27/03/2025 (Thursday) 13:00-14:00 E21B-G002
Un-coding AI in Everyday Life: Practices and Reasoning in AI Encounters
Abstract:
Artificial intelligence technologies, particularly large language models (LLMs) that have emerged in recent years, have introduced new variables into the human communication context. Against this backdrop, human communication behaviors have undergone significant changes at the relational, formal, and modal levels. These changes have profound implications for digital media research, creating new scenarios and opportunities for exploring how communication unfolds in digital environments.
This presentation aims to explore the transformative potential of large language models specifically within the realm of digital media research. It examines how LLMs can create “new bottles” while reconciling “old wine”—that is, how they can introduce novel methodologies and perspectives while integrating with existing frameworks and theories in digital media studies. By focusing on the intersection of AI and digital media, the presentation seeks to address two critical questions: Can large language models transform digital media research, and if so, how can this transformation be effectively realized? The presentation will delve into the development of large language models, highlighting their potential to bring new propositions to digital media research. It will also explore how LLMs can engage in dialogue with the existing trajectory of communication research, particularly in the context of digital media. By addressing both the possibility and the mechanisms of this transformation, the presentation aims to provide actionable insights into the future of digital media research in the age of AI.
Bio:
Chen Anfan is a Research Assistant Professor in the Department of Communication Studies at the School of Communication, Hong Kong Baptist University. His research interests include computational social science, political communication, science communication, and crisis communication. He has published over 60 journal articles, including in Journal of Computer-Mediated Communication, New Media & Society, Social Media & Society, Science Communication, Public Understanding of Science, International Journal of Press/Politics, Public Relations Review, among others.
