Generative Monoculture

Generative monoculture describes the phenomenon where large language models (LLMs) and other generative AI systems produce surprisingly homogenous outputs, even when trained on diverse data, limiting the variety of perspectives and potentially reinforcing biases. Current research focuses on understanding the root causes of this behavior, particularly within model training and alignment processes, and exploring mitigation strategies beyond simple adjustments to prompting or sampling techniques. This issue has significant implications for fairness, accessibility, and the preservation of diverse cultural outputs across various applications, from education and search engines to creative fields like art and writing.