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In Episode 85, Patrick and Ciprian speak with returning guest Steven Girvin of Yale University. The team discusses error correction, Rydberg states, erasure errors, and dual rail encoding.Dr. Steve GirvinAfter graduating in a high school class of 5 students in the small village of Brant Lake, NY and completing his undergraduate degree in physics from Bates College, Dr. Girvin earned his Ph.D. in theoretical physics from Princeton University in 1977. Dr. Girvin joined the Yale faculty in 2001, where he is Eugene Higgins Professor of Physics and Professor of Applied Physics. From 2007 to 2017 he served as Yale's Deputy Provost for Research, overseeing strategic planning for research across Yale. From 2019 to 2021, he served as founding director of the Co-Design Center for Quantum Advantage, one of five national quantum information science research centers funded by the Department of Energy. Along with his experimenter colleagues Michel Devoret and Robert Schoelkopf, Professor Girvin co-developed ‘circuit QED,' the leading architecture for construction of quantum computers based on superconducting microwave circuits. Dr. Girvin is a Foreign Member of the Royal Swedish Academy of Sciences and Member of the US National Academy of Sciences. In 2007, he and his collaborators, Allan H. MacDonald and James P. Eisenstein were awarded the Oliver E. Buckley Prize of the American Physical Society for their work on the fractional quantum Hall effect. In 2019, he and coauthor Kun Yang published the textbook “Modern Condensed Matter Physics” with Cambridge University Press.
In this episode of Choiceology with Katy Milkman, we look at how framing a decision based on what you stand to lose versus what you stand to gain affects your tolerance of risk.Luis Green was a contestant on the popular TV game show Deal or No Deal. The game is largely one of chance, but there are moments during play where the contestant has an option to accept a cash offer to quit. At one point in the game, Luis was offered $333,000 to simply walk away. A guaranteed win! It seems like an obvious choice. But as you'll hear from the story, there are other factors that influenced his decision.Katy illustrates these factors with a version of a famous experiment. Volunteers are presented with two differently worded but mathematically identical scenarios. A simple shift from framing the scenario as a potential gain to one of potential loss results in starkly different choices from the volunteers.Next, Katy speaks with special guest Daniel Kahneman about the underlying theory that explains human behavior in these types of situations. Daniel Kahneman served as professor of psychology and public affairs emeritus at the Woodrow Wilson School and the Eugene Higgins Professor of Psychology Emeritus at Princeton University. He was awarded the 2002 Nobel Prize in Economics for his pioneering research with Amos Tversky. Their work helped establish the field of behavioral economics. Kahneman also wrote the bestselling book Thinking, Fast and Slow.Finally, Katy speaks with Colin Camerer about some of his favorite studies on risk seeking in the domain of losses, as well as practical approaches for avoiding this less-than-ideal behavior. Colin Camerer is the Robert Kirby Professor of Behavioral Finance and Economics at the California Institute of Technology, where he teaches cognitive psychology and economics. You can read his paper “Prospect Theory in the Wild: Evidence from the Field” here.Choiceology is an original podcast from Charles Schwab. If you enjoy the show, please leave a rating or review on Apple Podcasts.Important DisclosuresThe comments, views, and opinions expressed in the presentation are those of the speakers and do not necessarily represent the views of Charles Schwab.Data contained herein from third party providers is obtained from what are considered reliable source. However, its accuracy, completeness or reliability cannot be guaranteed and Charles Schwab & Co. expressly disclaims any liability, including incidental or consequential damages, arising from errors or omissions in this publication. All corporate names and market data shown above are for illustrative purposes only and are not a recommendation, offer to sell, or a solicitation of an offer to buy any security. Supporting documentation for any claims or statistical information is available upon request. Investing involves risk including loss of principal.The policy analysis provided by the Charles Schwab & Co., Inc., does not constitute and should not be interpreted as an endorsement of any political party.The book How to Change: The Science of Getting from Where You Are to Where You Want to Be is not affiliated with, sponsored by, or endorsed by Charles Schwab & Co., Inc. (CS&Co.). Charles Schwab & Co., Inc. (CS&Co.) has not reviewed the book and makes no representations about its content.(0424-VAX6)
Sheldon Lee Glashow (born December 5, 1932) is a Nobel Prize-winning American theoretical physicist. He is the Metcalf Professor of Mathematics and Physics at Boston University and Eugene Higgins Professor of Physics, emeritus, at Harvard University, and is a member of the board of sponsors for the Bulletin of the Atomic Scientists. In 1961, Glashow extended electroweak unification models due to Schwinger by including a short range neutral current, the Z0. The resulting symmetry structure that Glashow proposed, SU(2) × U(1), forms the basis of the accepted theory of the electroweak interactions. For this discovery, Glashow along with Steven Weinberg and Abdus Salam, was awarded the 1979 Nobel Prize in Physics. In collaboration with James Bjorken, Glashow was the first to predict a fourth quark, the charm quark, in 1964. This was at a time when 4 leptons had been discovered but only 3 quarks proposed. The development of their work in 1970, the GIM mechanism showed that the two quark pairs: (d.s), (u,c), would largely cancel out flavor changing neutral currents, which had been observed experimentally at far lower levels than theoretically predicted on the basis of 3 quarks only. The prediction of the charm quark also removed a technical disaster for any quantum field theory with unequal numbers of quarks and leptons — an anomaly — where classical field theory symmetries fail to carry over into the quantum theory. In 1973, Glashow and Howard Georgi proposed the first grand unified theory. They discovered how to fit the gauge forces in the standard model into an SU(5) group, and the quarks and leptons into two simple representations. Their theory qualitatively predicted the general pattern of coupling constant running, with plausible assumptions, it gave rough mass ratio values between third generation leptons and quarks, and it was the first indication that the law of Baryon number is inexact, that the proton is unstable. This work was the foundation for all future unifying work. Glashow shared the 1977 J. Robert Oppenheimer Memorial Prize with Feza Gürsey. Original video here Full Wikipedia entry here Sheldon Glashow's books here --- Support this podcast: https://podcasters.spotify.com/pod/show/theunadulteratedintellect/support
