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.

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.

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 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 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.

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

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

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.

Our guests:

• Chad Dorsey is president and CEO of the Concord Consortium, which has been an innovation leader in researching and developing STEM educational technology for the past 30 years.
• Victor R. Lee is an associate professor in the Graduate School of Education at Stanford University and is faculty lead for the Stanford Accelerator for Learning's AI + Education program.

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.

Our guests:

• Raffaella Sadun is the Charles E. Wilson Professor of Business Administration at Harvard Business School, and is a co-chair of Harvard Business School’s Project on Managing the Future of Work and co-PI of the Digital Reskilling Lab. Her research focuses on managerial and organizational drivers of productivity and growth in corporations and the public sector.
• Ben Waber is a leading thinker at the intersection of management, data, workplace, and people. He is currently a visiting scientist at MIT and a senior visiting scientist at Ritsumeikan University. Previously, he was the president and CEO of Humanyze, a workplace analytics company he co-founded.