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In this podcast episode (recorded on 3/23/22) we spoke with Maxim Lott – the mind behind the Maximum Truth Substack and ElectionBettingOdds.com – to discuss the current military, political, and economic situation in Russia as it pertains to the Russo-Ukrainian crisis. As a former journalist for organizations like ABC and Fox, Maxim has deep experience operating within  mainstream media companies. And as a result of his time working for those institutions, he has focused his career on providing alternatives to mainstream media narratives, including the current war in Ukraine. Maxim has been covering (and forecasting) the war in Ukraine throughout March, providing nuanced perspectives on the crisis. From casting doubt on the severity of the current sanctions regime impacting the Russian economy, to sharing sentiment polls from Russian citizens, Maxim consistently provides interesting vantage points on this conflict. Maxim also spent time in Eastern Europe before our conversation, and talks about his experience in the region and how that has impacted his analysis.

In this podcast episode, we sat down with Tom Chivers—author, journalist, and science writer for The i—to have a conversation on forecasting and the news media. We talked about his background in the media industry, his frustrations with mainstream news and its lack of nuance, his views on forecasting and prediction markets in media, and more. Tom previously wrote for BuzzFeed UK, served as the science editor for UnHerd, and has bylines with New York Times, Guardian, New Scientist, and The Telegraph. He often writes data-driven rebuttals to topics that are being primarily depicted in one way in the media, interjecting nuance into the conversations. In many ways, the same exercise as distinguishing signals from noise. Conducting journalism with a forecaster’s mindset. He's also written two books, The AI Does Not Hate You in 2019 and How to Read Numbers in 2021, and writes about similar topics discussed in our communities, including effective altruism, rationality, and forecasting. To our knowledge, Tom is one of the most prominent journalists writing about and covering quantified forecasts. In June of last year, Tom assembled a panel of superforecasters for an article on whether China will invade Taiwan and has started to make his own predictions too! You can follow Tom on Twitter: @TomChivers.

And we’re back! In this year’s first podcast, we are speaking with Tina Fordham, Partner & Head of Global Political Strategy at Avonhurst, a London-based advisory business. Tina is one of the most veteran players in the political risk industry, beginning her career at Eurasia Group where she launched Eurasia Group's financial markets business, including leading the Lehman Brothers-Eurasia Group index—the first political risk index on Wall Street. While there she also led the roll-out of Eurasia Group's European business. Since then, Tina’s career has included roles as Managing Director, Chief Global Political Analyst at Citigroup (the first position of its kind on Wall Street), as well as Member of the High-Level Panel for Women's Economic Empowerment—the first-ever UN High-Level Panel dedicated to promoting Women's Economic Empowerment. She also created her own framework for processing political risk, Vox Populi, which was born in the post-Arab Spring era that we will talk about in-depth. Today we will discuss Tina’s impressive career, her risk framework, and some specific forecasts she has made in her many roles as well as her thoughts on quantified forecasting and much more. We are very excited about this interview, and we think you will enjoy this one!

When the Suez Canal got blocked by the Ever Given shipping vessel a global trade crisis began, costing the global economy $10 billion a day. Knowing when this crisis would end had immense valuable, but predicting the clearing was easier said than done—as our own forecast showed. One person who got it done was Peter Wildeford, a top-100 forecaster on Metaculus and Forecast App, and the co-CEO of the think tank Rethink Priorities. Peter’s forecast was more accurate than most, letting him turn his foresight into triple-digit returns. In the inaugural episode of The Right Side of Maybe—a new podcast where we learn from and about elite forecasters—we talked to Peter about the method behind his Ever Given forecast and the ways in which he leveraged it for profit on Polymarket. We also talked to Peter about his background in forecasting and recent experience with prediction markets, as well as some of the most important areas of psychology and science where Peter thinks forecasters can improve. Find Peter Wildeford : https://twitter.com/peterwildeford Rethink Priorities: https://www.rethinkpriorities.org/ Global Guessing: https://globalguessing.com/#/portal/signup

