Harvard Data Science Review Podcast

The Intelligence and Rationality of AI and Humans: A Conversation With Steven Pinker

This month, we are diving into the important and currently hot topic of artificial intelligence. Do we think rising platforms like ChatGPT are going to be running the world anytime soon? Does technology not only have the ability to be intelligent, but also rational? In this episode we get the pleasure of discussing these issues with Steven Pinker, an experimental cognitive psychologist and a popular writer on language, mind, and human nature. Listen to the conversation and find out what happens when an expert on the human mind sits down to discuss intelligence in machines with two data scientists!

Our Guest:

• Dr. Steven Pinker is the Johnstone Family Professor in the Department of Psychology at Harvard University. He conducts research on language, cognition, and social relations; writes for publications such as the New York Times, The Guardian, Time, and The Atlantic; and is the author of twelve books, including The Language Instinct, How the Mind Works, The Blank Slate, The Stuff of Thought, The Better Angels of Our Nature, The Sense of Style, Enlightenment Now, and Rationality: What It Is, Why It Seems Scarce, Why It Matters.

70 Years After the Kinsey Reports: Is Data Science Improving Our Sex Studies (and Lives?)

On today’s episode we commemorate the publication of the Kinsey Reports, two scholarly books by Alfred Kinsey on human sexual behavior, Sexual Behavior in the Human Male (1948) and Sexual Behavior in the Human Female (1953). These reports were among the earliest research studies to look at sexual behavior, but they also raise important questions for the data science community concerning ethics and bias. We explore those questions and more with the help of two experts. 

Our Guests:

• Dr. Justin Garcia, Executive Director of the Kinsey Institute and the Ruth N. Halls Professor of Gender Studies at Indiana University, and Co-Chair of Human Sexuality and Health at the Indiana University School of Medicine. 
• Dr. Carlos Rodriguez-Diaz, Associate Professor and Vice Chair of the Department of Prevention and Community Health at the Milken Institute School of Public Health at George Washington University. Dr. Rodriguez-Diaz is also the President of the Society for the Scientific Study of Sexuality. 

From Financial Markets to ChatGPT: A Conversation With Andrew Lo

What can data tell us when it comes to how our money is invested? Are there data science tools that can help us manage the ups and downs of the financial markets? How has machine learning impacted forecasting? Can we rely on AI for investment advice? On today’s episode we explore these questions and more during a deep dive discussion on financial markets with our expert guest, Professor Andrew Lo.

Our Guest:

Andrew W. Lo is the Charles and Susan Harris Professor of Finance at the MIT Sloan School of Management, Director of the MIT Laboratory for Financial Engineering, and a principal investigator at the MIT Computer Science and Artificial Intelligence Laboratory. Professor Lo was recognized for his work on financial markets by being named one of TIMEMagazine’s 100 most influential people in the world.

I Promise to Exercise Every January: Can Data Science Help My New Year’s Resolution?

It's the post-holiday season and the time when people are focused on self-improvement and getting in shape for the new year. But how do we keep and meet our fitness goals? How many days a week should we exercise? Do diet and food tracking apps actually work? In this episode we explore the data on fitness and health and discover successful strategies for keeping those New Year’s goals.  

Our guests:

• Dr. Michele Patel, clinical psychologist and instructor at Stanford University School of Medicine who conducts research on optimizing digital health interventions for treating obesity. Her latest work focuses on identifying what exactly people should be tracking (such as their steps, diet, body weight) to promote weight loss.
• Erin Como, anchor/reporter with FOX 5 DC who covers the fitness and food scene in the nation's capital. Erin hosts the popular Cooking With Como series and is a co-host of the new hit show, LION Lunch Hour, airing daily at 11am EST. 

Does Praying Work? Let’s Pray Data Science Can Help to Answer

For centuries religion has played an important role in shaping our society as a whole and determining the basis of life/purpose for individuals. Whether it’s several daily prayers, Sunday church, or the determination of what time you can eat, religion dictates day-to-day life for many. In this episode, we explore religion’s relationship to health and civic society.  Can religious practices deeply increase your quality of life, or even save it? What does the data tell us?

Our guests are:

• Dr. Melissa Deckman, CEO of Public Religion Research Institute and political scientist studying the impact of gender, religion, and age on public opinion and political behavior. She is currently working on a book about the impact of gender on the politics of Generation Z. Her most recent book is Tea Party Women (NYU Press: 2016), which examined the role of women in conservative politics.  She is also a co-author of Women and Politics, a top-selling textbook on gender politics in the United States, now in its updated fourth edition.
• Dr. Harold Koenig, Professor of Psychiatry and Behavioral Sciences, Associate Professor of Medicine, Senior Fellow in the Center for Study of Aging and Human Development, and Founding Co-Director of the Center for Spirituality, Theology and Health at Duke University. 

