Title: Disrupting Mis- and Disinformation: Educational, AI-Based, and Regulatory Countermeasures
Date: April 28, 2023
Time: 1:00pm
Room: Luddy Auditorium 1106
Abstract: Deceptive, inaccurate, or misleading content is pervasive in digital media, yet the solution remains elusive. Many of us run the risk of being woefully misinformed online in some aspects of our lives including health, finances, and politics. Why does the problem persist? What are the underlying causes? How can we move towards solutions? Taking the lead from epidemiological modeling, Rubin posits that three interacting factors causes the spread of mis- and disinformation. She proposes that simultaneous and sustained disruption of the interactions between these factors should dampen the epidemic. Three kinds of interventions include the education of susceptible minds, regulation of toxic digital environments, and automated detection of virulent “fakes.” Human minds, susceptible to being deceived and manipulated, can be more purposefully and vigorously trained in the practical skills of digital literacy. Toxic digital environments require further efforts in the legislative oversight. Given the scale of the problem, artificial intelligence (AI) can, at least in part, enhance our human intelligence, and should be employed as assistive technologies. Certain systematic analyses can reliably and accurately sift through large volumes of textual data and should be made available, and more routinely used by the general public. Such AI-based applications use natural language processing (NLP) and machine learning (ML). This talk exemplifies existing works, in which such NLP or ML systems, with varying degrees of success, automatically discriminate various types of text-based “fakes” – including clickbait, satire, other falsehoods, and rumors – from verified legitimate content and truthful language.
Bio: Victoria L. Rubin is an Associate Professor at the Faculty of Information and Media Studies and the Director of the Language and Information Technologies Research Lab (LiT.RL) at the University of Western Ontario. She specializes in information retrieval and natural language processing techniques that enable analyses of texts to identify, extract, and organize structured knowledge. She studies complex human information behaviors that are, at least partly, expressed through language such as deception, uncertainty, credibility, and emotions. Her research on Deception Detection and Automated News Verification has been published in several core workshops on these topics, in prominent information science and computational linguistics conferences, as well as the Journal of the Association for Information Science and Technology. Her project entitled Digital Deception Detection: Identifying Deliberate Misinformation in Online News was funded by the Government of Canada Social Sciences and Humanities Research Council (SSHRC) Insight Grant. In her recent textbook Misinformation and Disinformation: Detecting Fakes with the Eye and AI, Rubin (2022) puts forward a package of countermeasures to disrupt the mis- and disinformation spread (Springer Nature, Switzerland): https://doi.org/10.1007/978-3-030-95656-1