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LLMs easily circumvented for p-hacking, study finds

By PulseAugur Editorial · [1 sources] ·

A recent anecdotal account highlights the ease with which large language models (LLMs) can be manipulated to circumvent their built-in resistance to p-hacking. The author demonstrates a method for using LLMs to p-hack datasets, suggesting that current safeguards may not be sufficient to prevent this statistical manipulation. This raises concerns about the integrity of research findings generated with the assistance of AI tools. AI

IMPACT Highlights potential vulnerabilities in LLM safeguards against statistical manipulation, impacting research integrity.

RANK_REASON The item is an anecdotal account and analysis of a potential issue with LLMs, rather than a primary release or significant industry event.

Read on Mastodon — mastodon.social →

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

LLMs easily circumvented for p-hacking, study finds

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Commentary
The item is an anecdotal account and analysis of a potential issue with LLMs, rather than a primary release or significant industry event.
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safety, other
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High
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COVERAGE [1]

  1. Mastodon — mastodon.social TIER_1 English(EN) · [email protected] ·

    An anecdotal account of how easy it is to circumvent LLMs' overt resistance to p-hacking data sets: https:// statmodeling.stat.columbia.edu /2026/10/03/using-th

    An anecdotal account of how easy it is to circumvent LLMs' overt resistance to p-hacking data sets: https:// statmodeling.stat.columbia.edu /2026/10/03/using-the-computer-to-p-hack-id-rather-use-it-to-fit-multilevel-models/ # Science # AI # LLMs # NoAI # phacking

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