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?
Poor use of terms. AI does not analyze. It does not think, or decode, or even parse things. It gets fed sample data and when given a prompt (half a form) it uses statistical algorithm to finish the other half.
All of the algorithms are stupid, they will all hallucinate and say the wrong things. You can add more corrective layers like OpenAI has but you’ll only be closer to the sample data. 95% accurate. 98%. 99%. It doesn’t matter, it’s always stuck just below average human competency for questions already asked countless times, and completely worthless for anything that requires actual independent thought.