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A courts reporter wrote about a few trials. Then an AI decided he was actually the culprit. (www.niemanlab.org)

submitted 1 month ago by Stopthatgirl7@lemmy.world to c/technology@lemmy.world

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When German journalist Martin Bernklautyped his name and location into Microsoft’s Copilot to see how his articles would be picked up by the chatbot, the answers horrified him. Copilot’s results asserted that Bernklau was an escapee from a psychiatric institution, a convicted child abuser, and a conman preying on widowers. For years, Bernklau had served as a courts reporter and the AI chatbot had falsely blamed him for the crimes whose trials he had covered.

The accusations against Bernklau weren’t true, of course, and are examples of generative AI’s “hallucinations.” These are inaccurate or nonsensical responses to a prompt provided by the user, and they’re alarmingly common. Anyone attempting to use AI should always proceed with great caution, because information from such systems needs validation and verification by humans before it can be trusted.

But why did Copilot hallucinate these terrible and false accusations?

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[–] femtech@midwest.social 5 points 1 month ago (10 children)

https://cloud.google.com/discover/what-are-ai-hallucinations#:~:text=AI%20hallucinations%20are%20incorrect%20or,medical%20diagnoses%20or%20financial%20trading.

AI hallucinations are incorrect or misleading results that AI models generate. These errors can be caused by a variety of factors, including insufficient training data, incorrect assumptions made by the model, or biases in the data used to train the model. A

[–] mindlesscrollyparrot@discuss.tchncs.de 2 points 1 month ago (2 children)

Sure, but which of these factors do you think were relevant to the case in the article? The AI seems to have had a large corpus of documents relating to the reporter. Those articles presumably stated clearly that he was the reporter and not the defendant. We are left with "incorrect assumptions made by the model". What kind of assumption would that be?

In fact, all of the results are hallucinations. It's just that some of them happen to be good answers and others are not. Instead of labelling the bad answers as hallucinations, we should be labelling the good ones as confirmation bias.

[–] femtech@midwest.social 1 points 1 month ago (1 children)

It was an incorrect assumption based on his name being in the article. It should have listed him as the author only, not a part of the cases.

[–] mindlesscrollyparrot@discuss.tchncs.de 1 points 1 month ago

That is the error that the model made. Your quote talks about the causes of these errors. I asked what caused the model to make this error.

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