Sergiu Klainerman is the Eugene Higgins Professor of Mathematics at Princeton University. Born in communist Romania, he sees disturbing parallels between life in the Soviet Bloc and the "soft totalitarianism" or "pre-totalitarianism" taking root in America. He joins the show to discuss these parallels and reflect on Aleksandr Solzhenitsyn's 1978 speech, "A World Split Apart." Klainerman's essay "Reflections on Solzhenitsyn's Harvard Address" is here. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/politics-and-polemics
Sergiu Klainerman is the Eugene Higgins Professor of Mathematics at Princeton University. Born in communist Romania, he sees disturbing parallels between life in the Soviet Bloc and the "soft totalitarianism" or "pre-totalitarianism" taking root in America. He joins the show to discuss these parallels and reflect on Aleksandr Solzhenitsyn's 1978 speech, "A World Split Apart." Klainerman's essay "Reflections on Solzhenitsyn's Harvard Address" is here. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/russian-studies
Sergiu Klainerman is the Eugene Higgins Professor of Mathematics at Princeton University. Born in communist Romania, he sees disturbing parallels between life in the Soviet Bloc and the "soft totalitarianism" or "pre-totalitarianism" taking root in America. He joins the show to discuss these parallels and reflect on Aleksandr Solzhenitsyn's 1978 speech, "A World Split Apart." Klainerman's essay "Reflections on Solzhenitsyn's Harvard Address" is here. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/intellectual-history
The PiWi family of genes may have a diminutive sounding name, but they have a large role in the function of the germline and germline stem cells. Initially discovered in Drosophila, these highly conserved RNA-binding proteins have well-established roles in the regulation of spermatogenesis and germ stem cell maintenance, in addition to silencing transposable elements. However, PiWi function outside of the germline is relatively unexplored. New findings from the Lin laboratory show that Drosophila Piwi has a role in intestinal homeostasis where it functions to establish intestinal stem cells, maintain the enteroblast lineage, and support of the enterocytes. It also has a role in silencing retrotransposons of the gut. Collectively, these intestinal roles of PiWi are critical to organismal longevity as the loss of PiWi leads to a shortened lifespan in the fly. Martin Pera is joined by scientists Drs. Haifan Lin and Xiongzhuo Tang. Dr. Lin is the Eugene Higgins Professor of Cell Biology and the Founding Director of the Yale Stem Cell Center. Among his many achievements, Haifan is a member of US National Academy of Sciences, a member of American Academy of Arts and Sciences, and a Foreign Member of Chinese Academy of Sciences. He is currently the president of the ISSCR. Xiongzhuo Tang was a postdoctoral fellow in the Lin laboratory and is now a professor in the Animal and Nutritional Genome and Germplasm Innovation Research Center in the College of Animal Science and Technology at the Hunan Agricultural University in Hunan China.Drs. Lin and Tang are authors of the recent paper published in Stem Cell Reports entitled, Piwi maintains homeostasis in the Drosophila adult intestine.GuestsHaifan Lin, PhD, Yale UniversityXiongzhuo Tang, PhD, Hunan Agricultural UniversityHostMartin Pera, PhD, Editor-in-Chief, Stem Cell Reports and The Jackson LaboratoryTwitter: @martinperaJAXSupporting ContentPiwi maintains homeostasis in the Drosophila adult intestine, Tang, et al., Stem Cell Reports (2023)About Stem Cell ReportsStem Cell Reports is the open access journal of the ISSCR for communicating basic discoveries in stem cell research, in addition to translational and clinical studies. Stem Cell Reports focuses on original research with conceptual or practical advances that are of broad interest to stem cell biologists and clinicians. Twitter: @StemCellReportsAbout ISSCRWith more than 4,600 members from 75+ countries, the International Society for Stem Cell Research (@ISSCR) is the preeminent global, cross-disciplinary, science-based organization dedicated to stem cell research and its translation to the clinic. The ISSCR mission is to promote excellence in stem cell science and applications to human health.ISSCR StaffKeith Alm, Chief Executive OfficerYvonne Fisher, Managing Editor, Stem Cell ReportsKym Kilbourne, Director of Media and Strategic CommunicationsJack Mosher, Scientific AdvisorVoice WorkBen Snitkoff
In this episode I have the honour to interview a Nobel Laureate who has devoted his life to understanding the way we think. His work has interesting links, not only to my new research topic of cognitive biases, but also on humanity's continuing self examination of consciousness and the mysteries of the mind. Berkely-trained psychologist Daniel Kahneman was corecipient of the Nobel Prize for Economics in 2002 for his integration of psychological research into economic science. His pioneering work examined human judgment and decision making under uncertainty. He was a lecturer (1961–70) and a professor (1970–78) of psychology at the Hebrew University, University of British Columbia, University of California Berkeley, and Princeton University where he was the Eugene Higgins Professor of Psychology and a professor of public affairs at Princeton's Woodrow Wilson School of Public and International Affairs. Kahneman's groundbreaking nobel research showed that people's inferences of future probabilities are not strictly rational, but show various biases. In 2011 Kahneman received the Talcott Parsons Prize from the American Academy of Arts and Sciences for his contributions to the social sciences. Also that year he published the best-selling book Thinking, Fast and Slow, which highlights two different ways in which people make decisions. His other books included Noise: A Flaw in Human Judgment. In 2013 Kahneman was awarded the U.S. Presidential Medal of Freedom. Follow me at www.therationalview.ca Join the Facebook discussion @TheRationalView Twitter @AlScottRational Instagram @The_Rational_View #TheRationalView #podcast #consciousness #cognitivebias #mind #economics #rationality
Eric chats with Susan Fiske, Eugene Higgins Professor of Psychology and Professor of Public Affairs at Princeton University. Susan is one of the world's leading scholars studying social cognition, having written more than 400 articles and chapters as well as several books, including Envy Up, Scorn Down, and The Human Brand. She has won more awards than could possibly be listed, including a Guggenheim Fellowship and the APA Distinguished Scientific Contributions Award. Susan's biography is currently being highlighted in the 40 Women in Science, Engineering, and Medicine exhibit at the National Academy of Sciences, to which she was elected in 2013. In this episode, Eric asks Susan about her latest work on how diverse environments paradoxically make us see different ethnic groups as more, not less similar. In the second half of the chat, Susan reveals why she brings exotic chocolate to lab meetings and how to find a research idea worth pursuing. She talks about her complicated journey into academia and how she developed her influential stereotype content model. She discusses the importance of female role models and the obstacles women face in academia. As if that is not exciting enough, she even gives dating advice!If you found this episode interesting at all, consider leaving us a good rating! It just takes a second but will allow us to reach more people and make them excited about psychology.Links:Susan's paper on stereotype dispersion: https://www.pnas.org/doi/abs/10.1073/pnas.2000333117 Susan's book on envy and scorn: https://www.russellsage.org/publications/envy-scorn-down-1 Susan's book on marketing psychology: https://thehumanbrand.com/ Eric's websiteEric's Twitter @EricNeumannPsyPodcast Twitter @StanfordPsyPodLet us know what you thought of this episode, or of the podcast! :) stanfordpsychpodcast@gmail.com
