Presenter: ZiYu (Mike) Mu

Title: Real or Fake? A Proposed Study on University Students Examinations of AI Images

Type of Presentation: Oral

Abstract

My interest is driven by a question with how generative artificial intelligence interacts with humankind and challenges human judgment in this rapid growth tech era, this oral presentation conducts a proposal investigating the synthetic reality. This project is built by the multidisciplinary researchers' arguments. Kwok and Koh (2021) highlighted that deepfakes blur the boarder between factual and fake information, potentially eroding public trust. Moreover, while AI is being highly beneficial, verification has become a crucial skill (Pataranutaporn et al., 2021). However, there is a gap in understanding how effective we are at separating real from the fake images in everyday contexts. This proposed study asks how do university students evaluate the creditability of AI images, compared to the real-world images. This study applied an experimental study survey to test whether students can find fake images in a mixed AI and non-AI images group. Data will be collected and shown by the quantitative online survey, framed by Truth-Default Theory. This study expect is finding the accuracy throughout students' evaluations of AI images. However, due to the experimental design and small samples account, causing limits in my research such as lower reliance of discussion and might be unable to conduct a conclusion.

Biography

Z. Mu (Mike) is an undergraduate student at the UBC who transitioned from the Vantage One Arts Program into the Faculty of Science. With a deep interest in trustworthy AI and algorithms, He transferred into science, deciding to learn high-levels mathematics and computer science courses to find his research topic in the computer science field. Beyond the academia He also likes to play some games and watch some anime for enjoying and recharging himself.