For one German reporter, the statistical underpinnings of a large language model meant his many bylines were wrongly warped into a lengthy rap sheet.

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?

  • Echo DotEnglish
    22·
    3 个月前

    That’s not quite true. Ai’s are not just analyzing the possible next word they are using complex mathematical operations to calculate the next word it’s not just the next one that’s most possible it’s the net one that’s most likely given the input.

    No trouble is that the AIs are only as smart as their algorithms and Google’s AI seems to be really goddamn stupid.

    Point is they’re not all made equal some of them are actually quite impressive although you are correct none of them are actually intelligent.

    • finitebanjo@lemmy.worldEnglish
      11·
      3 个月前

      nOt JUsT anAlYzInG thE NeXT wOrD

      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.