------------------Support the channel------------ Patreon: https://www.patreon.com/thedissenter PayPal: paypal.me/thedissenter PayPal Subscription 1 Dollar: https://tinyurl.com/yb3acuuy PayPal Subscription 3 Dollars: https://tinyurl.com/ybn6bg9l PayPal Subscription 5 Dollars: https://tinyurl.com/ycmr9gpz PayPal Subscription 10 Dollars: https://tinyurl.com/y9r3fc9m PayPal Subscription 20 Dollars: https://tinyurl.com/y95uvkao ------------------Follow me on--------------------- Facebook: https://www.facebook.com/thedissenteryt/ Twitter: https://twitter.com/TheDissenterYT Anchor (podcast): https://anchor.fm/thedissenter This show is sponsored by Enlites, Learning & Development done differently. Check the website here: http://enlites.com/ Dr. Susan Fiske is Eugene Higgins Professor of Psychology and Public Affairs at Princeton University. Dr. Fiske's research addresses how stereotyping, prejudice, and discrimination are encouraged or discouraged by social relationships, such as cooperation, competition, and power. In this episode, we talk about social categorization, stereotypes, prejudice, discrimination., individuation, and social comparison. -- A HUGE THANK YOU TO MY PATRONS/SUPPORTERS: KARIN LIETZCKE, ANN BLANCHETTE, PER HELGE LARSEN, LAU GUERREIRO, JERRY MULLER, HANS FREDRIK SUNDE, BERNARDO SEIXAS, HERBERT GINTIS, RUTGER VOS, RICARDO VLADIMIRO, CRAIG HEALY, OLAF ALEX, PHILIP KURIAN, JONATHAN VISSER, JAKOB KLINKBY, ADAM KESSEL, MATTHEW WHITINGBIRD, ARNAUD WOLFF, TIM HOLLOSY, HENRIK AHLENIUS, JOHN CONNORS, PAULINA BARREN, FILIP FORS CONNOLLY, DAN DEMETRIOU, ROBERT WINDHAGER, RUI INACIO, ARTHUR KOH, ZOOP, MARCO NEVES, COLIN HOLBROOK, SUSAN PINKER, PABLO SANTURBANO, SIMON COLUMBUS, PHIL KAVANAGH, JORGE ESPINHA, CORY CLARK, MARK BLYTH, ROBERTO INGUANZO, MIKKEL STORMYR, ERIC NEURMANN, SAMUEL ANDREEFF, FRANCIS FORDE, TIAGO NUNES, BERNARD HUGUENEY, ALEXANDER DANNBAUER, FERGAL CUSSEN, YEVHEN BODRENKO, HAL HERZOG, NUNO MACHADO, DON ROSS, JONATHAN LEIBRANT, JOÃO LINHARES, OZLEM BULUT, NATHAN NGUYEN, STANTON T, SAMUEL CORREA, ERIK HAINES, MARK SMITH, J.W., JOÃO EIRA, TOM HUMMEL, SARDUS FRANCE, DAVID SLOAN WILSON, YACILA DEZA-ARAUJO, IDAN SOLON, ROMAIN ROCH, DMITRY GRIGORYEV, TOM ROTH, DIEGO LONDOÑO CORREA, YANICK PUNTER, ADANER USMANI, CHARLOTTE BLEASE, NICOLE BARBARO, ADAM HUNT, PAWEL OSTASZEWSKI, AL ORTIZ, NELLEKE BAK, KATHRINE AND PATRICK TOBIN, GUY MADISON, GARY G HELLMANN, SAIMA AFZAL, ADRIAN JAEGGI, NICK GOLDEN, PAULO TOLENTINO, JOÃO BARBOSA, JULIAN PRICE, EDWARD HALL, HEDIN BRØNNER, DOUGLAS P. FRY, FRANCA BORTOLOTTI, GABRIEL PONS CORTÈS, URSULA LITZCKE, DENISE COOK, SCOTT, ZACHARY FISH, TIM DUFFY, AND TRADERINNYC! A SPECIAL THANKS TO MY PRODUCERS, YZAR WEHBE, JIM FRANK, ŁUKASZ STAFINIAK, IAN GILLIGAN, LUIS CAYETANO, TOM VANEGDOM, CURTIS DIXON, BENEDIKT MUELLER, VEGA GIDEY, THOMAS TRUMBLE, AND NUNO ELDER! AND TO MY EXECUTIVE PRODUCERS, MICHAL RUSIECKI, ROSEY, JAMES PRATT, MATTHEW LAVENDER, SERGIU CODREANU, AND BOGDAN KANIVETS!
Life gets busy. Has Thinking, Fast and Slow been gathering dust on your bookshelf? Instead, pick up the key ideas now. We're scratching the surface here. If you don't already have the book, order it https://geni.us/thinking-fast-book (here) or get thehttps://geni.us/slow-free-audiobook ( audiobook for free) on Amazon to learn the juicy details. --- Get the PDF, full text, and animated versions of this analysis and summary in our free top-ranking app: https://go.getstoryshots.com/free (https://go.getstoryshots.com/free) Daniel Kahneman's Perspectivehttps://geni.us/daniel-kahneman-bio (Daniel Kahneman) is Professor of Psychology and Public Affairs Emeritus at the Princeton School of Public and International Affairs, the Eugene Higgins Professor of Psychology Emeritus at Princeton University, and a fellow of the Center for Rationality at the Hebrew University in Jerusalem. Dr. Kahneman is a member of the National Academy of Science, the Philosophical Society, and the American Academy of Arts and Sciences. He is also a fellow of the American Psychological Association, the American Psychological Society, the Society of Experimental Psychologists, and the Econometric Society. In 2015, The Economist listed him as the seventh most influential economist in the world. In 2002, Kahneman was also awarded a Nobel Prize in Economic Sciences. Introductionhttps://geni.us/slow-free-audiobook (Thinking, Fast and Slow) provides an outline of the two most common approaches our brains utilize. Like a computer, our brain is built of systems. System 1 is fast, intuitive, and emotional. Daniel Kahneman encourages us to move away from our reliance on this system. System 1 is the most common source of mistakes and stagnation. In comparison, system 2 is a slower, more deliberate, and logical thought process. Kahneman recommends tapping into this system more frequently. As well as this advice, Kahneman provides guidance on how and why we make our decisions. StoryShot #1: System 1 Is InnateThere are two systems associated with our thought processes. For each system, Kahneman outlines the primary functions and the decision making processes associated with each system. System 1 includes all capabilities that are innate and generally shared with similar creatures within the animal kingdom. For example, each of us is born with an innate ability to recognize objects, orient our attention to important stimuli, and fear things linked to death or disease. System 1 also deals with mental activities that have become near-innate by becoming faster and more automatic. These activities generally move into system 1 because of prolonged practice. Certain pieces of knowledge will be automatic for you. For example, you do not even have to think about what the capital of England is. Over time, you have built an automatic association with the question, ‘What is the capital of England?' As well as intuitive knowledge, system 1 also deals with learned skills, such as reading a book, riding a bike and how to act in common social situations. There are also certain actions that are generally in system 1 but can also fall into system 2. This overlap occurs if you are making a deliberate effort to engage with that action. For example, chewing will generally fall into system 1. That said, suppose you become aware that you should be chewing your food more than you had been. In that case, some of your chewing behaviors will be shifted into the effortful system 2. Attention is often associated with both systems 1 and 2. They work in tandem. For example, system 1 will be driving your immediate involuntary reaction to a loud sound. Your system 2 will then take over and offer voluntary attention to this sound and logical reasoning about the sound's cause. System 1 is a filter by which you interpret your experiences. It is the system you use for making intuitive decisions. So, it is undoubtedly the oldest brain system as it is evolutionarily primitive....
