Co-Intelligence: Living and Working with AI

by Ethan Mollick

As AI improves, it will be tempting to delegate everything to it, relying on its efficiency and speed to get the job done. But AI can have some unexpected weaknesses. For one thing, they don’t actually “know” anything. Because they are simply predicting the next word in a sequence, they can’t tell what is true and what is not. It can help to think of the AI as trying to optimize many functions when it answers you, one of the most important of which is “make you happy” by providing an answer you will like. That goal often is more important than another goal, “be accurate.” If you are insistent enough in asking for an answer about something it doesn’t know, it will make up something, because “make you happy” beats “be accurate.” LLMs’ tendency to “hallucinate” or “confabulate” by generating incorrect answers is well known. Because LLMs are text prediction machines, they are very good at guessing at plausible, and often subtly incorrect, answers that feel very satisfying.