Disinformation is proliferating on the internet, and platforms are responding by attaching warnings to content. There is little evidence, however, that these warnings help users identify or avoid disinformation. In this episode of the Center for Law & Economics' vlog & podcast series, Prof. Jonathan Mayer (Princeton) discusses the study "Adapting Security Warnings to Counter Online Disinformation" with Amit Zac (ETH Zurich). In their work, Jonathan Mayer (Princeton) and his co-authors Ben Kaiser, Jerry Wei, Eli Lucherini, Kevin Lee (Princeton), and J. Nathan Matias (Cornell University) adapt methods and results from the information security warning literature in order to design and evaluate effective disinformation warnings. They show a path forward for designing effective warnings, and contribute repeatable methods for evaluating behavioral effects. They also surface a possible dilemma: disinformation warnings might be able to inform users and guide behavior, but the behavioral effects might result from user experience friction, not informed decision making. In this podcast with Amit Zac (ETH Zurich), Jonathan Mayer provides insights into the background of the study and its results. Paper References: Ben Kaiser, Jerry Wei, Eli Lucherini, and Kevin Lee - Princeton University J. Nathan Matias - Cornell University Jonathan Mayer - Princeton University Adapting Security Warnings to Counter Online Disinformation Usenix Security (2021) https://www.usenix.org/conference/usenixsecurity21/presentation/kaiser
Audio Credits for Trailer: AllttA by AllttA
