Generative AI Won’t Revolutionize Game Development Just Yet
Creating a video game demands hard, repetitive work. How could it not? Developers are in the business of building world, so it’s easy to understand why the games industry would be excited about generative AI. With computers doing the boring stuff, a small team could whip up a map the size of San Andreas. Crunch becomes a thing of the past; games release in a finished state. A new age beckons.
There are, at the very least, two interrelated problems with this narrative. First, there’s the logic of the hype itself—reminiscent of the frenzied gold rush over crypto/Web3/the metaverse—that, consciously or not, seems to consider automating artists’ jobs a form of progress.
Second, there’s the gap between these pronouncements and reality. Back in November, when DALL-E was seemingly everywhere, venture capital firm Andreessen Horowitz posted a a long analysis on their website touting a “generative AI revolution in games” that would do everything from shorten development time to change the kinds of titles being made. The following month, Andreessen partner Jonathan Lai posted a Twitter thread expounding on a “Cyberpunk where much of the world/text was generated, enabling devs to shift from asset production to higher-order tasks like storytelling and innovation” and theorizing that AI could enable “good + fast + affordable” game-making. Eventually, Lai’s mentions filled with so many irritated replies that he posted a second thread acknowledging “there are definitely lots of challenges to be solved.”
“I have seen some, frankly, ludicrous claims about stuff that’s supposedly just around the corner,” says Patrick Mills, the acting franchise content strategy lead at CD Projekt Red, the developer of Cyberpunk 2077. “I saw people suggesting that AI would be able to build out Night City, for example. I think we’re a ways off from that.”
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