DANIEL KAHNEMAN (https://www.edge.org/memberbio/daniel_kahneman) is Eugene Higgins Professor of Psychology Emeritus, Princeton University, author of Thinking, Fast and Slow, and co-author (with Cass R. Sunstein and Olivier Sibony) of Noise. He is the winner of the 2013 Presidential Medal of Honor, and the recipient of the 2002 Nobel Prize in Economic Sciences. The Conversation: https://www.edge.org/conversation/daniel_kahneman-adversarial-collaboration
Daniel Kahneman is Professor of Psychology and Public Affairs Emeritus at the Princeton School of Public and International Affairs, the Eugene Higgins Professor of Psychology Emeritus at Princeton University, and a fellow of the Center for Rationality at the Hebrew University in Jerusalem. Dr. Kahneman has held the position of professor of psychology at the Hebrew University in Jerusalem (1970-1978), the University of British Columbia (1978-1986), and the University of California, Berkeley (1986-1994). Dr. Kahneman is a member of the National Academy of Science, the Philosophical Society, the American Academy of Arts and Sciences and a fellow of the American Psychological Association, the American Psychological Society, the Society of Experimental Psychologists, and the Econometric Society. He has been the recipient of many awards, among them the Distinguished Scientific Contribution Award of the American Psychological Association (1982) and the Grawemeyer Prize (2002), both jointly with Amos Tversky, the Warren Medal of the Society of Experimental Psychologists (1995), the Hilgard Award for Career Contributions to General Psychology (1995), the Nobel Prize in Economic Sciences (2002), the Lifetime Contribution Award of the American Psychological Association (2007), and the Presidential Medal of Freedom (2013). Dr. Kahneman holds honorary degrees from numerous Universities.
Read the full transcript here. How can we apply the theory of measurement accuracy to human judgments? How can cognitive biases affect both the bias term and the noise term in measurement error? How much noise should we expect in judgments of various kinds? Is there reason to think that machines will eventually make better decisions than humans in all domains? How does machine decision-making differ (if at all) from human decision-making? In what domains should we work to reduce variance in decision-making? If machines learn use human decisions as training data, then to what extent will human biases become "baked into" machine decisions? And can such biases be compensated for? Are there any domains where human judgment will always be preferable to machine judgment? What does the "fragile families" study tell us about the limits of predicting life outcomes? What does good decision "hygiene" look like? Why do people focus more on bias than noise when trying to reduce error? To what extent can people improve their decision-making abilities? How can we recognize good ideas when we have them? Humans aren't fully rational, but are they irrational?Daniel Kahneman is Professor of Psychology and Public Affairs Emeritus at the Princeton School of Public and International Affairs, the Eugene Higgins Professor of Psychology Emeritus at Princeton University, and a fellow of the Center for Rationality at the Hebrew University in Jerusalem. Dr. Kahneman has held the position of professor of psychology at the Hebrew University in Jerusalem (1970-1978), the University of British Columbia (1978-1986), and the University of California, Berkeley (1986-1994). He is a member of the National Academy of Science, the Philosophical Society, the American Academy of Arts and Sciences, and is a fellow of the American Psychological Association, the American Psychological Society, the Society of Experimental Psychologists, and the Econometric Society. He has been the recipient of many awards, among them the Distinguished Scientific Contribution Award of the American Psychological Association (1982) and the Grawemeyer Prize (2002), both jointly with Amos Tversky, the Warren Medal of the Society of Experimental Psychologists (1995), the Hilgard Award for Career Contributions to General Psychology (1995), the Nobel Prize in Economic Sciences (2002), the Lifetime Contribution Award of the American Psychological Association (2007), and the Presidential Medal of Freedom (2013). He holds honorary degrees from numerous universities. Find out more about him here.Here's the link to the Thought Saver deck that accompanies this episode: https://app.thoughtsaver.com/embed/JGXcbe19e1?start=1&end=17 [Read more]
Read the full transcriptHow can we apply the theory of measurement accuracy to human judgments? How can cognitive biases affect both the bias term and the noise term in measurement error? How much noise should we expect in judgments of various kinds? Is there reason to think that machines will eventually make better decisions than humans in all domains? How does machine decision-making differ (if at all) from human decision-making? In what domains should we work to reduce variance in decision-making? If machines learn use human decisions as training data, then to what extent will human biases become "baked into" machine decisions? And can such biases be compensated for? Are there any domains where human judgment will always be preferable to machine judgment? What does the "fragile families" study tell us about the limits of predicting life outcomes? What does good decision "hygiene" look like? Why do people focus more on bias than noise when trying to reduce error? To what extent can people improve their decision-making abilities? How can we recognize good ideas when we have them? Humans aren't fully rational, but are they irrational?Daniel Kahneman is Professor of Psychology and Public Affairs Emeritus at the Princeton School of Public and International Affairs, the Eugene Higgins Professor of Psychology Emeritus at Princeton University, and a fellow of the Center for Rationality at the Hebrew University in Jerusalem. Dr. Kahneman has held the position of professor of psychology at the Hebrew University in Jerusalem (1970-1978), the University of British Columbia (1978-1986), and the University of California, Berkeley (1986-1994). He is a