Stephan Lewandowsky: Technology and Democracy - Cognitive Pressure Points and Solutions - Lecture 7

Democracy is under threat around the world including in Europe. How does the online information landscape contribute to that threat? Everyone talks about misinformation online, but what is really happening? Are citizens really drenched in misinformation and are they affected by it? Do social media really polarize societies? And if so, is regulation the answer? Answers to those questions require an understanding of how people process information online and how their vulnerabilities might be exploited. I propose that there are several systematic pressure points between online architectures and human cognition. I highlight two pressure points that may engender a threat to democracy: First, your attention online is worth money—a lot of money—to advertisers, and so the online economy is optimized to attract and capture your attention. Platforms make money while you hang around to consume more information. The quality of that information is of little concern to the platforms. Second, virtually everything you see on the internet is curated by algorithms (e.g., the newsfeed on Facebook or Twitter). These algorithms are designed by platforms without public accountability or auditing, with the primary intent of keeping you engaged longer. Thus, if extremist and conspiratorial content can keep you engaged longer, then there is an incentive for platforms to show you that content. Those pressure points can imperil our democracy when people are being radicalized or are presented with misinformation not because they want to, but because platforms are making money by facilitating it. Only through understanding of those pressure points between how humans think and how information is presented online can we hope to change anything. I review the space of available solutions, focusing on the notion of “inoculation”, which involves providing people with the skills to avoid being misled by low-quality information. This podcast has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 870883. The information and opinions are those of the authors and do not necessarily reflect the opinion of the European Commission.