Title:
Combating Multimodal Disinformation in the Age of AI: A Media Literacy Approach

Abstract:
The rise of generative artificial intelligence (AI) has supercharged the proliferation of multimodal disinformation or so-called “deepfakes.” The surge in the volume of deepfakes and their alarming adverse impacts have raised serious concerns not only about deepfakes’ manipulative capabilities but also about the erosion of public trust in the integrity of online information environments. In this talk, she will first provide an overview of AI-enabled multimodal disinformation and discuss its characteristics and effects. Next, she will discuss media literacy education as a viable approach to addressing the challenges posed by AI-enabled multimodal disinformation and share two empirical studies that tested the effectiveness of various media literacy interventions aimed at improving people’s resilience against deepfakes. She will conclude with a discussion on potential future directions for this line of research.

Speaker Bio:
Dr. Guanxiong Huang is Associate Professor of Persuasive Communication and the Co-Convenor of the Digital Learning and Literacy Research Cluster in the College of Liberal Arts and Social Sciences at City University of Hong Kong. Her research interests include media psychology, persuasion, and health and science communication. Her current research focuses on the role of AI in human communication and on addressing the challenges AI poses to the information ecosystem. Many of her studies have been published in top-tier communication journals, including Communication Research, Health Communication, Journal of Communication, New Media & Society, and Science Communication. Her research on media literacy was cited by the Scottish Government and Australia’s National Science and Technology Council in their policy documents to inform measures for strengthening resilience to misinformation.

If you are interested in attending this research talk, please scan the QR code or click here: Research Talk with Dr Guanxiong Huang – Fill out form