The Harvard Data Science Review podcast aims to show 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
Xiao-Li Meng, Co-host | Liberty Vittert, Co-host
Tina Tobey Mack, Producer
Rebecca McLeod, Executive Producer
Episode 18: Differential Privacy for the 2020 U.S. Census: Can We make Data Both Private and Useful? Part 1 (July 29, 2022)
While most Americans have heard of the U.S. Census and understand that it is designed to count every resident in the United States every 10 years, many may not realize that the Census’s role goes far beyond the allocation of seats in Congress. For this episode, we invited the three co-editors of Harvard Data Science Review’s special issue on the U.S. Census to help us explore what the Census is, what it’s used for, and how the data it collects should remain both private and useful.
Our guests are:
Erica Groshen, former Commissioner of Labor Statistics and Head of the U.S. Bureau of Labor Statistics
Ruobin Gong, Assistant Professor of Statistics at Rutgers University
Salil Vadhan, Professor of Computer Science and Applied Mathematics at Harvard University
Episode 17: Public Opinions on Immigrants and Refugees: Does the Data Inform or Misinform Us? (June 29, 2022)
In this episode we dive into the data on refugees and immigration. American public opinion seems very divided on these issues, but is it really? Is the U.S. more or less welcoming to refugees and immigrants than other parts of the world? How has disinformation influenced politics? Will the U.S. Southern Border, Ukraine, and other potential refugee crises affect the upcoming political elections in the U.S.? We bring in two experts to help discuss:
Scott Tranter, Senior Vice President, Data Science and Engineering at Dynata and Co-Founder of Øptimus Analytics, which was acquired by Dynata in 2021. He is also an investor in Decision Desk HQ, which provides election results data to news outlets, political campaigns, and businesses.
Episode 16: Is It a Good Idea to Legalize Marijuana? What Can Data Tell Us? (May 25, 2022)
In this episode we discuss the hotly debated topic of marijuana legalization. While 18 states have legalized recreational marijuana and the United States House of Representatives just passed a landmark marijuana legalization bill, cannabis is still an illegal substance under federal law in the United States. With the help of two experts, we dive into the data behind the arguments for and against the legalization of marijauna.
Our guests are Dr. Silvia Martins, MD, PhD, Director of the Substance Use Epidemiology Unit, Department of Epidemiology at Columbia University and Lt. Diane Goldstein, Executive Director of Law Enforcement Action Partnership (LEAP) and law enforcement veteran having worked in investigations, crisis negotiation, and gang enforcement for 21 years.
Episode 15: Can or Should the Question, “Are We Alone?” be Answered by Data Alone? (April 22, 2022)
Does life exist elsewhere in the universe? It's a question as old as time. On this month’s episode of the HDSR podcast we find out everything there is to know about life beyond earth by talking to the foremost experts who seek data and evidence to investigate the question, “Are we alone?”
Our guests are Abraham (Avi) Loeb, the Frank B. Baird, Jr., Professor of Science at Harvard University, Director of the Galileo Project and the Black Hole Initiative at Harvard University, and the bestselling author of Extraterrestrial: The First Sign of Intelligent Life Beyond Earth and Life in the Cosmos and Nick Pope, former civilian employee of the UK Ministry of Defense where his duties included investigating UFO sightings to assess the defense implications. Currently he works as a freelance journalist and broadcaster, specializing in UFOs, the unexplained, and conspiracy theories.
Episode 14: Recommender Systems: “People who listened to this episode also listened to . . . ” (March 25, 2022)
Recommender systems have become omnipresent in our everyday lives exemplified by Netflix telling us what movies to watch, to Amazon suggesting which books we should read, to Instacart promoting specific brands we must buy. We are constantly being influenced and seduced by these algorithms and the humans who designed them. On this month’s HDSR podcast we examine the pros and cons of recommender systems as well as the art, passion, and creativity that can be lost when we rely too heavily on them.
Our expert guests are Dr. Pearl Pu, the leading data scientist on recommender systems and a senior scientist at the Faculty of Information and Communication Sciences at EPFL in Lausanne, Switzerland, and film-maker Brandt Andersen whose most recent film, Refugee about a Syrian doctor’s escape from her war torn country, was short-listed for an Academy Award for Best Live Action Short in 2020.
