Harvard Data Science Review Podcast

Harvard Data Science Review

Artificial Intelligence

Data Science

Generative AI

Creativity

Dating Apps

Ethics

Public Health

Synthetic Food Dyes

Education

Misinformation

Communication Science

Privacy

Food Safety

Fashion

Music

Art

Audience Perception

United Nations Refugee Agency

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Brought to you by the award winning journal, Harvard Data Science Review, our podcast highlights news, policy, and business through the lens of data science. Each episode is a “case study” into how data is used to lead, mislead, manipulate, and inform the important decisions facing us today.

57 ratings

Publishes	Monthly	Episodes	68	Founded	5 years ago
Number of Listeners		Categories	Tech NewsNewsNews Commentary

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Latest Episodes

The Impact of AI on Podcasts: From Linear Digression to SuperDataScience

This month’s episode of the Harvard Data Science Review Podcast turns the microphone on two people who regularly bring data science, machine learning, and AI to podcast audiences: Katie Malone, host of Linear Digressions, and Jon Krohn, host of Super... more

31 Aug 2026 • 28 min

Active Industrial Learning: What We've Learned—and What We'd Like to Learn From You

This month’s episode of the Harvard Data Science Review Podcast takes listeners behind the scenes of Active Industrial Learning, HDSR’s column exploring how data science and AI are applied in real organizations. We speak with column co-editors Hamit ... more

27 Jul 2026 • 30 min • Most popular

Recreations in Randomness: From Glicko Rating to World Cup

This month’s episode of the Harvard Data Science Review Podcast explores the rapidly evolving world of sports analytics and how advances in data science are transforming the way we understand competition. We are joined by Harvard statistician Mark Gl... more

30 Jun 2026 • 39 min

The Judgment of Paris at 50: Wine, Wisdom, and What We Still Don’t Know

This month’s episode of the Harvard Data Science Review Podcast uncorks the fascinating intersection of wine, judgment, and data science. Economist and wine expert Orley Ashenfelter and Master of Wine Susan Lin join us to explore the enduring legacy ... more

1 Jun 2026 • 29 min

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Recent Guests

Hamit Hamutcu

Co-founder of the Initiative for Analytics and Data Science Standards

Initiative for Analytics and Data Science Standards

Episode: Active Industrial Learning: What We've Learned—and What We'd Like to Learn From You

Miguel Perdi

Partner at Kearney; Executive Fellow at Harvard Business School

Kearney; Harvard Business School

Episode: Active Industrial Learning: What We've Learned—and What We'd Like to Learn From You

Mark Glickman

Senior Lecturer in Statistics at Harvard; creator of the Glicko Rating System

Harvard University

Episode: Recreations in Randomness: From Glicko Rating to World Cup

Stephanie Kovalchik

Sports statistician focusing on tennis analytics

Harvard University / Tennis analytics community

Episode: Recreations in Randomness: From Glicko Rating to World Cup

Orley Clark Ashenfelter

Economist and wine enthusiast

Princeton University

Episode: The Judgment of Paris at 50: Wine, Wisdom, and What We Still Don’t Know

Susan Lin

Master of Wine and artist

Unspecified in transcript (Princeton context)

Episode: The Judgment of Paris at 50: Wine, Wisdom, and What We Still Don’t Know

Stephanie Dick

Historian of mathematics and technology with a focus on artificial intelligence

Harvard Data Science Review

Episode: What Can We Learn From The Histories of AI: A Conversation With Stephanie Dick

Tyler VanderWeele

John L. Loeb and Frances Lehman Loeb Professor of Epidemiology; Director of the Human Flourishing Program, Harvard

Harvard TH. Chan School of Public Health

Episode: Spiritual Enlightenment and AI Enhancement: Can They Align?

Noreen Herzfeld

Nicholas and Bernice Rutter Professor of Science and Religion, St. John's University

St. John's University

Episode: Spiritual Enlightenment and AI Enhancement: Can They Align?

Hosts

Liberty Vitter Capito

Host affiliations consistently with the Harvard Data Science Review; seasoned editor/host focusing on data science literacy, policy, and application.

Shally Knight

Editor-in-chief and co-host with roles in content curation and guest selection.

Shaili Neng

Co-host and editor-in-chief; contributes editorial perspective.

