Chei Sian Lee

Deepfake videos are widely recognized for their potential to manipulate and distort reality. This study aims to identify prevalent deepfake identification strategies among an often-overlooked age group, seniors (55 years and older) and how these strategies develop over time. We conducted a 3-week diary study with 30 seniors, guided by prior work on information credibility and deepfake identification. Four main deepfake identification strategy categories emerged: (1) source, (2) endorsement, (3) media, and (4) content. A common combination was the use of strategies from the media, source, and endorsement categories. Another common combination was the content, endorsement, and source categories. Notably, the number of strategy combinations employed increased over the 3-week data collection period. By incorporating a longitudinal perspective, the study offers a more dynamic understanding of how seniors’ identification strategies evolve over time. Practically, the insights from this study can inform targeted interventions and collaborative programs that aim to enhance seniors’ resilience against video-based disinformation.

Generative AI (GenAI)-related misinformation has emerged as a significant concern affecting higher education learners, yet research on mitigating this challenge through fact-checking remains limited. This research aims to examine how GenAI users process information and respond to potential misinformation generated by such tools during learning, using the lens of heuristic-systematic processing by focusing on two information processing mechanisms: heuristic (prompt, short-cut based, convenient thinking) and systematic (in-depth, critical, dedicated thinking). The study investigates the relationships between information-processing mechanisms and digital literacy, positing that digital literacy in the use of GenAI constitutes an essential competence for higher-education learners and shapes their intention to fact-check GenAI-generated responses. The study employed path analysis using self-reported survey data collected from 688 higher education learners. Findings showed that digital literacy in GenAI usage positively influences the intention to fact-check GenAI information, both directly and indirectly through information self-efficacy and user heuristics. The influence of digital literacy on the intention to fact-check GenAI Information is also sequentially mediated by systematic processing, which, in turn, influences information self-efficacy. Theoretically, this research adds to the literature on human-AI interaction and enhances our understanding of information processing by applying the dual-process theory framework, specifically in learning. The results also contribute to practice, especially in terms of underscoring the role of digital literacy in GenAI to foster fact-checking on GenAI outputs.