Large language models respond differently based on user's motivation

A new study reveals how large language models (LLMs) respond to different motivational states. In their evaluation of three LLM-based generative conversational agents (GAs)--ChatGPT, Google Bard, and Llama 2, scientists found that while GAs are able to identify users' motivation states and provide relevant information when individuals have established goals, they are less likely to provide guidance when the users are hesitant or ambivalent about changing their behavior.