for prime time. But streaming algorithms and derivative programming have prepared the way for it.

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By James Poniewozik

Television loves a good sentient-machine story, from “Battlestar Galactica” to “Westworld” to “Mrs. Davis.” With the Writers Guild of America strike, that premise has broken the fourth wall. The robots are here, and the humans are racing to defend against them, or to ally with them.

Among the many issues in the strike is the union’s aim to “regulate use of material produced using artificial intelligence or similar technologies,” at a time when the ability of chatbots to auto-generate all manner of writing is growing exponentially.

In essence, writers are asking the studios for guardrails against being replaced by A.I., having their work used to train A.I. or being hired to punch up A.I.-generated scripts at a fraction of their former pay rates.

The big-ticket items in the strike involve, broadly, how the streaming model has disrupted the ways TV writers have made a living. But it’s the A.I. question that has captured imaginations, understandably so. Hollywood loves robot stories because they make us confront what distinguishes us as human. And when it comes to distinguishing features, the ability to conjure imaginary worlds is simply sexier than the opposable thumb.

So the prospect of A.I. screenwriting has become potent, both as threat and rallying cry. Detractors of the striking writers taunted them on social media that software was going to horse-and-buggy their livelihoods. Striking WGA members workshopped A.I. jokes on their picket signs, like “ChatGPT doesn’t have childhood trauma.” (Well, it doesn’t have its own. It has Sylvia Plath’s, and that of any other former unhappy child whose writing survives in machine-readable form.)

But it shouldn’t surprise anyone if the TV business wants to leave open the option of relying on machine-generated entertainment. In a way, it already does.

Not in the way the WGA fears — not yet. Even the most by-the-numbers scripted drama you watch today was not written by a computer program. But it might have been recommended to you by one.

Algorithms, the force behind your streaming-TV “For You” menu, are in the business of noticing what you like and matching you with acceptable-enough versions of it. To many, this is indeed acceptable enough: More than 80 percent of viewing on Netflix is driven by the recommendation engine.

In order to make those matches, the algorithm needs a lot of content. Not necessarily brilliant, unique, nothing-like-it content, but familiar, reliable, plenty-of-things-like-it content. Which, as it happens, is what A.I. is best at.

The debate over A.I. in screenwriting is often simplified as, “Could a chatbot write the next ‘Twin Peaks’?” No, at least for now. Nor would anyone necessarily want it to. The bulk of TV production has no interest in generating the next “Twin Peaks” — that is, a wild, confounding creative risk. It is interested in more reboots, more procedurals, more things similar to what you just watched.

TV has always relied on formula, not necessarily in a bad way. It iterates, it churns out slight variations on a theme, it provides comfort. That’s what has long made strictly formatted shows like “Law & Order” such reliable, relaxing prime-time companions. That’s also what could make them among the first candidates for A.I. screenwriting.

Large language models like ChatGPT work by digesting vast quantities of existing text, identifying patterns and responding to prompts by mimicking what they’ve learned. The more done-to-death a TV idea is, the greater the corpus of text available on it.

And, well, there are a lot of “Law & Order” scripts, a lot of superhero plots, a lot of dystopian thrillers. How many writers-contract cycles before you can simply drop the “Harry Potter” novels into the Scriptonator 3000 and let it spit out a multiseason series?

In the perceptive words of “Mrs. Davis,” the wildly human comedic thriller about an all-powerful A.I., “Algorithms love clichés.” And there’s a direct line between the unoriginality of the business — things TV critics complain about, like reboots and intellectual-property adaptations and plain old derivative stories — and the ease with which entertainment could become bloated by machine-generated mediocrity.

After all, if studios treat writers like machines, asking for more remakes and clones — and if viewers are satisfied with that — it’s easy to imagine the bean counters wanting to skip the middle-human and simply use a program that never dreamed of becoming the next Phoebe Waller-Bridge.

And one could reasonably ask, why not? Why not leave the formulas to machines and rely on people only for more innovative work? Beyond the human cost of unemployment, though, there’s an entire ecosystem in which writers come up, often through precisely those workmanlike shows, to learn the ropes.

Those same writers may be able to use A.I. tools productively; the WGA is calling for guardrails, not a ban. And the immediate threat of A.I. to writers’ careers may be overstated, as you know if you’ve ever tried to get ChatGPT to tell you a joke. (It’s a big fan of cornball “Why did the …” and “What do you call a …” constructions.) Some speculations, like the director Joe Russo’s musing that A.I. some day might be able to whip up a rom-com starring your avatar and Marilyn Monroe’s, feel like science fiction.

But science fiction has a way of becoming science fact. A year ago, ChatGPT wasn’t even available to the public. The last time the writers went on strike, in 2007, one of the sticking points involved streaming media, then a niche business involving things like iTunes downloads. Today, streaming has swallowed the industry.

The potential rise of A.I. has workplace implications for writers, but it’s not only a labor issue. We, too, have a stake in the war with the storybots. A culture that is fed entirely by regurgitating existing ideas is a stagnant one. We need invention, experimentation and, yes, failure, in order to advance and evolve. The logical conclusion of an algorithmicized, “more like what you just watched” entertainment industry is a popular culture that just … stops.

Maybe someday A.I. will be capable of genuine invention. It’s also possible that what “invention” means for advanced A.I. will be different from anything we’re used to — it might be wondrous or weird or incomprehensible. At that point, there’s a whole discussion we can have about what “creativity” actually means and whether it is by definition limited to humans.

But what we do know is that, in this timeline, it is a human skill to create a story that surprises, challenges, frustrates, discovers ideas that did not exist before. Whether we care about that — whether we value it over an unlimited supply of reliable, good-enough menu options — is, for now, still our choice.

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