Be Careful What You Prompt For: Generative AI in Computational Communication Research

Le résumé fourni par la source

Generative artificial intelligence (GenAI) has field-level implications for computational communication research (CCR), not only by expanding methodological repertoires, but also by reshaping what CCR is uniquely positioned to study and contribute. This editorial argues that GenAI intersects with CCR in two analytically distinct yet connected ways: as a research tool and as an object of inquiry. As a tool, GenAI expands possibilities for content annotation, stimuli construction, simulation, multimodal analysis, and software development, while also introducing persistent challenges involving validity, reliability, reproducibility, bias, privacy, and ethical accountability. It further opens important questions in adjacent research practices such as survey/experiment design, qualitative inquiry, literature review, and theory development. As an object of study, GenAI requires analysis at multiple levels, including systemic and normative concerns, implications for media and public discourse, and everyday human–AI communication. We argue that CCR is especially well positioned to contribute because generative systems are themselves communicative technologies that reshape production, circulation, interpretation, and power across media environments. We conclude by outlining future directions for CCR, emphasizing methodological standards, ecologically valid empirical inquiry, and the field’s distinctive role in shaping the broader social science research of AI.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.