Take, for example, non-player characters. Text-based generative AI tools seem like a great way to deepen conversation, and Togelius has been advising developers intrigued by this very idea. But it’s not that simple. Characters based on these language models are liable to go off on tangents, discussing topics outside of the game’s world. “This is super interesting, but it’s also super hard,” says Togelius. “You can’t just drop it in there. It’s not going to work. You can’t expect the NPCs to behave in Skyrim or Elden Ring or Grand Theft Auto or your typical RPG. You have to design around the fact that they are, in some sense, uncontrollable.”
Nevertheless, there are some peripheral uses for generative AI right now. A good rule of thumb—one that applies to procedural generation too—is that the less crucial the content is, the more likely deep learning methods could be helpful. “For things like text generation, I could use this today to help generate filler for assets that aren’t really meant to be the focus of the player’s attention, like prop newspapers and such,” says Mills.
Another appeal is these tools’ low barrier of entry, says Adrian Hon, the CEO and founder of independent games developer Six to Start and the co-creator of Zombies, Run! Procedural generation, at least as the term is typically understood, requires a coder; anyone can use tools like Midjourney and Stable Diffusion. He can see how they could help with prototyping or mood-boarding during a game’s early concept phase.
But, Hon notes, many artists are skeptical of AI. Part of the backlash to the generative AI hype has been that these tools are modeling their output on the work of human creators. Some are even suing Stable Diffusion and Midjourney, claiming that Stable Diffusion, which powers Midjourney, was trained on images used without permission. “Obviously, there’s a whole copyright question. We know about all these suits going on,” he says. “But even if they get resolved, I think that there’ll be some real upset among artists, which is understandable.”
As with so many discussions about automation, the hype here is detached from current reality (debates over automation usually arise during times of “deep anxiety about the functioning of the labor market,” writes sociologist Aaron Benanav). But, leaving reality for a second, it’s notable that much of the conversation around generative AI seems almost to revel at the prospect of replacing humans. Even an innocuous statement promising a boon for indie developers—“A small team can make a world the size of Red Dead’s,” for example—contains a kernel of this logic, explains Raphael van Lierop, the founder and creative director of independent studio Hinterland. It’s reductive, suggesting the work of a large part of that large team is mindlessly robotic.
“The focus on generative AI is another facet of what feels like an attack on creators and the act of creation, one that is expressed in a lot of different ways in our society right now,” he says. Reflecting a prevailing mood among artists across mediums, he sees nothing interesting about art made by an AI. “It’s a dead end,” he says.
There’s definitely an unsettlingly inhuman element to all of this, one that you could imagine manifesting as a torrent of AI-generated shovelware run on predatory monetary systems. But at the higher echelons of game development, games created entirely by machines—ones worth playing, at least—are some way off. “The way some people say it’s going to be used, to just suddenly replace people and do the whole job by itself, is bullshit,” says Togelius. “You need humans.”