How should we understand the Omicron relative to Delta? How does Omicron change the nature of the pandemic and what steps should we be taking in response? These questions require navigating and quantifying uncertainty, while also making forecasts about the future. We could think of no one better than Juan Cambeiro for answers. Juan Cambeiro is a Global Guessing alum, Good Judgment superforecaster, and Metaculus analyst, who placed first in IARPA's FOCUS Tournament on COVID-19 forecasting and was the former first-place COVID forecaster on Good Judgment Open. Juan recently wrote a fantastic article on Metaculus about the Omicron variant–providing a concise analysis of the variant from an epidemiological and public health perspective, while also offering five concrete forecasts about it. In this podcast, we'll talk to Juan about how he analyzed and understood the variant, chose and forecasted these five questions, and key signals he’s identified and looking out for in the future. We'll also chat about how policymakers and others should respond to the variant and understand the information from these forecasts. At the end, we'll discuss additional forecasting questions we should be asking to better understand the variant's impact on the pandemic. Learn more: https://globalguessing.com/forecasting-omicron-juan-cambeiro/ Note: This podcast was recorded on December 6, 2021. 

It's hard to imagine, but 51 weeks ago we launched Global Guessing with our inaugural forecast on the 2020 Burkina Faso Presidential Election. In the time since, we've released 43 podcast episodes, 34 forecasts, and a new newsletter. In today's final (??) episode of the Weekly Podcast, we wanted to go over this incredible past year–discussing why we started this project, recount the content we've produced, highlight our favorite moments, and discuss how our thoughts about quantified forecasting and the content we produced evolved since that Burkinabe forecast. While this may be the final GGWP for a while, we're not going anywhere! At the end of this episode, we'll share with you our exciting plans for 2022 and beyond with respect to forecasts and podcasts. Thank you so much for being with us for the last year and the support you have shown. We hope you enjoy the show!

Do consumers of geopolitical risk reports want accurate forecasts? You would think surely yes, but recurring listeners of our podcast know that in many cases individuals prefer vague verbiage over accountable, quantifiable forecasts. In this week's Global Guessing Weekly Podcast we wanted an answer, so we spoke with Manas Chawla, founder and CEO of London Politica–a student-run pro-bono political risk organization based out of London. Manas founded London Politica in 2020 during the pandemic when he noticed an accessibility problem in the geopolitical risk industry. Today, the geopolitical industry resembles an oligopoly: there is a small handful of large firms that retain the largest clients and drive trends. The issue is that the fees which these firms charge are often too lofty for the massive pool of SMBs and independent business owners around the world. And that’s where London Politica comes in. Run by students who provide new and innovative perspectives on the world of geopolitics, London Politica provides geopolitical risk services and thought leadership at affordable prices to a diverse world of clients. Today Manas will walk us through how he founded his firm which boasts 70 analysts in 20 countries with backgrounds from the likes of Goldman Sachs, Credit Suisse, and clients such as Global Citizen. And to make this all more impressive, Manas is currently a student at the London School of Economics where he is studying International Relations. We'll also talk with Manas about the role geopolitical forecasts play in geopolitical risk, and how the future of the two might look. Note: This podcast was recorded on August 31, 2021.

Welcome back to the Global Guessing Weekly Podcast. This week we are joined by David McCullough, Managing Director of Government Operations and Superforecaster and Good Judgement Inc. Prior to joining Good Judgement, David was an underwater Archaeologist for over twenty years after receiving his Ph.D. in Maritime Archeology from the University of Glasgow. In this week's episode, we talked to David about his background in Archaeology and the ways in which his training helped him become an elite forecaster. Afterwards, we discussed the importance of creating good forecasting questions and the qualities associated with them. We also chatted with David the importance of pre-mortem analysis and the roadblocks hindering government and private-sector adoption of forecasting and the principles outlined in Tetlock and Gardner's Superforecasting. We really enjoyed speaking with David, finding his answers thoughtful and insightful. If you did as well, make sure to check out Good Judgement's upcoming Superforecasting Workshop on December 8th and 9th at 12:00 - 2:30pm EST.