Episode 13: Dating App or Matchmaker: Will You Swipe Right? (February 14, 2022)
Love is the topic of this Valentine’s Day episode of the HDSR Podcast. How do you find it and how do you make it last? Dating apps are a commonplace way for couples to meet and relationships to form, but do they help to make real love connections? With the help of two experts, we dive into the world of dating apps and discover how they can help and hinder your search for love. We also explore matchmaking services and discuss how working with a professional matchmaker might be more effective in finding true love than any dating app algorithm.
Our guests are Liesel Sharabi, Assistant Professor in the Hugh Downs School of Human Communication, Director of the Relationships & Technology Lab at Arizona State University, and author of the HDSR article, Finding Love on a First Data: Matching Algorithms in Online Dating; and Talia Goldstein, President and Founder of Three Day Rule Matchmaking, an exclusive matchmaking company for busy professionals.
Episode 12: Data Science for Criminal Justice: Can We Avoid Black Box Algorithms for High-Stake Decisions? (January 25, 2022)
In this episode we examine the use of secret or black box algorithms for high-stake decisions, particularly in the criminal justice system. How do they factor in the decisions made every day by state and federal courts concerning bail, sentencing and parole? Are black box algorithms fair and unbiased? Do they help counteract or support societal prejudices? Is their use in criminal justice cases serving the public’s best interest?
We discuss these issues and more with two leading experts on the topic: Cynthia Rudin, Professor of Computer Science, Electrical and Computer Engineering, Statistical Science, Mathematics, and Biostatistics & Bioinformatics, Director of the Interpretable Machine Learning Lab at Duke University and author of The Age of Secrecy and Unfairness in Recidivism Prediction for HDSR and Brandon Garrett, Professor of Law, Founder of the Wilson Center for Science and Justice at Duke University and author of Justice in Forensic Algorithms for HDSR.
Episode 11: Can Data Science Help the Wine Industry (and me, to pick up a good bottle)? (December 16, 2021)
‘Tis the season to be merry and bright, and doesn’t a glass of wine go a long way to help ring in the festivities? We think so because this month's episode of the HDSR Podcast is devoted to the wine industry – from production to consumption. We discuss the impact of COVID on the global supply chain, the idiosyncrasies of local government regulations, the effects climate change is having on traditional and emerging grape growing regions, how winemakers use data analysis, and most important, what are the key data points that every potential wine connoisseur should know in order to impress their families and friends at holiday gatherings this season.
Our guests are Orley Ashenfelter, the Joseph Douglas Green 1895 Professor of Economics at Princeton University and President of the American Association of Wine Economists and Don St Pierre, the Executive Chairman of Vinfolio, the U.S.’s leading fine wine marketplace, investment advisor, and professional wine storage facility.
Episode 10: Government Data: How Do They Serve Us but Also Concern Us (November 19, 2021)
On this month’s episode we examine how the U.S. government collects data to serve the public and how to ensure such a process does not hurt the people it aims to serve. We discuss the good, the bad, and the ugly sides of this topic including privacy issues, the 2020 U.S. Census, how well-intended methods may adversely affect minority populations, and why it’s important for local communities to collect and report their own data. We also ask how transparent should the federal government be about its data collection and who should the public be most worried about when it comes to data privacy?
Our guests are Tim Persons, Chief Scientist for the U.S. Government Accountability Office (GAO) and Managing Director of its Science, Technology Assessment, and Analytics team and Julia Lane, New York University professor and co-founder of the Coleridge Initiative, a not-for-profit organization that is working with governments to ensure that data are more effectively used for public decision-making. Julia is also the author of numerous books including Democratizing our Data: A Manifesto by the MIT Press.
Episode 9: Pollsters: The Discoverers and Guardians of Public Opinion (October 20, 2021)
This month’s episode focuses on the art and science of measuring public opinion. We discuss the challenges pollsters face when trying to predict how public opinion may change over time, review both the innovative and time-tested methods of polling and discover which recent polls have revealed the most surprising data.
Our guests are Kristen Soltis Anderson, pollster, speaker, commentator, author and co-founder of Echelon Insights, an opinion research and analytics firm; and Cliff Young, President of US Public Affairs at Ipsos, Adjunct Lecturer at Johns Hopkins University and a frequent writer, analyst, and commentator on elections, electoral polling, and public opinion.
Episode 8: The Future of Artificial Intelligence: Will it be the Terminator or the Jetsons? (September 16, 2021)
On this episode we explore all things AI with our guests Kathleen Walch and Ron Schmelzer, hosts of the popular AI Today podcast and principal analysts and managing partners of Cognilytica, an AI research and advisory firm.