member of the National Academy of Science, the Philosophical Society, the American Academy of Arts and Sciences, and is a fellow of the American Psychological Association, the American Psychological Society, the Society of Experimental Psychologists, and the Econometric Society. He has been the recipient of many awards, among them the Distinguished Scientific Contribution Award of the American Psychological Association (1982) and the Grawemeyer Prize (2002), both jointly with Amos Tversky, the Warren Medal of the Society of Experimental Psychologists (1995), the Hilgard Award for Career Contributions to General Psychology (1995), the Nobel Prize in Economic Sciences (2002), the Lifetime Contribution Award of the American Psychological Association (2007), and the Presidential Medal of Freedom (2013). He holds honorary degrees from numerous universities. Find out more about him here.Here's the link to the Thought Saver deck that accompanies this episode: https://app.thoughtsaver.com/embed/JGXcbe19e1?start=1&end=17
How can we apply the theory of measurement accuracy to human judgments? How can cognitive biases affect both the bias term and the noise term in measurement error? How much noise should we expect in judgments of various kinds? Is there reason to think that machines will eventually make better decisions than humans in all domains? How does machine decision-making differ (if at all) from human decision-making? In what domains should we work to reduce variance in decision-making? If machines learn use human decisions as training data, then to what extent will human biases become "baked into" machine decisions? And can such biases be compensated for? Are there any domains where human judgment will always be preferable to machine judgment? What does the "fragile families" study tell us about the limits of predicting life outcomes? What does good decision "hygiene" look like? Why do people focus more on bias than noise when trying to reduce error? To what extent can people improve their decision-making abilities? How can we recognize good ideas when we have them? Humans aren't fully rational, but are they irrational?Daniel Kahneman is Professor of Psychology and Public Affairs Emeritus at the Princeton School of Public and International Affairs, the Eugene Higgins Professor of Psychology Emeritus at Princeton University, and a fellow of the Center for Rationality at the Hebrew University in Jerusalem. Dr. Kahneman has held the position of professor of psychology at the Hebrew University in Jerusalem (1970-1978), the University of British Columbia (1978-1986), and the University of California, Berkeley (1986-1994). He is a member of the National Academy of Science, the Philosophical Society, the American Academy of Arts and Sciences, and is a fellow of the American Psychological Association, the American Psychological Society, the Society of Experimental Psychologists, and the Econometric Society. He has been the recipient of many awards, among them the Distinguished Scientific Contribution Award of the American Psychological Association (1982) and the Grawemeyer Prize (2002), both jointly with Amos Tversky, the Warren Medal of the Society of Experimental Psychologists (1995), the Hilgard Award for Career Contributions to General Psychology (1995), the Nobel Prize in Economic Sciences (2002), the Lifetime Contribution Award of the American Psychological Association (2007), and the Presidential Medal of Freedom (2013). He holds honorary degrees from numerous universities. Find out more about him here.Here's the link to the Thought Saver deck that accompanies this episode: https://app.thoughtsaver.com/embed/JGXcbe19e1?start=1&end=17
How can we apply the theory of measurement accuracy to human judgments? How can cognitive biases affect both the bias term and the noise term in measurement error? How much noise should we expect in judgments of various kinds? Is there reason to think that machines will eventually make better decisions than humans in all domains? How does machine decision-making differ (if at all) from human decision-making? In what domains should we work to reduce variance in decision-making? If machines learn use human decisions as training data, then to what extent will human biases become "baked into" machine decisions? And can such biases be compensated for? Are there any domains where human judgment will always be preferable to machine judgment? What does the "fragile families" study tell us about the limits of predicting life outcomes? What does good decision "hygiene" look like? Why do people focus more on bias than noise when trying to reduce error? To what extent can people improve their decision-making abilities? How can we recognize good ideas when we have them? Humans aren't fully rational, but are they irrational? Daniel Kahneman is Professor of Psychology and Public Affairs Emeritus at the Princeton School of Public and International Affairs, the Eugene Higgins Professor of Psychology Emeritus at Princeton University, and a fellow of the Center for Rationality at the Hebrew University in Jerusalem. Dr. Kahneman has held the position of professor of psychology at the Hebrew University in Jerusalem (1970-1978), the University of British Columbia (1978-1986), and the University of California, Berkeley (1986-1994). He is a member of the National Academy of Science, the Philosophical Society, the American Academy of Arts and Sciences, and is a fellow of the American Psychological Association, the American Psychological Society, the Society of Experimental Psychologists, and the Econometric Society. He has been the recipient of many awards, among them the Distinguished Scientific Contribution Award of the American Psychological Association (1982) and the Grawemeyer Prize (2002), both jointly with Amos Tversky, the Warren Medal of the Society of Experimental Psychologists (1995), the Hilgard Award for Career Contributions to General Psychology (1995), the Nobel Prize in Economic Sciences (2002), the Lifetime Contribution Award of the American Psychological Association (2007), and the Presidential Medal of Freedom (2013). He holds honorary degrees from numerous universities. Find out more about him here.
