This paper explores the impact of a generative AI-powered chatbot (e.g., ChatGPT) on human language and culture. Using hundreds of thousands of hours of YouTube academic lectures and podcasts, we use econometric causal inference techniques to analyze the spikes in usage of specific words following the launch of the chatbot. We find measurable increases in usage of ChatGPT’s preferred words (e.g., delve, comprehend, boast, swift, meticulous). We argue that this signals the beginning of a closed cultural feedback loop in which machines trained on human data exhibit unique cultural characteristics, which in turn transform human culture.