With Kathleen and Ron, we discuss the spread of AI in our lives, from autonomous vehicles to Taco Bell’s new automatic drive thru lanes. But has too much been promised and not delivered? Are we on the brink of an AI winter, where development and investment cool down? We look at all the possibilities of how our future will change with AI.
Our hosts Xiao-Li and Liberty were also guests on the AI Today podcast. If you’d like to hear that interview, you can listen here: https://www.cognilytica.com/2021/09/16/ai-today-podcast-interview-with-harvard-data-science-review-hdsr-podcast-hosts-liberty-vittert-xiao-li-meng/
Episode 7: Healthcare Data: Who Takes Care of it and How Healthy is it? (August 20, 2021)
Over 30% of the world’s data is comprised of healthcare data with the U.S. government arguably collecting the largest portion. On this month’s episode of the Harvard Data Science Review Podcast, we explore all things healthcare data with the help of two experts who provide their perspectives from the public and private sectors.
Our guests are Justin Fanelli, Chief Architect of Defense Medical Intelligence Data and the Technical Director at the Naval Information Warfare Center and Michelle Holko, Principal Architect Public Sector Cloud for Healthcare and Life Sciences at Google.
Episode 6: Mental Health Challenges: How Can Data Science Help? (July 16, 2021)
This month’s episode focuses on the increasing role of data science in the diagnosis and treatment of mental health disorders. It explores how statistical tools like adaptive testing are being successfully deployed to rapidly identify people with high levels of depression, anxiety or suicide risk. It also examines how the data science community could further improve its efforts to support mental health research and policymaking. Our guests are Margarita Alegria, Chief of the Disparities Research Unit, Massachusetts General Hospital and Professor, Harvard Medical School and Robert Gibbons, Professor of Biostatistics, Departments of Medicine, Public Health and Psychiatry, University of Chicago .
See also Robert Gibbons’ related article in HDSR: Medications and Suicide: High Dimensional Empirical Bayes Screening (iDEAS)
Episode 5: Are you Disinformed or Misinformed?
(June 17, 2021)
On this episode, we dig into the world of disinformation and misinformation and the difference between them. Is the weaponization of both a new phenomenon or is history repeating itself? How has social media and the democratized access to published information contributed to today’s sensationalized headlines? Hosts Xiao-Li Meng and Liberty Vittert explore these questions and more with the help of guests Scott Tranter, CEO and founder of Optimus Analytics and Hany Farid, Professor at the University of California, Berkeley with a joint appointment in Electrical Engineering & Computer Science and the School of Information.
Episode 4. The Art and Value of Machine Learning in Valuing Art: Hype or Hope? (May 20, 2021)
What is the value of art? Is it in the eye of the beholder or can data analytics tools place a monetary value on beauty? Hosts Xiao-Li Meng and Liberty Vittert explore the use of data and technology in the art world with guests Jason Bailey, CEO and founder of Artnome and Dan Cameron, renowned American art curator, writer, and educator.
See also Jason Bailey’s related article in HDSR: “Can Machine Learning Predict the Price of Art at Auction?”
Episode 3. Predicting (2021) Oscar Winners: How Crystal is the Statistical Ball? (April 15, 2021)
What are the biggest predictors of an Oscar win? What are the pros and cons of using quantitative vs. qualitative data? Has the film industry’s increased use of streaming services impacted Oscar predictions? Hosts Xiao-Li Meng and Liberty Vittert investigate these questions and more by speaking with two renowned Oscar awards predictors: Boston Globe film critic and columnist Ty Burr and Ben Zauzmer, author of Oscarmetrics: The Math Behind the Biggest Night in Hollywood.
See also Ben Zauzmer’s related article in HDSR: "Oscar Seasons: The Intersection of Data and the Academy Awards."
Episode 2. Tracking the (Money) Balls: How Data Science is Becoming a Game Changer (March 19, 2021)
Data science is huge in sports, and it's not just game stats anymore. Player and ball tracking data are changing the way major sports leagues play games. We dive into how these data are analyzed and what the results mean to coaches and teams with Kirk Goldsberry, NBA analyst at ESPN and author of “Sprawlball,” and Brian Macdonald, Faculty in Sports Analytics at Carnegie Mellon University.
See also Brian Macdonald’s related article in HDSR: “Recreating the Game: Using Player tracking Data to Analyze Dynamics in Basketball and Football”
Episode 1. The Data of Love (February 12, 2021)
Xiao-Li and Liberty speak with relationship experts Drs. Julie and John Gottman from the Love Lab. Listen to find out how to insure your relationship lasts the test of time.