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Artwork for Data Skeptic

Data Skeptic

Kyle Polich
Recommender Systems
Machine Learning
Large Language Models
Network Science
Artificial Intelligence
Data Science
Animal Behavior
Graph Theory
Computer Vision
Network Analysis
Social Network Analysis
Generative AI
Community Detection
Social Media
Graph Neural Networks
Criminal Networks
Graph Databases
Natural Language Processing
Lemurs
Fraud Detection

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.

PublishesTwice monthlyEpisodes611Founded12 years ago
Number of ListenersCategories
TechnologyMathematicsScience

Listen to this Podcast

Artwork for Data Skeptic

Latest Episodes

The next evolution of wearable technology may not require new screens or controllers, but new ways to interact with the devices we already wear. Shimon explores how gesture-sensing earbuds could transform virtual reality and wearable computing throug... more

How do we design robots and autonomous vehicles that understand the unwritten rules of human behavior? Kyle speaks with Cornell Tech professor Wendy Ju about implicit interaction, "Wizard of Oz" prototyping, and what studying pedestrians, self-drivin... more

The data we collect about ourselves can tell us a lot—but only if the technology collecting it actually fits into our lives. Daniel Epstein explores personal informatics, from fitness trackers and food journals to baby tracking and AI, and explains w... more

In the final episode of our Recommender Systems season, we explore the growing questions of trust, manipulation, privacy, fairness, sustainability, and user control. From fake reviews and shilling attacks to explainable recommendations and user-selec... more

Key Facts

Accepts Guests
Accepts Sponsors
Contact Information
Podcast Host
Number of Listeners
Find out how many people listen to this podcast per episode and each month.

Recent Guests

Sheik Shaan Arifin Shimon
Doctoral researcher in human-computer interaction at the University of Waterloo
University of Waterloo
Episode: Gestures Around the Ear
Wendy Ju
Professor at Cornell Tech
Cornell Tech
Episode: Implicit Interactions
Daniel Epstein
Associate professor in the Department of Informatics at UC Irvine
University of California, Irvine
Episode: The Lived Informatics Model
Rowan Schellingerhout
PhD student focused on explainable recommenders
Maastricht University
Episode: Recommender Systems Today and Tomorrow
Robin Burke
Researcher contributing prognostications on recommender futures
Episode: Recommender Systems Today and Tomorrow
Fu Yanli
Researcher focusing on user control and interaction with recommendations
Episode: Recommender Systems Today and Tomorrow
Anas Buhai
Researcher presenting alternative models and user-centric approaches
Episode: Recommender Systems Today and Tomorrow
Kunal Mukherjee
Applied Scientist at Zillow
Zillow
Episode: Recommender Systems Today and Tomorrow
Aditya Chichani
Researcher focusing on shilling attacks and defenses
Episode: Recommender Systems Today and Tomorrow

Hosts

Kerry
Host affiliated with Data Skeptic; appears as a primary host across episodes.
Kyle
Co-host and lead presenter on recommender systems topics.

Reviews

4.6 out of 5 stars from 1k ratings
  • LOVE THE SHOW

    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?

    Apple Podcasts
    5
    Cdascientist
    United States8 months ago
  • A gem of a podcast

    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!

    Apple Podcasts
    5
    AH24Z
    United Kingdom2 years ago
  • great

    great

    Apple Podcasts
    4
    JVo12
    Canada3 years ago
  • Nice podcast

    Listen it to learn industry English and new technology . Really good for me

    Apple Podcasts
    5
    jiazhi chao
    China3 years ago
  • Great resource

    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!

    Apple Podcasts
    5
    calzone.onsets
    United States3 years ago

Listeners Say

Key themes from listener reviews, highlighting what works and what could be improved about the show.

Guests are consistently strong and diverse in expertise, offering valuable insights for research and practice.
Listeners praise the depth and breadth of topics, noting accessibility despite technical complexity.
Some listeners critique mic/production quality and co-host dynamics, suggesting more balanced conversations.

Chart Rankings

How this podcast ranks in the Apple Podcasts, Spotify and YouTube charts.

Apple Podcasts
#245
Germany/Technology
Apple Podcasts
#56
India/Technology
Apple Podcasts
#153
South Africa/Technology
Apple Podcasts
#189
China/Technology
Apple Podcasts
#214
Saudi Arabia/Technology
Apple Podcasts
#232
Indonesia/Technology

Talking Points

Recent interactions between the hosts and their guests.

Gestures Around the Ear
Q: How do you measure whether one approach is better than another?
The researchers measured task completion times between sequential tasks and used standard VR experience questionnaires to assess participants' comfort with each interaction approach.
Gestures Around the Ear
Q: Could you describe what the experiment was like for a participant who put on the goggles?
Participants completed varied tasks in a VR maze, including navigating, crouching, jumping and interacting with objects. Researchers compared controllers, gestures in front of the headset and gestures around the earbud.
Social Choice for Fair Recommendations
Q: Could you talk a little bit about how you chose to implement the aggregation of multiple fairness concerns?
We use a social-choice-inspired framework where multiple fairness agents vote on the final ranking, producing a re-ranked list that balances user interests with several fairness objectives without retraining the main recommender.
Give Users the Wheel
Q: What do LLMs unlock for this opportunity, and how does the UI change with this approach?
LLMs enable a chat-like, natural interaction that bypasses complicated UI designs; users can instruct the system with nuanced prompts, and the model can interpret and apply these instructions during ranking and filtering, reducing the burden of traditional UI/HCI development.
Give Users the Wheel
Q: Can you give listeners a sense of what's under the umbrella of this framework and how it fits into current recommender systems?
The framework starts with offshore embeddings from language models, uses standard sequential recommender models for the base predictions, and then fuses the language-model and user-instruction signals through two hidden representations to guide final recommendations without re-training the entire system.

Audience Metrics

Listeners, social reach, demographics and more for this podcast.

Listeners per Episode
Gender Skew
Location
Interests
Professions
Age Range
Household Income
Social Media Reach

Frequently Asked Questions About Data Skeptic

What is Data Skeptic about and what kind of topics does it cover?

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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How many episodes of Data Skeptic are there?

Data Skeptic launched 12 years ago and published 611 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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What guests have appeared on Data Skeptic?

Recent guests on Data Skeptic include:

1. Sheik Shaan Arifin Shimon
2. Wendy Ju
3. Daniel Epstein
4. Rowan Schellingerhout
5. Robin Burke
6. Fu Yanli
7. Anas Buhai
8. Kunal Mukherjee

To view more recent guests and their details, simply upgrade your Rephonic account. You'll also get access to a typical guest profile to help you decide if the show is worth pitching.

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