And we're back! Welcome everyone to the eighteenth episode of the Global Guessing Weekly Podcast, the podcast on all things geopolitics and forecasting. Today we are joined by GG alum David Manheim, lead researcher for the human challenge trial advocacy group 1DaySooner who previously appeared on The Right Side of Maybe to discuss his accuracy in forecasting Covid vaccines. David received a PhD in Public Policy from Pardee Rand Graduate School focusing on risk analysis and decision theory. He has done work on a variety of grants and contracts to research existential risk mitigation, public health, computational modelling, and infectious disease epidemiology for organizations such as the RAND Corporation. In addition to his work with 1DaySooner, David currently works with the Foresight Institute, is a Superforecaster with Good Judgement Inc., and recently became a visiting professor at the Israel Institute of Technology "working to build interdisciplinary collaborations with technical researchers on the promises and risks of emerging technologies." In this episode, you'll hear David talk about his work in biosecurity including the recent report he worked on for the Council on Strategic Risks, a US think tank, and his work with 1DaySooner on human challenge trials to learn how this change in vaccine testing could save millions of lives. We also chatted with David about the role that quantified forecasting currently plays in government policy and discuss why the technique is under-utilized. Finally, we get David’s thoughts on real-money prediction markets and the importance of question-quality in both prediction markets and platforms. Note: This episode was recorded on July 29th.

Career paths rarely unfold linearly, and this week's guest is no exception. But his winding way in geopolitics (as he discusses) provided him with exceptional perspective which has surely informed his geopolitical chops. In this week's episode we sat down with John Fowler of International Intrigue, a newsletter covering all things geopolitics and global affairs. We talked about his circuitous route to International Intrigue, including stops to study law, join the Australian foreign service, and earn an MBA. We also chatted about some of his most memorable International Intrigue editions as well as exploring the many linkages between the worlds of geopolitics and forecasting. Be sure to listen or watch this episode for some interesting conversation, and to discover another great content hub to consume. International Intrigue: https://www.internationalintrigue.io/ John Fowler: https://twitter.com/johnsnonsense Global Guessing: https://globalguessing.com/ ​​​Twitter: https://twitter.com/GlobalGuessing Facebook: https://facebook.com/globalguessing​​​ LinkedIn: https://www.linkedin.com/company/global-guessing/

Since beginning Global Guessing, we have noted that interdisciplinary approaches to forecasting have often borne positive results. Whether guests have come from the world of finance, academics, or biology, their ‘outside views’ have frequently contributed to their forecasting accuracy. And our guest this week, Juan Cambeiro, is no different. In this episode 6 of The Right Side of Maybe, Clay and Andrew sat down with student, biostatistics student, and Metaculus summer analyst Juan Cambeiro to discuss his background in forecasting and work with Metaculus Pandemic. Juan placed first in Good Judgement Open's 2020 Coronavirus Outbreak forecasting challenge, and is currently in second place overall. After discussing Juan's background in forecasting, we dove deep into three recent forecasts he made covering Mortgage Interest Rates, US COVID Deaths, and the Tokyo Summer Olympics. Two of the questions Juan got to the right side of maybe, while the third he ended up on the wrong side. We not only discussed what went well with his correct forecasts, but also explored potential sources of error with the third. We also spoke with Juan about his information diet, how he goes about finding new sources, and the importance of forecasting for the world! Be sure to tune into this episode as you will learn a lot about good forecasting habits and how to perform well in tournaments.

Every forecaster has wanted to know what the most important factor for improving forecasting accuracy is, but for a long time the answer was not clear. Thanks to a chance overlap of co-authors Ville Satopää and Marat Salikhov at INSEAD, however, a new paper was published alongside forecasting pioneers Philip Tetlock and Barbara Mellers that does a great job of providing a solution. Their paper, “Bias, Information, Noise: The BIN Model of Forecasting,” deconstructs the forecasting process into its component parts of: Information (the inputs you use to move your forecast away from the base rate), Bias (systematic error across a number of forecasts from a single forecaster), and Noise (non-information that is registered as information in a forecast). From there they test which of these parts is most critical to the accuracy of a forecast, and posit methods to improve in these areas. In this episode we are lucky enough to sit down with Ville and Marat to discuss the origins of this paper, its findings, and the implications for the future of forecasting. We talk about possible avenues for further research based on the exciting results from Ville and Marat’s research, and even speculate on potential applications of the research in new and interesting environments.