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Behind the Data
Behind every dataset is a story — and a new way of seeing the world
Behind the Data is a podcast about the hidden stories tucked inside the data that shapes our world. From political polls to global happiness indexes, we go beyond charts and headlines to uncover where data comes from, wh
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14. Searching for life in the Milky Way
43:41||Season 2, Ep. 14Is there life in our galaxy? How would we know if we spotted it? Dr. Moiya McTier, astrophysicist and folklorist, joins us to talk about her Ph.D. research on exactly that, plus the many surprising ways we get data about our universe (plus some existential pondering, of course)! Warning: we will be talking about the vastness of space and it's *no joke*!If you're overwhelmed by the universe but want to be its friend, be sure to check out Moiya's fantastic podcast Pale Blue Pod! I'm also a guest on an episode this week hooray :).Follow Moiya!@GoAstroMo on all the things!Moiyamctier.comHer book is The Milky Way: An Autobiography of Our GalaxyHer podcast rules: https://palebluepod.com/Links & references in the episode:Foundational archao-astronomer Owen GingerichCultural astronomer Jarita HolbrookLIGO chirp sounds & informationNASA datasetsNASA's exoplanet archiveOur music is from Music Radio Creative and we are proudly part of the Daily Tech News Show ecosystem! Find me at @jonesrooy and jonesrooy.com.Chapters00:00 Exploring Life in the Milky Way04:09 Astrophysics vs. Astronomy: Understanding the Differences10:30 Data Collection in Astrophysics16:42 The Breakthrough of Gravitational Waves21:13 The Sound of Space: Gravitational Waves and Data Representation22:19 Multi-Messenger Astronomy: A New Era of Discovery24:48 The Cosmic Gold Rush: Understanding Element Formation26:21 Data Overload: The Stress of Astronomical Discoveries28:50 Big Data in Astronomy: The Challenge of Analysis31:12 AI in Astronomy: The Future of Data Processing33:33 Bias in Data: The Challenges of Observational Astronomy36:14 Null Results: The Importance of Scientific Rigor38:37 The Search for Life: Habitable Zones in the Milky Way40:54 Existential Reflections: Finding Meaning in the Vastness of Space42:05 Exploring Space Data: Resources for the CuriousKeywordsMilky Way, life, astrophysics, astronomy, gravitational waves, data collection, science communication, cultural astronomy, world building, aliens, gravitational waves, multi-messenger astronomy, data analysis, AI in astronomy, bias in data, habitable zones, cosmic discoveries, Milky Way, space exploration, scientific rigor
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13. Creating a bot based on a real person
47:42||Season 2, Ep. 13Vasant Dhar has been working on AI since way before it was cool (and before most people thought it was possible). I've admired his work for a long time and since I started this show have wanted to have him on as a guest to talk about the strengths and limitations of LLMs. A few days ago, he published an article in The Hill about how DOGE is using AI wrong, and I knew I had to talk to him immediately.We discuss, indeed, what DOGE is doing wrong, as well as the broader lessons we all can learn from this example about what makes a good vs. not-so-good use case for LLMs. We also talk about his recent and completely earth-shattering Severance-esque research where he and a colleague create a bot with the goal of simulating the valuation reasoning of investing legend Aswath Damodaran. Naturally, throughout the conversation, I pepper him with questions about how scared or optimistic we should be about all of this, as well as how AI can somehow be both incredible and limited at the same time.Follow Vasant!Vasant's (excellent!) Brave New World podcast: http://bravenewpodcast.com/Vasant's substack: https://vasantdhar.substack.com/Vasant's article: "DOGE is using AI the wrong way."Vasant's recent paper: "DBOT: Artificial intelligence for systematic long-term investing"I'm @jonesrooy on Instagram and at jonesrooy.com.And, because I'm trying to make friends with AI, below is a chapter summary! Woo hoo.Chapters00:00 The Evolution of AI: A Personal Journey01:49 Understanding LLMs: Are They Thinking?04:35 The Fear of AI: Balancing Optimism and Caution06:57 Explaining LLMs to Newcomers09:37 Learning and The Integration of the Senses12:24 DOGE's Approach to AI in Government15:22 The Need for Better AI Implementation in Government17:47 Could This Actually Work?20:16 A Problem with Using AI on Data from Humans21:47 Contextualizing Project Failures22:33 Applying AI to Investing23:45 Building an AI Investor27:36 The Science of Long-Term Investing28:40 Simulating Expertise: The Damodaran Bot32:33 The Art of Questioning in AI36:07 Expectations and Realities of AI Development40:10 Be the AI Change You Wish to See in the World12. The power of turning political attitudes into numbers
30:36||Season 2, Ep. 12We take it as a given that Americans are politically polarized, but how do we actually know if empirically this is the case? We talk with Prof. Patrick Egan (NYU) about how we can quantify something as abstract as a political attitude, why doing so helps us understand polarization, and how all of this helps reveal opportunities where we can make progress on areas where we're most divided -- such as climate change.Explore Pat's research and writing: https://wp.nyu.edu/egan/.Papers and resources mentioned in the episode:An example of Pat's work on issue ownership is here.The data Pat mentioned on Americans' political attitudes since 1948 is from the American National Election Studies (ANES), which you can explore for free here.An example of measuring leaders' ideologies based on their roll call votes is here.An example of measuring ideology based on campaign contributions is here.Learn more about Hanna Pitkin's concept of representation in her 1972 book The Concept of Representation (helpful summary here).Pat's 2024 climate change paper (with Megan Mullin) is US partisan polarization on climate change: Can stalemate give way to opportunity? (appeared in PS: Political Science and Politics 57(1): pp. 30-35).BTW: the adage that states that headlines that pose a question tend to have the answer "no" is Betteridge's law of headlines and it's very fun.Follow Andrea at @jonesrooy on Instagram and/or learn more at jonesrooy.com. Be sure to check out our partner show The Daily Tech News Show!11. Building a data warehouse to help find a cure for ALS
