Margaret Atwood says the problem with AI is ‘garbage in, garbage out’
TL;DR
Margaret Atwood discussed AI at the Babell Literary and Cultural Festival in Porto and said she had tried Claude exactly once. She used it to look up information about the British detective series Father Brown. According to Atwood, Claude gave a wrong answer because it had likely learned from reviews that did not reveal the ending. Atwood framed the issue as „garbage in, garbage out“: even business users have to check AI output because models make mistakes.
Nauti's Take
Atwood’s example is small, but it lands. If a model can stumble over a TV plot, nobody should blindly use the same pattern for contracts, support replies, or strategy calls.
The uncomfortable lesson for AI fans is that prompting does not replace expertise. Productive AI work needs better inputs, clear boundaries, and a review process, otherwise automation just produces faster nonsense.
Briefingshow
Atwood points at a practical failure mode: AI can sound confident even when its source material is incomplete. The problem is not only hallucination, but source blindness: a model can turn partial, outdated, or deliberately incomplete writing into a polished answer. For teams, AI saves time only when verification, sourcing, and responsibility are part of the workflow.
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