I Want a Perfect Face (and Bra): Can Data Science Help?

In this month’s episode, we dive into the glamorous side of data science by exploring the ways the field is being integrated in the beauty and fashion industries. We talk to two experts, a plastic surgeon and a fashion designer, about the tools and techniques they use.

Our guests are:

• Dr. Heather Levites, a fellowship-trained plastic surgeon with a special interest in advanced cosmetic surgery. She earned her undergraduate degree at MIT, her MD from the State University of New York at Stony Brook, and completed her plastic surgery training at Duke University. She currently practices in Chapel Hill, North Carolina. 
• Nini Hu, a designer and art director with over 20 years of experience working with global fashion lifestyle brands and author of AI and Creativity for HDSR. Nini is also the founder of &HER, building customizable bras using AI, eco-friendly fibers, and automated production technology. &HER uses machine learning models to bring body shape and measurements directly to production. 

It’s Election Time Again—Do We Predict Better This Time?

With the 2022 U.S. midterms right around the corner, this month’s podcast is all about elections. Who is going to win and why? In today's episode, we talk to four experts about their predictions for the upcoming midterm elections in November and how these elections might impact the presidential race in 2024. 

Our guests are:

• Caroline Carlson, Senior Data Science Analyst at Dynata and Analyst for Decision Desk HQ
• Ryan Enos, Professor of Government and Director of the Center for American Political Studies at Harvard University and co-author of Predicting the 2020 Presidential Election for HDSR
• Allan Lichtman, Distinguished Professor of History at American University and author of The Keys to the White House: Forecast for 2020 for HDSR. 
• Scott Tranter, Founder and  CEO of Øptimus Analytics and Decision Desk HQ and co-author of Forecasting the 2020 U.S. Elections with Decision Desk HQ: Methodology for Modern American Electoral Dynamics for HDSR.

 

Personalized Treatments: Is That Possible and What Can Data Science Tell Us?

Today we discuss the most important element of our lives: our health. We do so by diving into personalized medicine, or more specifically, personalized (N-of-1) trials  – clinical trials in which a single patient is the entire trial. For this episode, we invited two editors of Harvard Data Science Review’s special issue on N-of-1 trials and data science to help us examine all aspects of these clinical trials designed for a population of one person.

Our guests:

• Dr. Karina Davidson, Senior Vice President of Research and Dean of Academic Affairs at Northwell Health
• Ken Cheung, Professor of Biostatistics at Mailman School of Public Health at Columbia University

To Drink or Not to Drink: Can Data Help Us Decide?

The effects of drinking is a constant news headline. Every month or so, there seems to be a new study released that weighs the benefits and risks of drinking alcohol. Is some level of alcohol good for your health or should everyone completely avoid drinking? On today’s episode we invited two experts with differing views on alcohol consumption to help us examine the data and decide.

Our guests:

Emmanuela Gakidou, Professor of Health Metrics Sciences and Senior Director of Organizational Development and Training at the Institute for Health Metrics and Evaluation (IHME) at the University of Washington.  

Eric Rimm, Professor of Epidemiology and Nutrition and Director of the Program in Cardiovascular Epidemiology at the Harvard T.H. Chan School of Public Health and Professor of Medicine at the Harvard Medical School. 

 

Differential Privacy for the 2020 U.S. Census: Can We Make Data Both Private and Useful? (Part 2)

For today’s episode we embark on part two of our discussion on the U.S. Census. 

Protecting the data privacy of survey respondents has always been a central consideration for the U.S Census Bureau, and throughout its history, many methods have been developed and implemented. For the 2020 Census, the Bureau adopted a new form of privacy protection—differential privacy which was received with mixed reaction. To further understand why the Census Bureau adopted this new form of privacy protection and to help explore the concerns raised about differential privacy, we invited two experts who represent both sides of the debate and who each contributed to the Harvard Data Science Review special issue on the 2020 U.S. Census.

 Our guests are:

• John Abowd, Associate Director for Research and Methodology, Chief Scientist at the U.S. Census Bureau, and author of the The 2020 Census Disclosure Avoidance System TopDown Algorithm for HDSR.

• danah boyd, founder and president of Data & Society, Principal Researcher at Microsoft, Visiting Professor at New York University, and author of Differential Perspectives: Epistemic Disconnects Surrounding the U.S. Census Bureau’s Use of Differential Privacy for HDSR.