Expert thinking with generative chatbots

What is it about?

Generative chatbots are artificial intelligence (AI) programs designed to have natural conversations with users. Since the release of ChatGPT (GPT stands for Generative Pre-trained Transformer), generative chatbots have become widely available. Generative chatbots are especially powerful because they are built on computer neural networks and trained on vast amounts of data. In addition, the text they produce can closely resemble expert knowledge and writing on nearly any topic. Consequently, individuals across industries and governments are interested in the potential for generative chatbots to support cognition in experts and nonexperts. This article reviews the history of chatbots, compares human expertise and artificial expertise, and then describes how individuals attain expertise through observing models, completing scaffolded tasks, and engaging in deliberate practice. Afterward, the article discusses how generative chatbots have been used—and could be used in the future—to support cognition (i.e., thoughts and mental processes) for users with varied amounts of domain knowledge (i.e., experts, novices, and laypersons). Research on potential approaches to leveraging generative chatbots to support cognition by these users is primarily drawn from three applied domains: education, medicine, and law. Research with the current generation of generative chatbots like ChatGPT is new and rapidly progressing, but research thus far suggests that (a) the roles that generative chatbots take on to support thinking vary depending on how much knowledge a user has on a particular topic and (b) generative chatbots show promise in supporting experts’ cognition and the training of novices who might be future experts in their fields, but (c) laypersons’ lack of prior knowledge currently limits generative chatbots’ ability to support their thinking and their agency in engaging with unfamiliar domains more broadly.

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Why is it important?

As generative chatbots become widely accessible and used it is imperative to understand how, why, and when they may be used. This is particularly true for their use within domains that affect our daily lives, such as as education, medicine, and law. Our review of existing research suggests that the amount of knowledge one has in a particular area matters a lot in how that individual may use generative chatbots to help them in everyday life and to solve real-world problems. While those who have a lot (experts) or some (novices) knowledge in a domain may have many uses for generative chatbots, those with little knowledge (laypersons) are limited in their ability to evaluate the accuracy of information from generative chatbots and may not always be able to use generative chatbots effectively.