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.

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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. 

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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:

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.

Artificial intelligence has made its way into the classroom—bringing excitement, confusion, and big questions about the future of learning. In this month’s episode of the Harvard Data Science Review Podcast, we explore how AI is transforming education with guests Chad Dorsey, president and CEO of the Concord Consortium, and Victor Lee, associate professor at the Stanford Graduate School of Education. Together, they discuss how teachers and students are using AI as a creative learning partner, the myths around AI-driven “cheating,” and how data literacy can empower the next generation. The conversation also dives into critical issues of equity, curiosity, and the evolving role of educators and parents in an AI-powered world—asking what it truly means to build a more human-centered future for learning.

Tune in for an honest, hopeful look at the future of education and what it means to build a smarter, more human-centered classroom.

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Will AI replace us, reshape our work, or create opportunities we’ve never imagined? For this month’s episode experts Ben Waber and Raffaella Sadun join the podcast to help us cut through the hype and discuss AI’s real impact on jobs, skills, and organizations. Drawing from research and industry experience, they tackle the myths of total automation, the need for firm-specific experimentation, and the evolving skills and management strategies required in the age of AI. 

Join us as we take a pragmatic look at the challenges and opportunities as AI transforms how we work.

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This month, we explore how data science and AI are transforming the wine industry—from vineyard planting and grape harvesting to customer engagement. Can advanced technologies help winemakers enhance quality, promote sustainability, and better match wines to consumers—all while preserving the essential human touch? Might these innovations be applied to other products as well?

Join us as we discuss these questions and more with industry leaders Kia Behnia, CEO and co-founder of Scout, and Katerina Axelsson, CEO and founder of Tastry. Pour yourself a glass and tune in as we uncork the intersection of data, AI, and the art of winemaking.

Our Guests:

This month, we’re taking a closer look at what’s on your dinner plate. From brightly colored cereals to shelf-stable snacks, food dyes, preservatives, and ultra-processed foods are found everywhere. But are they safe? Are they necessary—or could they actually be harmful? In this episode, we speak with leading experts in food science and public health to separate fact from fear. What does the evidence really say about these controversial ingredients? Are recent legislative bans rooted in science, or are other factors at play? Join us as we unpack the science, the politics, and the public perception behind what we eat.

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Once the stuff of science fiction, deepfake technology has rapidly become one of the most powerful—and consequential—applications of generative AI, blurring the line between reality and illusion and reshaping how we trust what we see and hear online. This month we delve into this phenomenon with Professor Hany Farid, a pioneer in digital forensics, and  Professor Siwei Lyu, whose lab develops state-of-the-art deepfake detection methods.Together, they’ll walk us through the data journey—from the vast raw data sets that fuel synthetic media to the pixel-level signatures that can unmask it. Whether you’re a computer scientist, policymaker, or simply curious about how synthetic content is transforming our information landscape, join us for an in-depth conversation about turning data into both convincing illusions and robust defenses—and learn how we can preserve trust and truth in our rapidly evolving digital world.

Our guests:

This month, we welcome back one of our most popular guests—MIT Professor Andrew Lo—for an insightful exploration into the complexities of tariffs. In this episode, we break down what tariffs are, how they work, and their far-reaching economic and political impacts. Our conversation delves into the challenges of predicting tariff outcomes, the need for better data-driven policies, and offers practical advice for individual investors navigating periods of economic uncertainty. Join us for a fascinating deep dive into the world of economic policy

Our guest:  Andrew W. Lo is the Charles E. and Susan T. Harris Professor of Finance at the MIT Sloan School of Management.