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Story

What Emily Bender meant by "stochastic parrots"

1 report

1 website

1 discussion

Latest report

Overview

The paper "On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?" argues that large language models generate text by statistically predicting likely sequences of words. The publication gained significant attention following the firing of two authors, Timnit Gebru and Margaret Mitchell, by Google.

Summary from spectrum.ieee.org.

Reports

One report so far. Additional coverage will appear here when it is linked to this story.

  1. spectrum.ieee.org

    What Emily Bender meant by "stochastic parrots"

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Community reactions

Each reaction summarizes sampled comments from the linked discussion.

Hacker News · spectrum.ieee.org

What Emily Bender meant by "stochastic parrots" ↗
Hacker News discussion ↗

Historical count: 5 · 5 saved in sample · Historical sample

Analysis ready

Read this discussion’s reaction

Based on 5 sampled comments from this thread. Analyzed 2026-07-06.

  • Praise: The criticisms about financial and environmental costs in the 'stochastic parrots' paper are crucial — we can't ignore the impact of AI on the planet.
  • Praise: There's a valid point in advocating for careful evaluation of datasets, rather than just dumping the entire internet into models — quality over quantity matters!
  • Praise: Some commenters appreciate the nuanced discussion around AI and its limitations, highlighting that LLMs can behave methodically, challenging the notion of them being merely 'haphazard'.
  • Concern: Many commenters feel the paper has been unfairly criticized without substantial argument — it's frustrating when people dismiss important work without engaging with its content.
  • Concern: The debate over the ethical implications of LLMs seems muddled, with some asserting that calling them 'intelligent' is misleading — they may mimic understanding but lack true cognition.
  • Concern: There's a strong sentiment that the term 'artificial intelligence' oversells the capabilities of these models, leading to misunderstandings about what they can truly do.