This article focuses on the unique ways that technical and professional communication (TPC) researchers can study artificial intelligence (AI) models that challenge the idea that humans and machines are separate yet equal entities. The authors present a brief definition of AI, a recap of HCI research paradigms, and a description of how AI models challenge traditional HCI research and how TPC researchers might respond to these challenges in their studies. Rather than presenting clear-cut methods for studying AI, the article highlights questions that researchers need to consider as they develop approaches for studying AI.

Though the remote internship is certainly not a new phenomenon, the COVID-19 pandemic has accelerated the growth of this model for undergraduate experiential learning. As we consider this shift, we must evaluate how to best assist students completing remote internships. In this article, we argue that infrastructure offers a useful framework for understanding students’ internship experience and corresponding professionalization. We present two case studies of student remote internship experiences, analyzing areas of challenge and success through the infrastructural areas of writing projects, communication, and logistics. We offer recommendations for faculty working with remote student interns to promote positive learning experiences.