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Artwork for Data Skeptic

Data Skeptic

Kyle Polich
Large Language Models
Artificial Intelligence
Machine Learning
Generative AI
Github Copilot
Natural Language Processing
Avanade
C. Elegans
Data Science
Usability Research
AI In Software Development
Programming
Microsoft
Oil and Gas Industry
Artificial General Intelligence
Survey Methodology
HCI (human-Computer Interaction)
Data Democratization
Ethical AI
AI Ethics

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 monthlyEpisodes598Founded12 years ago
Number of ListenersCategories
MathematicsTechnologyScience

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Artwork for Data Skeptic

Latest Episodes

Ervin Dervishaj, a PhD student at the University of Copenhagen, discusses his research on disentangled representation learning in recommender systems, finding that while disentanglement strongly correlates with interpretability, it doesn't consistent... more

Ekaterina (Kat) Fedorova 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 reveals surprising findings: algorithmic "protest m... more

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 specialized recommenders improve utility for niche use... more

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. Roan discusses his research on creating AI-powered jo... more

Key Facts

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

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Recent Guests

Ekaterina Filadova
PhD student at MIT studying strategic learning.
MIT
Episode: Collective Altruism in Recommender Systems
Roan Schellingerhout
Fourth year PhD student at Maastricht University studying explainable multi-stakeholder recommender systems.
Maastricht University
Episode: Healthy Friction in Job Recommender Systems
Cory Zechmann
Content curator and music blogger, who has worked with streaming services and has his own music blog.
Slink TV, Silence Nogood
Episode: Video Recommendations in Industry
Santiago de Leon Martínez
Spanish-American researcher at the Kempelin Institute of Intelligent Technologies and Brno University of Technology, focusing on eye tracking and AI.
Kempelin Institute of Intelligent Technologies
Episode: Eye Tracking in Recommender Systems
Alberto Carlo Mario Mancino
Postdoc researcher devoted to recommender systems
SysInflab Laboratory
Episode: DataRec Library for Reproducible in Recommend Systems
Aditya Chichani
Senior Machine Learning Engineer at Walmart with a focus on recommender systems.
Walmart
Episode: Shilling Attacks on Recommender Systems
Ashmi Banerjee
Doctoral candidate at Technical University of Munich specializing in recommender systems and sustainable tourism.
Technical University of Munich
Episode: Sustainable Recommender Systems for Tourism
Kunal Mukherjee
Postdoctoral research associate at Virginia Tech focusing on graph-based intrusion detection and explanations in AI recommendations.
Virginia Tech
Episode: Interpretable Real Estate Recommendations
Dimitri Ognibene
Director of the Bicone Club at the University of Milano, Bicocca
University of Milano, Bicocca
Episode: Why Am I Seeing This?

Hosts

Ekaterina Filadova
Host providing insights on data-driven discussions and expert interviews focusing on data science and its applications.
Kyle
A knowledgeable host guiding discussions in the fields of machine learning and AI, known for his critical approach to evaluating data methods and technologies.

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 Statesa month 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 Kingdoma year 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.

Listeners appreciate the engaging and informative discussions on complex data-related topics.
Many praise the host's ability to simplify dense subjects, making them accessible to a broader audience.
Some feedback highlights the professionalism and depth of the interviews with expert guests.
Concerns have been raised about audio quality during certain episodes, detracting from the listening experience.

Chart Rankings

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

Apple Podcasts
#217
United Kingdom/Technology
Apple Podcasts
#168
Italy/Technology
Apple Podcasts
#230
Australia/Technology
Apple Podcasts
#238
Germany/Technology
Apple Podcasts
#31
Argentina/Technology
Apple Podcasts
#37
Philippines/Technology

Talking Points

Recent interactions between the hosts and their guests.

Niche vs Mainstream
Q: How are you planning to move forward with your research?
The next study involves allowing users to control what is on their algorithm, emphasizing user agency in recommendation systems.
Niche vs Mainstream
Q: How do you look at it practically?
The simulation environment allows for testing how niche and mainstream recommenders affect user experience and whether users prefer one over the other.
Niche vs Mainstream
Q: What would it mean for a recommender system to be unfair?
Unfairness in recommender systems can arise from issues such as representative fairness and allocative fairness, impacting how different groups experience recommendations.
Collective Altruism in Recommender Systems
Q: Is it going to be effective?
Simulations show that collective action can be effective in promoting underrepresented content.
Collective Altruism in Recommender Systems
Q: Is my participation going to hurt the recommendations I get today?
The theory presents conditions for Pareto improvement, indicating it's possible to help others without harming one's own recommendations.

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?

This podcast features insightful discussions and interviews on topics surrounding data science, machine learning, artificial intelligence, and statistics. Focusing on the application of critical thinking and the scientific method, each episode evaluates the claims and methods used in data collection and analysis, ensuring accuracy and relevancy. Listeners can expect a blend of expert opinions, case studies, and research findings that highlight the importance of rigorous investigation in the field of data-driven technologies. The podcast is especially notable for its emphasis on fairness, ethics, and the interaction between technology and user experiences, making it a rich resource for tech enthusiasts and professionals alike.

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How many listeners does Data Skeptic get?

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How many subscribers and views does Data Skeptic have?

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Which podcasts are similar to Data Skeptic?

These podcasts share a similar audience with Data Skeptic:

1. Practical AI
2. Dwarkesh Podcast
3. Google DeepMind: The Podcast
4. The a16z Show
5. The AI Daily Brief: Artificial Intelligence News and Analysis

How many episodes of Data Skeptic are there?

Data Skeptic launched 12 years ago and published 598 episodes to date. You can find more information about this podcast including rankings, audience demographics and engagement in our podcast database.

How do I contact Data Skeptic?

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What guests have appeared on Data Skeptic?

Recent guests on Data Skeptic include:

1. Ekaterina Filadova
2. Roan Schellingerhout
3. Cory Zechmann
4. Santiago de Leon Martínez
5. Alberto Carlo Mario Mancino
6. Aditya Chichani
7. Ashmi Banerjee
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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