AI’s presence in the gaming industry has evolved from a mere novelty to an indispensable force. With every algorithmic breakthrough, new possibilities and challenges arise for gamers and developers alike.
In March 2023, a Reddit user shared a story of how AI was being used where she worked. “I lost everything that made me love my job through Midjourney overnight,” the author wrote. The post got a lot of attention, and its author agreed to talk to WIRED on condition of anonymity, out of fear of being identified by her employer.
“I was able to get a huge dopamine rush from nailing a pose or getting a shape right. From having this ‘light bulb moment’ when I suddenly understood a form, even though I had drawn it hundreds of times before,” says Sarah (not her real name), a 3D artist who works in a small video game company.
Sarah’s routine changed drastically with version 5 of Midjourney, an AI tool that creates images from text prompts. Midjourney has also been widely criticized for violating copyright of visual artists and stealing their work in order to train its image generation engine, criticism that’s led to a massive copyright lawsuit.
When Sarah started working in the gaming industry, she says, there was high demand for 3D environmental and character assets, all of which designers built by hand. She says she spent 70 percent of her time in a 3D motion capture suit and 20 percent in conceptual work; the remaining time went into postprocessing. Now the workflow involves no 3D capture work at all.
Her company, she explains, found a way to get good and controllable results using Midjourney with images taken from the internet fed to it, blending existing images, or simply typing a video game name for a style reference into the prompt. “Afterwards, most outputs only need some Photoshopping, fixing errors, and voilà: The character that took us several weeks before now takes hours—with the downside of only having a 2D image of it,” says Sarah. “It’s efficiency in its final form. The artist is left as a clean-up commando, picking up the trash after a vernissage they once designed the art for,” she adds.
“Not only in video games, but in the entire entertainment industry, there is extensive research on how to cut development costs with AI,” says Diogo Cortiz, a cognitive scientist and professor at the Pontifícia Universidade de São Paulo. Cortiz worries about employment opportunities and fair compensation, and he says that labor rights and regulation in the tech industry may not match the gold rush that’s been indicative of AI adoption. “We cannot outsource everything to machines. If we let them take over creative tasks, not only are jobs less fulfilling, but our cultural output is weakened. It can’t be all about automation and downsizing,” he says, adding that video games reflect and shape society’s values.
Cortiz says that gaming companies must, either as an industry or individually, collaboratively discuss AI, its usage, where it should be applied, and how far it can go. “The committees need to have diversity in terms of gender, age, class, and ethnicity, to discuss and create a more inclusive AI,” he says. “They need to make their AI principles available to everyone.” He adds that gamers should have access to how companies use AI so there can be greater transparency, trust, and more developed digital literacy on the topic.
In practice, that means companies should disclose the AI tools employed in games and make their AI committee available to write public reports and answer questions from all stakeholders involved in a video game—developers, players, and investors.
Labor-Saving or Labor-Crushing?
“Incorporation of AI in our workflows relies on three axes: creating more believable worlds, reducing the number of low-value tasks for our creators, and improving the player experience,” says Yves Jacquier, executive director of Ubisoft La Forge.
Jacquier describes several ways that his company is already experimenting with AI, from smoother AI-driven motion transitions in Far Cry 6, which make the game look more natural, to the bots designed to improve the new player experience in Rainbow Six Siege. There’s also Ghostwriter, an AI-powered tool that allows scriptwriters to create a character and a type of interaction they would like to generate and offers them several variations to choose from and edit.
Tech conglomerate Tencent caused a stir last year with the announcement that it would comply with China’s directive to incorporate facial recognition technology into its games in the country. The move was in line with China’s strict gaming regulation policies, which impose limits on how much time minors can spend playing video games—an effort to curb addictive behavior, since gaming is labeled by the state as “spiritual opium.”
The state’s use of biometric data to police its population is, of course, invasive, and especially undermines the privacy of underage users—but Tencent is not the only video game company to track its players, nor is this recent case an altogether new phenomenon. All over the world, video games, one of the most widely adopted digital media forms, are installing networks of surveillance and control.
In basic terms, video games are systems that translate physical inputs—such as hand movement or gesture—into various electric or electronic machine-readable outputs. The user, by acting in ways that comply with the rules of the game and the specifications of the hardware, is parsed as data by the video game. Writing almost a decade ago, the sociologists Jennifer R. Whitson and Bart Simon argued that games are increasingly understood as systems that easily allow the reduction of human action into knowable and predictable formats.
Video games, then, are a natural medium for tracking, and researchers have long argued that large data sets about players’ in-game activities are a rich resource in understanding player psychology and cognition. In one study from 2012, Nick Yee, Nicolas Ducheneaut, and Les Nelson scraped player activity data logged on the World of Warcraft Armory website—essentially a database that records all the things a player’s character has done in the game (how many of a certain monster I’ve killed, how many times I’ve died, how many fish I’ve caught, and so on).
The researchers used this data to infer personality characteristics (in combination with data yielded through a survey). The paper suggests, for example, that there is a correlation between the survey respondents classified as more conscientious in their game-playing approach and the tendency to spend more time doing repetitive and dull in-game tasks, such as fishing. Conversely, those whose characters more often fell to death from high places were less conscientious, according to their survey responses.
Correlation between personality and quantitative gameplay data is certainly not unproblematic. The relationship between personality and identity and video game activity is complex and idiosyncratic; for instance, research suggests that gamer identity intersects with gender, racial, and sexual identity. Additionally, there has been general pushback against claims of Big Data’s production of new knowledge rooted in correlation. Despite this, games companies increasingly realize the value of big data sets to gain insight into what a player likes, how they play, what they play, what they’ll likely spend money on (in freemium games), how and when to offer the right content, and how to solicit the right kinds of player feelings.
While there are no numbers on how many video game companies are surveilling their players in-game (although, as a recent article suggests, large publishers and developers like Epic, EA, and Activision explicitly state they capture user data in their license agreements), a new industry of firms selling middleware “data analytics” tools, often used by game developers, has sprung up. These data analytics tools promise to make users more amenable to continued consumption through the use of data analysis at scale. Such analytics, once available only to the largest video game studios—which could hire data scientists to capture, clean, and analyze the data, and software engineers to develop in-house analytics tools—are now commonplace across the entire industry, pitched as “accessible” tools that provide a competitive edge in a crowded marketplace by companies like Unity, GameAnalytics, or Amazon Web Services. (Although, as a recent study shows, the extent to which these tools are truly “accessible” is questionable, requiring technical expertise and time to implement.) As demand for data-driven insight has grown, so have the range of different services—dozens of tools in the past several years alone, providing game developers with different forms of insight. One tool—essentially Uber for playtesting—allows companies to outsource quality assurance testing, and provides data-driven insight into the results. Another supposedly uses AI to understand player value and maximize retention (and spending, with a focus on high-spenders).
