On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?

Editorial record

Plain-language summary

The paper contends that scaling training data and compute concentrates benefits, raises environmental and labor costs, encodes and amplifies bias from unaudited web text, and produces systems that stitch together form without meaning (the “stochastic parrot”). It calls for documentation, curation, and restraint. It became the defining critical counterpoint to the scale-first paradigm and remains contested.