The derogatory term "clanker" has emerged as a slang slur used to disparage artificial intelligence systems, chatbots, and robots [1].
This linguistic trend reflects growing public frustration with the rapid deployment of AI technology. As the term gains traction, it has evolved from a critique of software into a tool for social signaling and, in some instances, a shield for hate speech.
The term rose to prominence in mid-2025 [1], gaining significant media attention throughout August and September of that year [2, 3]. It is primarily spreading across English-speaking social media in the U.S., though international outlets have also reported on the trend [1, 2, 4].
"The word ‘clanker’ has become a catch‑all insult for anything that looks or sounds like a machine," Slate Technology Staff said [1].
While some users employ the term to signal distrust of AI, others have used it to bypass moderation filters on platforms like TikTok. In these cases, the anti-AI sentiment serves as a cover for racist jokes. An unnamed author from Nieman Lab said that individuals using the term for racist humor likely wanted an excuse to make those jokes and felt clever in making those connections [5].
Emily Johnson said that "clanker" started as a tongue-in-cheek jab at AI assistants and quickly morphed into a broader anti-AI slur [2].
There is disagreement regarding the cultural origins of the word. Some reports link the term to the television show "Battlestar Galactica" and the film "Blade Runner" [2], while other sources state it was popularized by a "Star Wars" show [3]. Regardless of its origin, the term has been tracked by three major tier-1 media outlets as of September 2025 [1, 2, 5].
““Clanker” is an anti‑AI slang term that has become a rallying cry.”
The rise of 'clanker' demonstrates how technological anxiety can manifest as new social hierarchies and linguistic weapons. By creating a derogatory category for AI, users are not only expressing distrust in automation but are also discovering ways to weaponize 'anti-AI' sentiment to mask traditional forms of prejudice, complicating the task for social media moderators.
