Using ChatGPT in foresight fieldwork pedagogy to address the preparedness paradox by mitigating the overoptimism and normalcy biases

This pedagogy-methodology paper addresses the challenges of preparing students for foresight fieldwork using AI. Foresight students engage with innovation forecasting, scenario planning, and technology roadmapping, applying them practically. Yet, universities hesitate to involve early career students with real-world stakeholders in fear of reputational risk. Teachers of these tools will often underestimate the role that their own experience has in their teaching, leaving students vulnerable to mistakes. This experience bias influences preparedness. Effectively mitigating a risk, diminishes its perceived severity, and individuals who overprepare may be disappointed when nothing goes wrong because they overinvested in preparing, reducing the perceived value of preparation. Moreover, overconfident individuals underestimate the likelihood of failure, assuming normalcy as the norm, possibly dismissing threat warnings.
Using foresight pedagogy as a case study, the paper proposes an approach to fieldwork preparation, that incorporates ChatGPT in a "roleplay" as stakeholder, for lowering risks, addressing cognitive biases, and emphasizing the importance of foresight in undergraduate education. We argue these tools can be used to develop futures literacy skills in controlled research settings, scalable to large classes and diverse case studies. There is potential for this approach to extend beyond future studies, aiding preparation for general community engagements.