Infodemiology, with Jens Koed Madsen

This week, Turi talks with Jens Koed Madsen who builds computer simulation models to understand complex systems. His latest experiments map the flow of information - testing the theory of the ‘marketplace of ideas’ to the limit.

S2 E14: Infodemiology

“The more we increase the connectivity of people, the more people get stuck in extreme positions and echo chambers on the extreme edges of our belief structures.”

In December 2017, Jens Koed Madsen heard Mark Zuckerberg talking about the power of connectivity. Zuckerberg’s hypothesis was that the more people were connected, the more quickly we would filter out bad ideas - a reworking of John Stuart Mill’s classic theory of the marketplace of ideas.

To test it, Jens built a computer model of a social network - full of rational agents sharing information with each other. What he found is disturbing: the larger the network of agents (or citizens, or Facebook users), the faster it builds echo chambers, and the more radicalised those echo chambers become.

“Nobody ever starts extreme - they’re pushed into it through connectivity”

We have spent years focusing on ‘fake news’, misinformation, gullible readers, on the design ethics of the platforms, on political manipulation and propaganda. But Jens’ research shows that it’s the very architecture of our social networks that polarises us.

Listen to him explain his experiment Large Networks of Rational Agents form Persistent Echo Chambers, as well as a forthcoming paper on the role broadcasters play in the media ecosystem - and attempt to look at how we can fix our infodemic.

“Media is an ecosystem. In the same way that an epidemiologist describes the spread of diseases, we do infodemiology - tracking the spread of misinformation across complex dynamic systems.”

Works cited include:

Read the Full Transcript

Jens Koed Madsen

Jens Koed Madsen is a Cognitive Psychologist at LSE. He is interested in misinformation and complex human environments, and how people change their beliefs and act in social networks.

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This page was last edited on Wednesday, 7 Apr 2021 at 09:51 UTC