Reviews

4.5 out of 5 stars from 57 ratings

The tariff episode is the best podcast on this topic
When a true expert explains a topic, they are able to simplify complex issues in a way that anybody can understand. The chosen topics are super relevant, and the interviewers and experts do a great job at being entertaining and explaining the use of data.
Apple Podcasts
5
InesHoy
United Statesa year ago
Loved it
Keep making this stuff !! I am here to listen :) Don’t stop .
Apple Podcasts
5
ilovetensor
India3 years ago
exceptional
awesome
Apple Podcasts
5
JVo12
Canada4 years ago
Great
Love these monthly data updates!
Apple Podcasts
5
v465carol
United States4 years ago
Why talk about aliens?
Started good but now has sensationalist alien journalists.
Apple Podcasts
1
Will nickname not taken angel
United States4 years ago

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Listeners Say

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

Thoughtful, practitioner-focused discussions with real-world applicability.

Consistent emphasis on data ethics and governance is appreciated by sponsors and guests alike.

Generally high-quality and educational, with occasional off-topic episodes.

Some listeners feel certain episodes tilt toward sensational topics.

Covers a wide range of topics from AI to data literacy with strong guest expertise.

Chart Rankings

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

Apple Podcasts	#54	United States/News/Tech News
Apple Podcasts	#100	United Kingdom/News/Tech News
Apple Podcasts	#172	Canada/News/Tech News
Apple Podcasts	#50	Germany/News/Tech News
Apple Podcasts	#85	Italy/News/Tech News
Apple Podcasts	#138	France/News/Tech News

Talking Points

Recent interactions between the hosts and their guests.

Recreations in Randomness: From Glicko Rating to World Cup

Q: Mark, your rating system has become the gold standard; can probabilistic models compete with raw neural pattern recognition, and will they remain relevant as AI evolves?

Mark argues that traditional rating systems remain robust in simple outcome settings, while more powerful techniques may help track ability changes over time; the dialogue acknowledges that context and data availability shape which methods are most effective.

Recreations in Randomness: From Glicko Rating to World Cup

Q: Steph, do you have anything to add here?

Stephanie expands on how tournament design and the structure of events like the World Cup introduce unpredictability, and how data-driven methods must account for limited sample sizes and the role of fan engagement in these decisions.

What Can We Learn From The Histories of AI: A Conversation With Stephanie Dick

Q: What can historical lessons teach us about predictive policing and policing data?

Historical lessons show that transforming a task to fit a computer can oversimplify problems and embed biases, so we must be mindful of how data and algorithms redefine human tasks and identities in policing.

What Can We Learn From The Histories of AI: A Conversation With Stephanie Dick

Q: What is the relationship between raw data and human values, and how does this affect current AI systems?

She argues that there is no such thing as raw data; all data are infused with human decisions about what to count and how, which means data-driven systems inherit those biases and values.

What Can We Learn From The Histories of AI: A Conversation With Stephanie Dick

Q: So if you can just start by telling the broad audience HDSR, like what do you actually do as a historian of science?

Stephanie explains that history of science is a distinct field that studies how knowledge changes over time, focusing on how what counts as knowledge is influenced by social and historical contexts, and how this shapes our understanding of technologies like AI.

Audience Metrics

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

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Frequently Asked Questions About Harvard Data Science Review Podcast

What is Harvard Data Science Review Podcast about and what kind of topics does it cover?

This show centers on how data science informs real-world decisions across business, policy, sport, education, and culture. Episodes emphasize practitioners' experiences, practical data literacy, and the societal implications of AI—often featuring academics, industry leaders, and practitioners who bridge theory and application. Notable threads include practical data usage in organizations, data-driven decision-making in sports and economics, and ethical questions around AI, transparency, and governance. A strength is its ability to mix historical or philosophical context with hands-on case studies, creating conversations that are informative for both practitioners and decision-makers seeking grounded, implementable insights.

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Which podcasts are similar to Harvard Data Science Review Podcast?

These podcasts share a similar audience with Harvard Data Science Review Podcast:

1. Super Data Science: ML & AI Podcast with Jon Krohn
2. HBS Managing the Future of Work
3. HBR IdeaCast
4. Hard Fork
5. The AI Daily Brief: Artificial Intelligence News and Analysis

How many episodes of Harvard Data Science Review Podcast are there?

Harvard Data Science Review Podcast launched 5 years ago and published 68 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 Harvard Data Science Review Podcast?

Our systems regularly scour the web to find email addresses and social media links for this podcast. We scanned the web and collated all of the contact information that we could find in our podcast database. But in the unlikely event that you can't find what you're looking for, our concierge service lets you request our research team to source better contacts for you.

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What guests have appeared on Harvard Data Science Review Podcast?

Recent guests on Harvard Data Science Review Podcast include:

1. Hamit Hamutcu
2. Miguel Perdi
3. Mark Glickman
4. Stephanie Kovalchik
5. Orley Clark Ashenfelter
6. Susan Lin
7. Stephanie Dick
8. Tyler VanderWeele

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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