Data Skeptic

Latest Episodes:

Voting Mechanisms Aug 31, 2020

Show notes

Steven Heilman joins us to discuss his paper Designing Stable Elections.

For a general interest article, see: https://theconversation.com/the-electoral-college-is-surprisingly-vulnerable-to-popular-vote-changes-141104

Steven Heilman receives funding from the National Science Foundation. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author and do not necessarily reflect the views of the National Science Foundation.

False Consensus Aug 24, 2020

Show notes

Sami Yousif joins us to discuss the paper The Illusion of Consensus: A Failure to Distinguish Between True and False Consensus. This work empirically explores how individuals evaluate consensus under different experimental conditions reviewing online news articles.

More from Sami at samiyousif.org

Link to survey mentioned by Daniel Kerrigan: https://forms.gle/TCdGem3WTUYEP31B8

Fraud Detection in Real Time Aug 18, 2020

Show notes

In this solo episode, Kyle overviews the field of fraud detection with eCommerce as a use case. He discusses some of the techniques and system architectures used by companies to fight fraud with a focus on why these things need to be approached from a real-time perspective.

Listener Survey Review Aug 11, 2020

Show notes

In this episode, Kyle and Linhda review the results of our recent survey. Hear all about the demographic details and how we interpret these results.

Human Computer Interaction and Online Privacy Jul 27, 2020

Show notes

Moses Namara from the HATLab joins us to discuss his research into the interaction between privacy and human-computer interaction.

Authorship Attribution of Lennon McCartney Songs Jul 20, 2020

Show notes

Mark Glickman joins us to discuss the paper Data in the Life: Authorship Attribution in Lennon-McCartney Songs.

GANs Can Be Interpretable Jul 11, 2020

Show notes

Erik Härkönen joins us to discuss the paper GANSpace: Discovering Interpretable GAN Controls. During the interview, Kyle makes reference to this amazing interpretable GAN controls video and it's accompanying codebase found here. Erik mentions the GANspace collab notebook which is a rapid way to try these ideas out for yourself.