Professor Neta Bahcall is a preeminent observational cosmologist and is the Eugene Higgins Professor of Astrophysics at Princeton University.Dr. Neta Bahcall was born in Israel. After completing her Bachelor's and Master's degree, she received her PhD from Tel Aviv University in 1970. Her husband, Dr. John Bahcall, was also a pioneer in the field.An interesting fact: Dr. Neta Bahcall's and Dr. John Bahcall's wedding rings were sent to the Hubble Space Telescope, and they flew around the earth more than two hundred times! Listen to this episode to learn more about this intriguing story!Dr. Neta Bahcall has held many prestigious positions such as the first Head of the Science Program Selection Office and Chief of the General Observer Branch at the Hubble Space Telescope Science Institute in Baltimore. She is the recipient of the prestigious Vaucouleurs Medal, Payne-Gaposchkin Award, the Bennett-McWilliams Award, an Honorary Doctor of Science Degree - OSU, Century Lecturer of the AAS, and member of various NASA, NSF, NAS, and Congressional Science committees."How much dark matter exists in the Universe and where is it located? What is the nature of the mysterious dark energy? What is the large-scale structure of our Universe? How did structure form and evolve? What is the fate of our Universe and its expansion?" These are some of the questions that Dr. Neta Bahcall researches.I hope you will enjoy listening to this episode! Subscribe, share this episode with your friends, and let me know your thoughts in the comments!Sources:Dr. Bahcall's bio: Department of Astrophysical Sciences, Princeton UniversityMusic credits: Querida- Cornelio and Riversides- Tape Machines both from Epidemic Sound
You can support this podcast and get early releases and bonus content at https://www.patreon.com/aksubversive Or check out my writing and the early releases on Substack at https://alexkaschuta.substack.com/ Sergiu Klainerman is the Eugene Higgins Professor of Mathematics at Princeton, where he's been teaching since 1987. He's also a fellow Romanian, an anti-communist dissident, someone who successfully fled the regime, and, recently, a fearless voice in what he sees as a rise in the US of the same forces he left behind in 1980s Romania. We speak about: His story, becoming disenchanted with communism early on, falling in love with mathematics, and finding a way to escape. The spreading politics of grievance Romania and the eternal Transylvania vs. Bucharest beauty contest Solzhenitsyn's Harvard Address, "A World Split Apart" and how prophetic he was about what was already happening to a devitalized and self-consuming western liberalism. Faith vs. Reason in mathematics and beyond "The Scientific Consensus" and its discontents Covid and narrative "Science" His recommended subversive thinker is Galileo Galilei. You can find his recent essays in Newsweek, Quillette, and National Review. --- Send in a voice message: https://anchor.fm/aksubversive/message
The classic economic theory embedded in western democracies holds an assumption that human beings will almost always behave rationally in the end and make logical choices that will keep our society balanced on the whole. Daniel Kahneman is the psychologist who won the Nobel Prize in Economics for showing that this is simply not true. There’s something sobering — but also helpfully grounding — in speaking with this brilliant and humane scholar who explains why none of us is an equation that computes. As surely as we breathe, we will contradict ourselves and confound each other.Daniel Kahneman received the Nobel Prize in Economics in 2002. He’s best known for his book, Thinking, Fast and Slow and is now releasing a new book, Noise: A Flaw in Human Judgment, written with Olivier Sibony and Cass R. Sunstein. He’s the Eugene Higgins Professor of Psychology Emeritus at Princeton University, Professor of Psychology and Public Affairs Emeritus at the Princeton School of Public and International Affairs, and a fellow of the Center for Rationality at the Hebrew University in Jerusalem.This interview is edited and produced with music and other features in the On Being episode "Daniel Kahneman — Why We Contradict Ourselves and Confound Each Other." Find the transcript for that show at onbeing.org.
The classic economic theory embedded in western democracies holds an assumption that human beings will almost always behave rationally in the end and make logical choices that will keep our society balanced on the whole. Daniel Kahneman is the psychologist who won the Nobel Prize in Economics for showing that this is simply not true. There’s something sobering — but also helpfully grounding — in speaking with this brilliant and humane scholar who explains why none of us is an equation that computes. As surely as we breathe, we will contradict ourselves and confound each other.Daniel Kahneman received the Nobel Prize in Economics in 2002. He’s best known for his book, Thinking, Fast and Slow and is now releasing a new book, Noise: A Flaw in Human Judgment, written with Olivier Sibony and Cass R. Sunstein. He’s the Eugene Higgins Professor of Psychology Emeritus at Princeton University, Professor of Psychology and Public Affairs Emeritus at the Princeton School of Public and International Affairs, and a fellow of the Center for Rationality at the Hebrew University in Jerusalem.Find the transcript for this show at onbeing.org.This show originally aired on October 5, 2017.
Sergiu Klainerman is the Eugene Higgins Professor of Mathematics at Princeton University. Born in communist Romania, he sees disturbing parallels between life in the Soviet Bloc and the "soft totalitarianism" or "pre-totalitarianism" taking root in America. He joins the show to discuss these parallels and reflect on Aleksandr Solzhenitsyn's 1978 speech, "A World Split Apart." "Reflections on Solzhenitsyn’s Harvard Address": https://quillette.com/2020/10/24/reflections-on-solzhenitsyns-harvard-address/ "How to Fight the Enemies of Academic Freedom": https://quillette.com/2020/08/10/how-to-fight-the-enemies-of-academic-freedom/ "Princeton's President Is Wrong. The University Is Not Systemically Racist": https://www.newsweek.com/princetons-president-wrong-university-not-systemically-racist-opinion-1530480 "Live Not by Lies": https://journals.sagepub.com/doi/pdf/10.1080/03064220408537357 "A World Split Apart": https://www.solzhenitsyncenter.org/a-world-split-apart
Quantum computing is the latest “buzz-word” in the tech industry – with over $450 million of private funding investments made between 2017 and 2018 – but what are quantum computers and how will they spark the quantum revolution? Do they truly live up to the “hype” or are the challenges facing them not resolvable in the near future? In this episode, Tiger and aspiring physicist Harsh Babla interview Prof. Steven Girvin to learn about his cutting-edge research in the field, his perspective on Google’s recent quantum supremacy claim, venture capital investments in the field, national security concerns raised by quantum computers, the philosophical implications behind quantum computing, and more. This might not be your one-stop shop for understanding quantum physics, but it should provide you with the appropriate technical and theoretical background to understand many of the current debates. Steven Girvin is the Eugene Higgins Professor of Physics at Yale University. He’s a theoretical physicist known for his founding role in developing Circuit QED – an architecture now used by Google, IBM, Rigetti, and many other companies to build quantum computers. Prof. Girvin is a strong advocate for the “Second Quantum Revolution.” He explains to us that the first quantum revolution, in the early 1900s, gave us a unique understanding of the world, explaining the strange behavior of atoms and molecules. This kicked off a spree of innovation, revolutionizing information processing with the transistor, atomic clock, and laser. The past couple of decades have established a new technological era. While first suggested in the early 1980s, quantum computers are finally being physically realized and made commercially available. These devices use the laws of quantum mechanics to solve problems that would otherwise take classical computers exponentially longer to work out. As such, they’ve emerged as a natural paradigm to accelerate breakthroughs in drug development to save lives, innovative materials for renewable energy generation, financial strategies to live comfortably in retirement, cryptography techniques to ensure provably secure communication, and machine learning methods to supercharge hardware. While quantum computers might seem like the panacea for many society’s challenges, most quantum computers today aren’t always able to return correct answers for even the most modest calculations. Prof. Girvin explains that this is because current quantum systems are plagued by several pervasive physical constraints: a significant susceptibility to environmental errors, an inability to control multiple qubits simultaneously, a lack of robust error correction schemes, to mention a few. These constraints gradually scramble the information stored in the quantum bits (qubits), limiting the qubits’ lifetimes to only a few microseconds. Prof. Girvin is very hopeful for the industry to overcome these hurdles, but he’s worried that there’s currently a tremendous shortage of engineers and experts in the field. He believes the education system is overdue for important changes, to get young minds excited about working on quantum computing, without necessarily pursuing a Ph.D. in Physics. The perhaps slightly technical conversation with Prof. Girvin covers a wide range of topics, from quantum mechanics to education and investing in technologies with far-reaching international consequences. But our curiosity certainly does not stop there, and we end the interview with a short but deep discussion on philosophy. Mathematician Alan Turing was famous for publishing philosophy journals and debating with Wittgenstein. It seems that there’s much overlap between the scientifically and metaphysically unanswerable questions, so we ask Prof. Girvin how science has helped him reason through philosophical questions.
