The 6 Best Data Skeptic Podcast Episodes
1) AI Decision-Making
Making a decision is a complex task. Today's guest Dongho Kim discusses how he and his team at Prowler has been building a platform that will be accessible by way of APIs and a set of pre-made scripts...Show More
2) P vs NP
In this week's episode, host Kyle Polich interviews author Lance Fortnow about whether P will ever be equal to NP and solve all of life’s problems. Fortnow begins the discussion with the example quest...Show More
3) [MINI] Bayesian Belief Networks
A Bayesian Belief Network is an acyclic directed graph composed of nodes that represent random variables and edges that imply a conditional dependence between them. It's an intuitive way of encoding y...Show More
4) [MINI] Big Oh Analysis
How long an algorithm takes to run depends on many factors including implementation details and hardware. However, the formal analysis of algorithms focuses on how they will perform in the worst case...Show More
5) Artificial Intelligence, a Podcast Approach
This episode kicks off the next theme on Data Skeptic: artificial intelligence. Kyle discusses what's to come for the show in 2018, why this topic is relevant, and how we intend to cover it.
6) The Death of a Language
USC students from the CAIS++ student organization have created a variety of novel projects under the mission statement of "artificial intelligence for social good". In this episode, Kyle interviews Za...Show More
7) Collective Altruism in Recommender Systems
Ekaterina (Kat) Filadova from MIT EECS joins us to discuss strategic learning in recommender systems—what happens when users collectively coordinate to game recommendation algorithms. Kat's research r...Show More
8) Niche vs Mainstream
Anas Buhayh discusses multi-stakeholder fairness in recommender systems and the S'mores framework—a simulation allowing users to choose between mainstream and niche algorithms. His research shows spec...Show More
9) Healthy Friction in Job Recommender Systems
In this episode, host Kyle Polich speaks with Roan Schellingerhout, a fourth-year PhD student at Maastricht University, about explainable multi-stakeholder recommender systems for job recruitment. Roa...Show More
10) Fairness in PCA-Based Recommenders
In this episode, we explore the fascinating world of recommender systems and algorithmic fairness with David Liu, Assistant Research Professor at Cornell University's Center for Data Science for Enter...Show More