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https://www.rollingstone.com/culture/culture-features/clanker-cogsucker-robot-ai-slurs-viral-1235401262/

How ‘Clanker’ Became the Internet’s New Favorite Slur

New derogatory phrases are popping up online, thanks to a cultural pushback against AI

By CT Jones

August 6, 2025

Clanker. Wireback. Cogsucker. People are feeling the inescapable inevitability of AI developments, the encroaching of the digital into everything from entertainment to work. And their answer? Slurs.

AI is everywhere — on Google summarizing search results and siphoning web traffic from digital publishers, on social media platforms like Instagram, X, and Facebook, adding misleading context to viral posts, or even powering Nazi chatbots. Generative AI and large language models (LLM) — AI trained on huge datasets — are being used as therapists, consulted for medical advice, fueling spiritual psychosis, directing self-driving cars, and churning out everything from college essays to cover letters to breakup messages.

Alongside this deluge is a growing sense of discontent from people fearful of artificial intelligence stealing their jobs, and worried what effect it may have on future generations — losing important skills like media literacy, problem solving, and cognitive function. This is the world where the popularity of AI and robot slurs has skyrocketed, being thrown at everything from ChatGPT servers to delivery drones to automated customer service representatives. Rolling Stone spoke with two language experts who say the rise in robot and AI slurs does come from a kind of cultural pushback against AI development, but what’s most interesting about the trend is that it uses one of the only tools AI can’t create: slang.

“Slang is moving so fast now that an LLM trained on everything that happened before it is not going to have immediate access to how people are using a particular word now,” says Nicole Holliday, associate professor of linguistics at UC Berkeley. “Humans [on] Urban Dictionary are always going to win.”

Clanker, the most popular of the current AI slurs, was first used in the 2005 Star Wars first-person shooter video game Republic Commando, according to Know Your Meme. But it was introduced to most audiences in a 2008 episode of the animated series Star Wars: The Clone Wars as a retort from a Jedi fighting a horde of battle droids. “OK, clankers,” the Jedi said. “Eat lasers.” According to Adam Aleksic, the creator of the TikTok page Etymology Nerd and author of the 2025 book Algospeak, the meme first gained popularity on the r/Prequelmemes subreddit, a Star Wars fan community. Star Wars isn’t the only science-fiction offering that had its characters say derogatory things to their robot counterparts. In Battlestar Galactica, people referred to the sentient robots, Cylons, as “toasters” or “chrome jobs.” Both Aleksic and Holliday note that the way slurs work — in these stories and in real life — is by carrying an assumed power structure along with them.

“Slurs are othering. Usually, the things that we end up considering to be slurs or epithets are from a majority group with power against a minority group,” says Holliday. “So when people use these terms, they’re in some ways doing so as a self-protective measure, and we tolerate that more because humans are [perceived as] the minority group. And punching up is always more socially acceptable than punching down.”

But there’s also a problem with using slurs as a way to fight back against AI encroachment, these experts say, as the words can actually reinforce the belief that AI is becoming more human. “It’s drawing on historical ways that slurs have dehumanized others,” Aleksic tells Rolling Stone. “Something requires a degree of anthropomorphization, of personification, for a slur to work.”

The easiest place to see the humanization and dehumanization of slurs is in POV videos that imagine situations where robot slurs like clanker, wireback, and tin-skinned aren’t used to cheekily fight back against chatbots, but against AI individuals that have some kind of place in a fictional future society — a Guess Who’s Coming to Dinner for the robot age. Many creators post skits where the robot slurs are spoken while a robot is applying for a job, or meeting their human partner’s parents for a holiday.

As robot slurs continue to have their viral moment, there’s been a rise in concerned internet users who feel like the trend is just a convoluted way for people to get close to saying real-life slurs. They’re not wrong — it’s how they got started on the Star Wars subreddit. “The way clanker was used was a clear analogy to the n-word,” Aleksic says. “There’d be a photo of a droid giving you the c-word pass or one captioned ‘What’s up my Clanka?’ with an ‘a.’” Aleksic thinks many of the robot slurs are popular because they inspire such mixed reactions. Algorithms reward strong feelings, and clanker content has the added benefit of grabbing people who don’t like AI, people who want to be edgy online, and people who are afraid of being the “woke” friend all at the same time. Unfortunately, even if the robot-slur trend died tomorrow, whatever took its place would most likely be equally rooted in shocking and controversial language.

While it’s hard to tell how much longevity these slurs will have, or how much of the trend’s popularity comes from anti-AI sentiment or the algorithmic appeal of buzzwords, the linguists who spoke to Rolling Stone say this fits into the natural way human language evolves. People adapt words because of how using them makes them feel — and words change based on the context of other words being used around them. “In the case of clanker, it’s seen as funny or cool to be counter-cultural to AI. African American English spread into the mainstream because it was perceived as cool from the outside. It was sociologically prestigious,” Aleksic says. “But if you look at how algorithms change these words, it’s kind of an exaggerated picture of what humans are doing with this medium.”

Though AI platforms have begun to recognize clanker as a slur, Holliday noted that both ChatGPT and Google AI did not recognize “wireback,” instead saying the word wasn’t recognized or possibly misspelled. For Holliday, this is one of the fundamental reasons why she believes changes in language and slang will remain the place where AI is always a step behind.

“Large language models, AI, it’s a flattening of meaning. Because we as humans co-create the meaning of a particular utterance in a context,” she says. “So AI has got a lot of context that it’s trained on, but it can’t tell you what this person meant in that conversation, because it doesn’t have the information that you have about previous interactions with that person, about the way that the word has changed in the last two weeks. That’s where humans will always have the edge.”

  
   

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