The "garbage in, garbage out" principle has now reached literary audiences at the highest level. At the inaugural Babell Literary and Cultural Festival in Porto, Portugal, Canadian author Margaret Atwood told the audience she had used Anthropic's Claude exactly once, looking for a spoiler about the British detective series Father Brown, and was misled. "Claude gave me the wrong answer, or it lied. Of course, it didn't know it was lying because it's not a human being; it's a large language model... It had skimmed and sampled a lot of television reviews, but they never give away the ending in online criticism, so it was misled by the things it had read about the show," she said (Deadline). Her broader verdict: "The thing about AI is that it's garbage in, garbage out. Even people who use it for business reasons have to check it because it makes mistakes." For practitioners, Atwood's anecdote is a precise public illustration of training-data coverage gaps - the failure mode where systematically absent information (here: spoilers) produces confident but wrong model outputs.
Half of Claude users say AI can already handle half their work according to Anthropic survey