When you close your eyes and imagine the universe, what do you see? Maybe you picture billions of swirling galaxies made of dust, gas, stars, and planets. But, what if we told you that the major source of mass in the universe is made out of something we cannot see? Not only can we not see it, we aren’t even entirely sure what it is. This mysterious cosmic substance is called dark matter, and it is the subject of this episode. To learn about dark matter, we spoke to Dr. Neta Bahcall, the Eugene Higgins Professor of Astrophysics at Princeton University. We discuss how it was discovered, as well as how astrophysicists are certain it exists, but are still frustrated by the elusive nature of the particles that make up dark matter. We also discuss some of the work currently being done to better understand what dark matter is, how it’s distributed in the universe, and what effect it has on the structure and evolution of the universe. This episode was written & produced by Stella Belonwu, Anna Lipkin, Cindy Liu and Liron Noiman. For more information on dark matter, check out Modelling the Invisible (https://www.modellinginvisible.org/dark-matter/) and The Illustris Simulation (https://www.illustris-project.org/about/). Additionally, to understand some of the concepts that we touched on, check out The Physics Hypertextbook (https://physics.info/standard/). The cover art for this episode is an image of the Abell 2218 galaxy cluster and beautifully demonstrates the effect of gravitational lensing, which we discuss in the episode [30:46]. The image was pulled from https://www.spacetelescope.org/images/heic0814a/, with credits to NASA, ESA, and Johan Richard from Caltech, with acknowledgements to Davide de Martin & James Long (ESA/Hubble). Music and sound effects were acquired from the YouTube Audio Library, www.freesound.org, and Free Music Archive. Music included in this episode: Algorithms and Moonrise by Chad Crouch Saturn V by Lee Rosevere Cute Avalanche by RKVC English Country Garden by Aaron Kenny Orbital Romance by Sir Cubworth Alive Evil by Hainbach Ether Oar by The Whole Other Da Jazz Blues by Doug Maxwell
In this episode of Choiceology with Katy Milkman, we look at how framing a decision based on what you stand to lose versus what you stand to gain affects your tolerance of risk.Luis Green was a contestant on the popular TV game show Deal or No Deal. The game is largely one of chance, but there are moments during play where the contestant has an option to accept a cash offer to quit. At one point in the game, Luis was offered $333,000 to simply walk away. A guaranteed win! It seems like an obvious choice. But as you’ll hear from the story, there are other factors that influenced his decision.Katy illustrates these factors with a version of a famous experiment. Volunteers are presented with two differently worded but mathematically identical scenarios. A simple shift from framing the scenario as a potential gain to one of potential loss results in starkly different choices from the volunteers.Next, Katy speaks with special guest Daniel Kahneman about the underlying theory that explains human behavior in these types of situations.Daniel Kahneman is a professor of psychology and public affairs emeritus at the Woodrow Wilson School and the Eugene Higgins Professor of Psychology Emeritus at Princeton University. He was awarded the 2002 Nobel Prize in Economics for his pioneering research with Amos Tversky. Their work helped establish the field of behavioral economics. Kahneman is also the author of the bestselling book Thinking, Fast and Slow.Finally, Katy speaks with Colin Camerer about some of his favorite studies on risk seeking in the domain of losses, as well as practical approaches for avoiding this less-than-ideal behavior.Colin Camerer is the Robert Kirby Professor of Behavioral Finance and Economics at the California Institute of Technology, where he teaches cognitive psychology and economics. You can read his paper “Prospect Theory in the Wild: Evidence from the Field” here.Choiceology is an original podcast from Charles Schwab. For more on the series, visit schwab.com/podcast.If you enjoy the show, please leave a ⭐⭐⭐⭐⭐ rating or review on Apple Podcasts.Important Disclosures:All expressions of opinion are subject to change without notice in reaction to shifting market conditions.The comments, views, and opinions expressed in the presentation are those of the speakers and do not necessarily represent the views of Charles Schwab.Data contained herein from third-party providers is obtained from what are considered reliable sources. However, its accuracy, completeness or reliability cannot be guaranteed.(0919-9CT3)
Today’s conversation is with one of the finest intellectual investors and academic at heart, Michael Mauboussin. Michael is the Director of Research at BlueMountain Capital Management in New York and was formerly the Head of Global Financial Strategies at Credit Suisse and Chief Investment Strategist at Legg Mason Capital Management. While rising to the top in his corporate career, Michael authored three books, including my favorite, More Than You Know: Finding Financial Wisdom in Unconventional Places, which was named one of the best business books by Businessweek and which features prominently in today’s show. Michael has been an adjunct professor of finance at Columbia Business School since 1993 and is on the faculty of the Heilbrunn Center for Graham and Dodd Investing. He is also Chairman of the Board of Trustees of the Santa Fe Institute, a leading center for multi-disciplinary research in complex systems theory. On this episode, Michael and I talk about the early epiphany he had that set him on the path to Chief U.S. Investment Strategist, the importance of teaching value investing alongside psychology, the main contributors to investment bias, the importance of cognitive diversity, the top three techniques you can use to mitigate against bias in your investment processes, and so much more! Key Topics: The epiphany Michael had from reading Creating Shareholder Value early in his Wall Street career (3:32) Why we should teach value investing in a way that includes both finance and psychology (5:38) How Michael’s focus on strategy and valuation issues helped him move from food analyst to Chief U.S. Investment Strategist at Credit Suisse (7:02) Why analyzing the investment process has been an underlying theme throughout Michael’s career (7:30) The three aspects to consider when examining how biases get incorporated into market valuations (9:54) The effect of market structure on the incorporation of biases (11:45) The conditions which have to be in place for the wisdom of crowds to operate efficiently (12:13) Why market prices don’t directly reflect information (14:05) The impact of financial institutions on the workings of the economy at large (16:04) Why cognitive diversity leads to better decision-making for complex issues (17:33) Applying the Diversity Prediction Theorem (18:47) What the Asch experiment teaches us about biased decision-making (22:07) The surprising neurological findings behind the results of the Asch experiment (24:56) Value investing means being a contrarian and a calculator (26:52) The difference between experience and expertise (28:36) How technology has led to “the expert squeeze” (31:17) Our thoughts on the future of machine-learning versus human judgment for investment decision-making (34:15) The important difference between outcome and process (36:25) Why you should audit your processes as an investor, even when you’re doing well (38:10) Using a base rate to incorporate an outside view into your investment decisions (40:52) How a pre-mortem helps you to identify bias and weaknesses by triggering the interpreter in your brain (43:57) Applying red teaming to investment process analysis and decision-making (46:28) Translating the margin of safety into decision processes (47:30) The types of scenarios which are well-suited to routinizing (51:24) Michael’s thoughts on passive investing (53:12) And much more! Mentioned in this Episode: Michael Mauboussin’s Website Michael Mauboussin’s Books BlueMountain Capital Management Alfred Rappaport’s Book | Creating Shareholder Value: A Guide for Managers and Investors Journal Articles: Franklin Allen | Do Financial Institutions Matter? Solomon E. Asch | Opinions and Social Pressure Sanford J. Grossman and Joseph E. Stiglitz | On the Impossibility of Informationally Efficient Markets Scott Page, Leonid Hurwicz Collegiate Professor of Complex Systems, Political Science, and Economics, The University of Michigan Daniel Kahneman, Professor of Psychology and Public Affairs Emeritus at the Woodrow Wilson School, the Eugene Higgins Professor of Psychology Emeritus at Princeton University Michael Gazzaniga, Director of the SAGE Center for the Study of Mind at the University of California, Santa Barbara Benjamin Graham’s Book | The Intelligent Investor: The Definitive Book on Value Investing. A Book of Practical Counsel Thanks for Listening! Be sure to subscribe on Apple, Google, Spotify, or wherever you get your podcasts. And feel free to drop us a line at valueinvesting@gsb.columbia.edu. Follow the Heilbrunn Center on social media on Instagram, LinkedIn, and more!
