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Harvard Data Science Review Podcast

Harvard Data Science Review Podcast

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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.Copyright 2021 All rights reserved. Política y Gobierno
Episodios
  • Better Data, Better Date?
    Feb 27 2026

    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.
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    27 m
  • Masterminds and Mindware for Agentic AI: Contextualized and Applied
    Jan 29 2026

    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
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    27 m
  • Digital Twins and Virtual Twins: What Are They and What Do They Do for Humans?
    Dec 23 2025

    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
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    38 m
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