Sorry for the unannounced hiatus that has now lasted for four years, but our host and producer Sam Hansen has had a lot of life events and changes that led them to not be able to devote the time they needed to making the show. We are planning on coming back very soon, but until then please enjoy this episode about the Mathematics of Voting from the podcast Carry the Two made by the Institute for Mathematical and Statistical Innovation where Sam is the new Director of Communications and Engagement.

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IMSI is very proud to announce that Carry the Two is back and with a new co-host, IMSI’s new Director of Communications and Engagement Sam Hansen!

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We in the United States are deep in the middle of a major national election, and over half of the world’s population also have elections in 2024. This is why Carry the Two is going to focus on the intersection of mathematics and democracy for our new season.

In this episode, the first episode of our mathematics and democracy season, we speak with mathematician Ismar Volić of Wellesley College and Director of the Institute for Mathematics and Democracy and Victoria Mooers, an economics PhD student at Columbia University. We discuss what mathematics has to say about our current plurality voting system, how switching to preference ranking votings systems could limit polarization and negative campaigning, and why too much delegation causes problems for those pushing for Liquid Democracy.  

Find our transcript here: Google Doc or .txt file

Curious to learn more? Check out these additional links:

Ismar Volić

Making Democracy Count: How Mathematics Improves Voting, Electoral Maps, and Representation 

Institute for Mathematics and Democracy

Victoria Mooers

Liquid Democracy. Two Experiments on Delegation in Voting

Follow more of IMSI’s work: www.IMSI.institute, (twitter) @IMSI_institute, (mastodon) https://sciencemastodon.com/@IMSI, (instagram) IMSI.institute

Music by Blue Dot Sessions and lowercase n

The Institute for Mathematical and Statistical Innovation (IMSI) is funded by NSF grant DMS-1929348