Harvard Data Science Review Podcast

Harvard Data Science Review
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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.

  1. 1 day ago

    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 Glickman, creator of the Glicko rating system, and sports statistician Stephanie Kovalchik to discuss the technologies, models, and data driving modern sports. From real-time player tracking and probabilistic rating systems to AI-assisted coaching and predictive modeling, the conversation examines how statistical methods continue to shape decision-making on and off the field. Glickman and Kovalchik also explore why traditional statistical models remain central to sports analytics, how access to high-quality data continues to limit innovation, and what emerging AI tools may—and may not—bring to the future of the field. The episode concludes with a look at Recreations in Randomness, HDSR’s column on the many ways data science enriches our recreational lives, and an invitation for readers to contribute new perspectives on the growing role of data in sports, hobbies, and beyond. Our guests: Mark Glickman is a senior lecturer on statistics at Harvard University; a senior statistician at the Center for Healthcare Organization and Implementation Research (CHOIR), a Veterans Administration Center of Innovation; and co-editor of HDSR’s Recreations in Randomness column. Stephanie Kovalchik is a senior manager of data science at Teamworks, where she develops data-driven solutions to enhance athlete performance and decision-making. She is also co-editor of HDSR’s Recreations in Randomness column.

    40 min

  2. 1 Jun

    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 of the 1976 “Judgment of Paris,” the blind tasting that reshaped perceptions of wine quality and transformed the global wine industry.  From statistical analysis of wine rankings to the psychology of taste perception, the conversation examines how experts evaluate wine and why even trained judges often disagree. Ashenfelter reflects on decades of wine tasting data and the role of probability, humility, and climate modeling in understanding wine quality, while Lin shares insights from her groundbreaking research on how music influences the perception of champagne. Together, they explore the complex relationship between sensory experience, human judgment, and data, revealing that wine may be as much about context, memory, and emotion as it is about chemistry and statistics. Our guests: Orley Ashenfelter is the Joseph Douglas Green 1895 Professor of Economics at Princeton University, transferred to emeritus status in 2024. Orley is known for his seminal research in labor economics, econometrics, and law and economics Susan R. Lin is a Master of Wine and a Master of Fine Arts in Classical Piano and Musicology. She creates memorable experiences through music and wine.

    30 min

  3. 30 Apr

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

    What can history teach us about today’s AI revolution? In this month’s episode of the Harvard Data Science Review Podcast, we are joined by Stephanie Dick, a historian of science and technology, to explore how past ideas about knowledge and intelligence shape today’s AI systems.  Drawing on examples from early AI, including facial recognition and police databanks, Dick shows that technical decisions are never purely technical—they reflect assumptions about knowledge, people, and power. Tracing AI through three historical “acts,” she challenges the idea that contemporary AI systems represent a clean break from the past. Dick also questions the pursuit of artificial general intelligence, emphasizing instead that intelligence is plural, embodied, and fundamentally relational. This conversation offers a fresh perspective for anyone building, studying, or thinking about AI today. Our guest: Stephanie Dick is an historian, speaker, and writer who works at the intersections of mathematics, computing, and artificial Intelligence. She is also an assistant professor in the School of Communication at Simon Fraser University and the co-editor of HDSR’s Mining the Past column.

    45 min

  4. 30 Mar

    Spiritual Enlightenment and AI Enhancement: Can They Align?

    In this month’s episode of the Harvard Data Science Review Podcast, we explore a timeless yet increasingly urgent question: What does it mean to flourish as a human being in an age of artificial intelligence? We are joined by experts Noreen Herzfeld and Tyler VanderWeele, who together bring empirical, philosophical, and theological perspectives to a wide-ranging conversation on human well-being, relationships, and the role of technology in each. The guests examine whether AI can support human flourishing—or whether it may erode the very capacities that make flourishing possible. They discuss the limits of AI in addressing deeper human longings for meaning and transcendence, the risks of replacing human connection with artificial interaction, and the ethical responsibilities of developers in shaping these tools. This episode invites listeners to reflect on what it truly means to live well in a technological age. Join in and add your voice to the conversation. The episode also highlights Dr. VanderWeele’s recent Psychology Today article, “Can We Remain Human in the Age of AI” and Dr. Herzfeld’s recent writings. Our guests: Noreen Herzfeld is the director of the Benedictine Spirituality and the Environment program at Saint John’s School of Theology and Seminary. Tyler VanderWeele is the John L. Loeb and Frances Lehman Loeb Professor of Epidemiology and the director of the Human Flourishing Program and the co-director of the Initiative on Health, Spirituality, and Religion at Harvard University.

