Botshit

  • Slop
  • Research term
3 steps

Botshit is inaccurate or fabricated chatbot content that people accept and use without questioning whether it is true.

A language model can produce plausible language without establishing every claim's source. A deadline and a polished presentation can encourage people to treat that plausibility as evidence. Grounding and checking are separate parts of the workflow.

Where you’ll meet it

You ask the AI in your slide software to fill in a market overview for tomorrow's client pitch. It adds a crisp line saying the market grew 18% last year, “according to industry analysts.” No report is named, and the slide looks ready.

What to do

Find the report behind that number and open it before the deck goes out. If no report you find has the figure, cut the line or use one whose source you've read.

Easy to mix up

A hallucination is the false claim the AI produces. Botshit is what happens next, when people accept that content and pass it on or rely on it without checking whether it is true.

Check yourself

An AI drafts your team's monthly client update from the project tracker. A teammate finds it clear and sends it, and the client later spots a wrong deadline. Which check directly addresses that error?

Go deeperThe authors separate truth importance from verification difficulty

Tim Hannigan, Ian McCarthy, and Andre Spicer introduced the term in Business Horizons, drawing on Harry Frankfurt’s distinction between lying and speaking without concern for truth. They use botshit for inaccurate or fabricated chatbot content that people apply uncritically to a task.

The framework considers both the importance of truth and the difficulty of checking it. Social media captions, legal citations, medication doses, and financial projections need different checks depending on the actual claim and its use. A citation's existence may be easy to confirm while its relevance needs expertise; a projection also needs its assumptions examined.

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