Expert thinking with generative chatbots

Journal of Applied Research in Memory and Cognition
Imundo, Megan N.; Watanabe, Micah; Potter, Andrew H.; Gong, Jiachen; Arner, Tracy; McNamara, Danielle S.

Artificial intelligence (AI)-driven generative chatbots can produce large quantities of text instantly across a range of domains, using authoritative tones that create the perception of expertise. This critical synthesis compares artificial expertise and human expertise and examines ways in which generative chatbots can support cognition using an expert thinking framework. Findings indicate that generative chatbots may support experts’ cognition as a collaborator or to offload lower level tasks. Moreover, generative chatbots are a promising training tool in developing future experts in part because they can provide learning models and practice opportunities. The use of generative chatbots to offload lower level tasks, however, may harm expert development by disrupting knowledge communities. Finally, a lack of domain knowledge in nonexpert users may limit the effectiveness of generative chatbots in supporting higher level cognition and agency. Overall, existing research suggests that the potential for generative chatbots to support users’ cognition depends on a user’s level of expertise.