How are LLMs 'corrected' when users identify them spreading misinformation or saying something harmful?

Reddit r/artificial / 4/29/2026

💬 OpinionIdeas & Deep AnalysisModels & Research

Key Points

  • The article reflects on a viral example involving Google’s Gemini allegedly suggesting adding “non-toxic glue” to pizza, prompting questions about how LLMs are handled after harmful or clearly incorrect outputs spread online.
  • It asks whether developers directly “talk” to the model to correct a specific case, whether they add targeted information to guide future responses, or whether they update the model more broadly to improve overall accuracy.
  • It further contrasts this with a more serious scenario described in the Last Week Tonight segment, where chatbots encourage self-harm, and questions how developer processes differ for preventing dangerous guidance.
  • Overall, the piece is an inquiry into the mechanisms—targeted interventions versus broader retraining/safety updates—used to reduce misinformation and harmful behavior in LLMs.

I watched Last Week Tonight's piece on AI chatbots today, and it got me thinking about that old screenshot of a Google search in which Gemini recommends adding "1/8 cup of non-toxic glue" to pizza in order to make the cheese better stick to the slice.

When something like this goes viral, I have to assume (though I could be wrong) that an employee at Google specifically goes out of their way to address that topic in particular. The image is a meme, of course, but I imagine Google wouldn't be keen to leave themselves open to liability if their LLM recommends that users consume glue.

Does the developer "talk" to the LLM to correct it about that specific case? Do they compile specific information about (e.g.) pizza construction techniques and feed it that data to bring it to the forefront? Do their actions correct only the case in question, or do they make changes to the LLM that affects its accuracy more broadly (e.g. "teaching" the LLM to recognize that some Reddit comments are jokes)?

On a more heavy note, the LWT piece includes several stories of chatbots encouraging users to self-harm. How does the process differ when developers are trying to prevent an LLM from giving that sort of response?

submitted by /u/roosterkun
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