GenAI Applications for Public Service Classrooms: Potential, Problems, and Paths for Qualitative Interview Research

Generative Artificial Intelligence (GenAI) is quickly becoming a necessity in modern organizational life.  The technology can reduce redundancy, help with creative processes, and add value to almost every facet of the organization’s business.  These features will certainly result in profits for investors in private corporations, but they will also serve to level the playing field for cash-strapped public and nonprofit agencies.  Students will be expected to demonstrate competence and skills in GenAi tools such as ChatGPT, Microsoft Co-Pilot, and Zapier.  Given these realities, I chose to incorporate GenAi into a long-standing interview assignment for my Introduction to Public Policy course.  This paper highlights lessons my students and I have gained from this experience in four key areas: (1) Using GenAI to improve primary questions and follow-ups, helping to create a useful structured or semi-structured interview guide for the researcher, (2) Using GenAI to rapidly transcribe recorded interviews through applications such as Otter.Ai to save hundreds of hours of transcribing; (3) Using GenAI to identify potential coding categories or schemes, and (4) bringing back the dead (more on this later).  I will describe lessons in each of these areas, provide guidance on effective use of prompts, explain the limitations and ethical concerns associated with GenAI and LLMs, and describe future research into classroom integration of GenAI technology.