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?
It’s only a completely static model if it is not allowed to use it’s own interactions as training data. If it is allowed to use the data acquired from those interactions, it stops being a static model.
Kids do learn elementary arithmetic by rote memorization. Number theory doesn’t actually develop significantly until somewhere around 3rd to 5th grade, and even then, we don’t place a lot of value on it at that time. We are taught to memorize the multiplication table, for example, because the efficiency of simply knowing that table is far more computationally valuable than the ability to reproduce it at any given time. That rote memorization is mimicry: the child is simply spitting out a previously learned response.
Remember: LLMs are currently toddlers. They are toddlers with excellent grammar, but they are toddlers.
Remember also that simple mimicry is an incredibly powerful problem solving method.