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Emily Bender questions LLM peer review in scholarship

By PulseAugur Editorial · [1 sources] ·

Emily M. Bender questions the value of using large language models for peer review in academic scholarship. She argues that if research and publishing are fundamentally human endeavors, then LLM-driven review undermines this core principle. Bender suggests that the outcomes of LLM reviews, even if similar to human ones, are irrelevant if the process itself deviates from human-centric scholarship. AI

IMPACT Challenges the integration of AI into core academic processes, questioning the validity of AI-driven scholarship.

RANK_REASON Opinion piece by a named credible voice questioning the application of AI in a specific domain.

Read on Bluesky Jetstream — AI desk →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Emily Bender questions LLM peer review in scholarship

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2 / 100
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Commentary
Opinion piece by a named credible voice questioning the application of AI in a specific domain.
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opinion, other
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Standard
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Breaking (< 6h)
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COVERAGE [1]

  1. Bluesky Jetstream — AI desk TIER_1 English(EN) · emilymbender.bsky.social ·

    "I understand that there have been some experiments showing that LLM review may have similar outcomes to human peer review, but who cares? Either scholarship, r

    "I understand that there have been some experiments showing that LLM review may have similar outcomes to human peer review, but who cares? Either scholarship, research and publishing are human enterprises or they aren’t." www.insidehighered.com/opinion/colu... >>

    LINKS insidehighered.com/…/generative-ai-not-ou…

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