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Study Warns AI Could Homogenize Human Creativity as Models Converge on "Artificial Hivemind"

Researchers from the University of Washington, Carnegie Mellon and the Allen Institute for AI found that a wide range of large‑language models produce nearly identical responses to open‑ended prompts, a phenomenon they label the “Artificial Hivemind.” In tests with 25 models, 80 percent of outputs clustered around just two metaphors for time, and pairwise similarity between unrelated models exceeded 80 percent. The study attributes the convergence to shared training data and alignment practices. Authors warn that such uniformity could erode creative diversity and cultural expression.