Why AI may overcomplicate answers: Humans and LLMs show ‘addition bias,’ often choosing extra steps over subtraction
When making decisions and judgments, humans can fall into common “traps,” known as cognitive biases. A cognitive bias is essentially the tendency to process information in a specific way or follow a systematic pattern. One widely documented cognitive bias is the so-called addition bias, the tendency of people to prefer solving problems by adding elements as opposed to removing them, even if subtraction would be simpler and more efficient. One example of this is adding more paragraphs or explanations to improve an essay or report, even if removing unnecessary sections would be more effective.
Researchers at the Center for Cognitive Science at TU Darmstadt and hessian.AI have investigated the properties of behavioral economic theories automatically learned by AI.
Researchers have found a better way to reduce gender bias in natural language processing models while preserving vital information about the meanings of words, according to a recent study that could be a key step toward addressing the issue of human biases creeping into artificial intelligence.