Sam Harris speaks with Daniel Kahneman at the Beacon Theatre in NYC. They discuss the replication crisis in science, System 1 and System 2, where intuitions reliably fail, expert intuitions, the power of framing, moral illusions, anticipated regret, the asymmetry between threats and opportunities, the utility of worrying, removing obstacles to wanted behaviors, the remembering self vs the experiencing self, improving the quality of gossip, and other topics. Daniel Kahneman is Eugene Higgins Professor of Psychology Emeritus at Princeton University and Professor of Psychology and Public Affairs Emeritus at Princeton’s Woodrow Wilson School of Public and International Affairs. He received the 2002 Nobel Prize in Economic Sciences for his pioneering work with Amos Tversky on decision-making. His most recent book is Thinking Fast and Slow.
With his book “Thinking, Fast and Slow,” Daniel Kahneman emerged as one of the most intriguing voices on the complexity of human thought and behavior. He is a psychologist who won the Nobel Prize in economics for helping to create the field of behavioral economics — and is a self-described “constant worrier.” It’s fun, helpful, and more than a little unnerving to apply his insights into why we think and act the way we do in this moment of social and political tumult. Daniel Kahneman is best known for his book “Thinking, Fast and Slow.” He’s the Eugene Higgins Professor of Psychology Emeritus at Princeton University, professor of psychology and public affairs emeritus at Princeton’s Woodrow Wilson School, and a fellow of the Center for Rationality at the Hebrew University in Jerusalem. Find the transcript for this show at onbeing.org.
With his book “Thinking, Fast and Slow,” Daniel Kahneman emerged as one of the most intriguing voices on the complexity of human thought and behavior. He is a psychologist who won the Nobel Prize in economics for helping to create the field of behavioral economics — and is a self-described “constant worrier.” It’s fun, helpful, and more than a little unnerving to apply his insights into why we think and act the way we do in this moment of social and political tumult. Daniel Kahneman is best known for his book “Thinking, Fast and Slow.” He’s the Eugene Higgins Professor of Psychology Emeritus at Princeton University, professor of psychology and public affairs emeritus at Princeton’s Woodrow Wilson School, and a fellow of the Center for Rationality at the Hebrew University in Jerusalem. This interview is edited and produced with music and other features in the On Being episode “Daniel Kahneman — Why We Contradict Ourselves and Confound Each Other.” Find more at onbeing.org.
MOLLY CROCKETT (https://www.edge.org/memberbio/molly_crockett) is an associate professor of experimental psychology, fellow of Jesus College, and distinguished research fellow at the Oxford Centre for Neuroethics, University of Oxford. DANIEL KAHNEMAN (https://www.edge.org/memberbio/daniel_kahneman) is the recipient of the Nobel Prize in Economics (2002), and the Presidential Medal of Freedom (2013). He is the Eugene Higgins Professor of Psychology Emeritus, Princeton, and author of Thinking, Fast and Slow. The Conversation: https://www.edge.org/conversation/mollycrockett-danielkahneman-deontology-or-trustworthiness
JOSHUA KNOBE (https://www.edge.org/memberbio/joshua_knobe) is an experimental philosopher and professor of philosophy and cognitive science at Yale University. DANIEL KAHNEMAN (https://www.edge.org/memberbio/daniel_kahneman) is the recipient of the Nobel Prize in Economics (2002), and the Presidential Medal of Freedom (2013). He is the Eugene Higgins Professor of Psychology Emeritus, Princeton, and author of Thinking Fast and Slow. The Conversation: https://www.edge.org/conversation/joshuaknobe-danielkahneman-a-characteristic-difference
YUVAL NOAH HARARI (https://www.edge.org/memberbio/yuval_noah_harari), Lecturer, Department of History, Hebrew University of Jerusalem, is the author of Sapiens: A Brief History of Humankind. DANIEL KAHNEMAN (https://www.edge.org/memberbio/daniel_kahneman) is the recipient of the Nobel Prize in Economics, 2002 and the Presidential Medal of Freedom, 2013. He is the Eugene Higgins Professor of Psychology Emeritus, Princeton, and author of Thinking, Fast and Slow. The Conversation: https://www.edge.org/conversation/yuvalnoahharari-daniel_kahneman-death-is-optional
Bernard Chazelle is Eugene Higgins Professor of Computer Science at Princeton University. He is a fellow of the Association for Computing Machinery, the American Academy of Arts and Sciences, the John Simon Guggenheim Memorial Foundation, and a member of the European Academy of Sciences. He’s authored an extensive collection of essays on music for A Tiny Revolution. This interview is edited and produced with music and other features in the On Being episode “Bernard Chazelle — Discovering the Cosmology of Bach.” Find more at onbeing.org.
Steven Girvin, Deputy Provost for Science and Technology and Eugene Higgins PRofessor of Physics and Applied Physics speaks about the benefits and pitfalls of interdisciplinary research and teaching.
Robert J. Schoelkopf, professor of applied physics, and Steven Girvin, Eugene Higgins Professor of Physics at Yale discuss their breakthrough results in quantum computing research.