
The Data Skeptic Podcast features interviews and discussion of topics related to data science, statistics, machine learning, artificial intelligence and the like, all from the perspective of applying critical thinking and the scientific method to evaluate the veracity of claims and efficacy of approaches.
| Publishes | Twice monthly | Episodes | 607 | Founded | 12 years ago |
|---|---|---|---|---|---|
| Number of Listeners | Categories | TechnologyMathematicsScience | |||

In part two of the Data Skeptic Recommender Systems season finale, Kyle asks a deceptively difficult question: what should recommender systems actually optimize for? Drawing on conversations from across the season, the episode explores engagement, fi... more
Where did recommender systems come from, and how do we know when they're actually working? In part one of Data Skeptic's three-part Recommender Systems finale, Kyle traces the field from collaborative filtering and the Netflix Prize to matrix factori... more
Recommender systems influence nearly every aspect of our digital lives—but what does it mean for those systems to be fair? Robin Burke joins Data Skeptic to discuss the history of recommender systems, the limitations of optimizing purely for accuracy... more
News recommendation algorithms influence far more than what stories we click—they can shape our understanding of the world. In this episode, Kyle Polich speaks with Andreea Iana about responsible AI, filter bubbles, multilingual news recommendation, ... more
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I just absolutely love the show and I’m just wondering if maybe you can cover as a topic sub polynomial compute for graph networks?
I am not a data scientist, but I very much enjoy the podcast! It is fascinating, the interviewer’s really know their field and it has provided me with topics that could be interesting to follow-up. If you are interested in technology, or a student, then this is a podcast that is well worth following and listening to. Top marks!
great
Listen it to learn industry English and new technology . Really good for me
A colleague introduced me to Data Skeptic last year and I’ve been enjoying the episodes. Kyle’s good at covering topics from many levels of data science understanding—his mini series with a non-data scientist are a great way to learn the basics!
Key themes from listener reviews, highlighting what works and what could be improved about the show.
How this podcast ranks in the Apple Podcasts, Spotify and YouTube charts.
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Apple Podcasts | #30 |
Recent interactions between the hosts and their guests.
Listeners, social reach, demographics and more for this podcast.
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The show centers on data science, statistics, ML, and AI, with frequent deep dives into practical methods, fairness, interpretability, and the societal implications of algorithmic systems. Episodes mix theory, architecture, and real-world case studies, often featuring researchers and practitioners who discuss how to apply rigorous thinking to complex data problems. A notable strength is the breadth of topics within recommender systems, responsible AI, and governance, rendered through accessible interviews that balance technical depth with practical insights. Listeners can expect thoughtful exploration of cutting-edge methods, evaluation challenges, and multi-stakeholder perspectives, making it valuable for both technical professionals and l... more
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These podcasts share a similar audience with Data Skeptic:
1. Super Data Science: ML & AI Podcast with Jon Krohn
2. Practical AI
3. DataFramed
4. Machine Learning Street Talk (MLST)
5. Google DeepMind: The Podcast
Data Skeptic launched 12 years ago and published 607 episodes to date. You can find more information about this podcast including rankings, audience demographics and engagement in our podcast database.
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Recent guests on Data Skeptic include:
1. Andrea Ayanna
2. Santiago de Leon
3. Asaf Shapiro
4. Robin Burke
5. Andreea Iana
6. Fuyuan Lyu
7. Hieu Le
8. Aaron Payne
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