46:36||Season 2, Ep. 11ALS is a fatal motor neuron disease that has no cure and is estimated to affect hundreds of thousands of people worldwide. Why is a cure, or even a meaningful treatment, so elusive? We talk with data engineer, scientist, and rare disease advocate Danielle Boyce at ALS TDI about her work helping us all better understand this terrible illness. While the topic is grim, Danielle provides a lot of hope -- as well as inspiration to all of us to get involved in solving problems through data.Follow Danielle and her amazing data & statistics tips on LinkedIn: https://www.linkedin.com/in/data-danielle/.Find out more about ALS Therapy Development Institute (ALS TDI): https://www.als.net/ (and donate if you like!).Two other resources Danielle mentioned to get involved: https://ohdsi.org/ and https://www.geoals.org/.Follow Brooke Eby on the various social medias: @limpbroozkit.Check out my father Robert Rooy's film about our friend John Godinet: https://www.lovingjohnmovie.com/ and watch the trailer here!Follow me at @jonesrooy and https://www.jonesrooy.com/. Behind the Data is proud to be part of the Daily Tech News Show ecosystem. Special thanks to Tom Merritt and our producer Roger Chang!10. Spying on Elon Musk and Tesla from space
42:21||Season 2, Ep. 10Oceans of numbers come pouring out at us each day about the big tech companies -- whether it's spending on AI, iPhone sales, Tesla stocks ... or, lawsuits against SpaceX by Cards Against Humanity? -- senior tech correspondent Rani Molla is on the case. We talk with her about how to make sense of all the numbers coming our way, the power of zooming out and getting the (literal and figurative!) big picture, and why her comparative literature degree has been a surprisingly huge asset in her numbers-centric work. Also, we find out about what the heck Elon is up to (at least with respect to some of his goings-on!).Rani's articles that use satellite images:"Before and after: Aerial photos show what being Elon Musk's neighbor can do to your land," Sherwood News"Tesla's massive pileup: Tesla's unsold inventory is creating stockpiles you can see from space," Sherwood NewsResources mentioned:Tesla's Form 10-K for 2024Flourish data visualization platformRead more of Rani's great work on Sherwood News here and follow her on Bluesky here!Read more about Andrea here and on Instagram. And check out our partner show, the Daily Tech News Show!9. Just how much misinformation is out there?
51:31||Season 2, Ep. 9We all have ideas about how social media and misinformation are affecting us and our world. But, as our guest Prof. Joshua Tucker explains, received wisdom is not the same thing as scientific findings. Join us for a tour de force through how to break down "social media" and "misinformation" into researchable parts that can be theoretically and quantitatively studied -- as well as some seriously surprising findings about both.Fun fact: This episode was originally going to come later in the season, but the topic is so important we decided to release it sooner.Follow Josh and the NYU Center for Social Media and Politics at csmapnyu.org.Josh references a lot of great research. Here are links to all the papers, reports, and books he mentions -- presented in the order of appearance!Tucker et al. 2018. "Social Media, Political Polarization, and Political Disinformation: A Review of the Scientific Literature." Hewlett Foundation.Persily & Tucker, ed. 2020. Social Media and Democracy. Cambridge University Press.Diamond & Plattner, ed. 2012. Liberation Technology. Hopkins Press.Persily, Nathan. 2017. "Can Democracy Survive the Internet?" Journal of Democracy.Tucker et al. 2017. "From Liberation to Turmoil." Journal of Democracy.Guess, Nagler, & Tucker. 2019. "Less Than You Think: Prevalence and Predictors of Fake News Dissemination on Facebook." Science Advances.Aslett et al. 2024. "Online Searches to Evaluate Misinformation Can Increase Its Perceived Veracity." Nature.Allen et al. 2020. "Evaluating the Fake News Problem at the Scale of the Information Ecosystem." Science Advances.Sanderson, Messing, & Tucker. 2024. "Misunderstood Mechanics: How AI, TikTok, and the Liar's Dividend Might Affect the 2024 Elections." Brookings.Allen, Watts, & Rand. 2024. "Quantifying the Impact of Misinformation and Vaccine-Skeptical Content on Facebook." Science.You can find AJR at jonesrooy.com and @jonesrooy on IG.Season 2 trailer
00:58||Season 2, Ep. 0Welcome to Season 2 of Behind the Data! We're going to explore brand new topics through the powerful lens of data, find common ground on some issues that are really dividing us, and even gaze into the night sky and the deep seas -- join us for an adventure, and then some, and walk away with a brand new way of looking at the world through the shared language of data. This season you can expect episodes on misinformation, political attitudes, happiness, ALS, tech, and more.Behind the Data is hosted by Andrea Jones-Rooy, Roger Chang is our producer, and we are proudly part of the Daily Tech News Show network!