    34 min

  5. 27 Feb

    Better Data, Better Date?

    This month on the Harvard Data Science Review Podcast, we explore the data behind modern dating. With millions of swipes happening daily, dating apps promise compatibility through algorithms—but do they really optimize for lasting connection? Host Liberty Vittert-Capito and guest co-host and HDSR column editor Miguel Paredes sit down with Linx Dating Founder and CEO Amy Andersen and Three Day Rule CEO Adam Cohen-Aslatei to examine the tension between human intuition and algorithmic matching. Drawing on decades of experience and tens of thousands of successful matches, they discuss what people say they want versus what they actually need.. From swipe data to AI-powered date coaching, this episode asks a provocative question: Can technology guide us to love, or is chemistry still beyond the reach of code? Listen in for a data-driven perspective on romance in the digital age. Our guests: Amy Andersen is the founder and CEO of Linx Dating, a private offline dating and social network located in the heart of Silicon Valley. Adam Cohen-Aslatei is the CEO of Three Day Rule, a personalized, high-end matchmaking service.

    27 min

  6. 29 Jan

    Masterminds and Mindware for Agentic AI: Contextualized and Applied

    Agentic AI is moving beyond assistive tools toward systems that can reason, plan, and act within complex workflows. In the latest episode of the Harvard Data Science Review Podcast,  we speak with Dirk Hofmann and Ulla Kruhse-Lehtonen, co-founders and co-CEOs of DAIN Studios, about what this shift means for organizations in practice. The conversation explores how agentic AI differs from traditional automation, why outcomes matter more than outputs, and how humans and AI agents can work together responsibly. Drawing on their long-standing work in data and AI strategy, Hofmann and Kruhse-Lehtonen offer practical insights into strategy, governance, and the evolving “mindware” required to make agentic AI deliver real value. The episode also highlights their forthcoming HDSR article, “The Agent-Centric Enterprise: Why 2–10x Productivity Gains Demand Radical Workflow Redesign,” and their joint online course with the Harvard Data Science Initiative, Agentic AI: Contextualized and Applied, which focuses on applying agentic systems responsibly in real organizational settings.  Our guests: Dirk Hofman is the co-founder DAIN Studios and CEO of DAIN Studios Germany Ulla Kruhse-Lehtonen is the co-founder of DAIN Studies and CEO of DAIN Studies Finland

    27 min

  7. 23/12/2025

    Digital Twins and Virtual Twins: What Are They and What Do They Do for Humans?

    In this month’s episode of the Harvard Data Science Review Podcast, we explore the rapidly evolving concept of digital twins—dynamic, data-driven replicas of complex systems—and their growing influence across engineering, cities, healthcare, and society at large. Blending real-world case studies with big-picture insight, the discussion highlights how real-time data, sophisticated models, and massive computing power converge to let us safely test ideas, anticipate disruptions, and design smarter systems. Just as importantly, the episode tackles the critical questions of ethics, privacy, and public trust, making it an essential listen for anyone interested in where data science is headed—and how it can responsibly shape the world we live in. Our guests: Rachel Franklin is the executive director of the Center for Geographic Analysis at Harvard University  Patrick Johnson is the executive vice president of Corporate Research and Science at Dassault Systèmes

    38 min

  8. 20/11/2025

    Tracking the Most Intoxicating Data: A Conversation With Eric LeVine

    Fine wine meets data science in this month’s episode of the Harvard Data Science Review Podcast. Hosts Liberty Vittert Capito and Xiao-Li Meng explore how data, taste, and technology intertwine with Eric LeVine, founder of CellarTracker, the world’s largest community-driven wine database. What began as a personal project for managing a home cellar has evolved into a global platform with millions of users and billions of data points on wines, prices, and human preferences.  During the conversation, they unpack the origins of CellarTracker at Microsoft, how big data and machine learning reveal trends in taste and behavior, and the use of AI to predict “Will I like this wine?” They investigate how to find your digital wine twin, data quality and privacy, and how AI could change how we buy, drink, and enjoy wine without losing the human touch. Grab a glass and join us for a thoughtful conversation about curiosity, community, and enjoying life—responsibly. Our guest: Eric LeVine is president and CEO of CellarTracker, the world’s most comprehensive database. Previously he was a group program manager at Microsoft.

    38 min
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About

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.

Information

  • Creator
    Harvard Data Science Review
  • Years Active
    2021 - 2026
  • Episodes
    66
  • Rating
    Clean
  • Copyright
    © Copyright 2021 All rights reserved.
  • Show Website
    Harvard Data Science Review Podcast

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