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 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.