Zukunft Denken – Podcast

Auch heute freue ich mich wieder darüber, einen äußerst kompetenten und prominenten Gast vorstellen zu dürfen: Prof. Gerd Gigerenzer. Das Thema ist eines, das uns seit einiger Zeit begleitet, und auch noch weiter begleiten wird, denn es gehört zu den wesentlichsten Fragen der heutigen Zeit. Werden wir von der stetig steigenden Komplexität in unserer Gesellschaft, Wirtschaft und Wissenschaft überrollt, oder gelingt es, Mechanismen zu entwickeln, trotzdem kluge und resiliente Entscheidungen zu treffen? Entscheidungen, die uns auch helfen, mit komplexen Risiken umzugehen?

Gerd Gigerenzer war unter anderem langjähriger Direktor am Max-Planck-Institut für Bildungsforschung, ist Direktor des Harding Center for Risk Literacy an der Universität Potsdam, Partner von Simply Rational - The Institute for Decisions und Vizepräsident des European Research Council (ERC). Er ist ehemaliger Professor für Psychologie an der Universität von Chicago und John M. Olin Distinguished Visiting Professor, School of Law an der Universität von Virginia. Darüber hinaus ist er Mitglied der Berlin-Brandenburgischen Akademie der Wissenschaften, der Deutschen Akademie der Wissenschaften und der British Academy sowie Ehrenmitglied der American Academy of Arts and Sciences und der American Philosophical Society. Er hat unzählige Preise gewonnen sowie zahlreiche Bücher geschrieben, die nicht nur inhaltlich höchst relevant sondern zudem auch noch sehr zugänglich für eine breite Leserschicht sind. 

Zu seinen Forschungsschwerpunkten zählen:

• Entscheidungen unter Unsicherheit und Zeitbeschränkung
• Risikokompetenz und Risikokommunikation
• Entscheidungsstrategien von Managern, Richtern und Ärzten

Und genau über diese Themen werden wir uns in der Episode unterhalten. Wie geht man in Situationen großer Unsicherheit mit Daten und Informationen um?

»Je größer die Unsicherheit ist, desto mehr Informationen muss man ignorieren.«

Was ist eine Heuristik, und welche Heuristiken wenden wir erfolgreich in welchen Situationen an?

»In Situationen von Unsicherheit, verlassen sich Menschen nicht auf die ganze Vergangenheit, sondern auf die jüngste Vergangenheit — das nennt man recency Heuristik.«

Warum führen mehr Daten nicht immer zu besseren Entscheidungen?

»Ein Datenpunkt, gut gewählt, erlaubt [in vielen Fällen] bessere Vorhersagen als Big Data«

Was ist Intuition und unter welchen Umständen ist intuitives sinnvoller als vermeintlich rationales Entscheiden?

»Intuition ist keine Willkür. Intuition ist gefühltes Wissen, das auf jahrelanger Erfahrung beruht.«

Was ist von den neuen Theorien der Rationalität, z. B. dem System 1 und 2 von Kahnemann zu halten?

»The abject failure of models in the global financial crisis has not dented their popularity among regulators.«, Mervyn King

Was ist defensives Entscheiden, und warum ist es eines der größten Probleme unserer modernen Welt?

»Der Arzt ist nicht in einer Situation, dem Patienten das Beste zu empfehlen. Viele Ärzte fürchten, dass die Patienten klagen, insbesondere, wenn etwas unterlassen wurde. Die Patienten klagen nicht, wenn unnötige Operationen vorgenommen wurden.«

Weniger kann oft mehr sein:

»Viele Menschen denken — auch in der Wissenschaft — mehr ist immer besser.«

Dabei gilt in den meisten Fällen, gerade auch dort, wo wir häufig versuchen, komplexe Modelle anzuwenden:

»Je größer die Unsicherheit ist, umso einfacher muss man die Regulierung [oder das Modell] machen.«

Eine Erkenntnis, die im Grunde jedem klar ist, der sich mit der Steuerung komplexer Systeme auseinandersetzt. Warum handeln wir stetig dagegen?

»Wir brauchen eine Welt, die den Mut hat zur Vereinfachung.«

Und dann gibt es noch den Aspekt der Rückkopplung von (schlechten) Modellen auf die Welt, die sie vermeintlich beschreiben oder vorhersagen, und wir kommen leicht in einen Teufelskreis der zirkulären und selbstverstärkenden Fehler. Wie lassen sich diese vermeiden?
Was wird die Folge sein, wenn diese Formen der Modellierung und Verhaltenssteuerung auf eine immer totalitärere und total überwachte Gesellschaft trifft?

Entwickeln wir uns aber in der Realität mit künstlicher Intelligenz, Large Language Models und IT-getriebener Automatisierung, aber nicht gerade ins Gegenteil? Eine Welt, deren Entscheidungen von immer komplexeren Systemen intransparent getroffen werden, wo niemand mehr nachvollziehen oder bewerten und in Wahrheit verantworten kann, ob diese Entscheidungen sinnvoll sind? Denken wir beispielsweise an Modelle, die Rückfallwahrscheinlichkeiten von Straftätern bewerten.

»Viele Menschen lächeln über altmodische Wahrsager. Doch sobald die Hellseher mit Computern arbeiten, nehmen wir ihre Vorhersagen ernst und sind bereit, für sie zu zahlen.«

Zu welcher Welt bewegen wir uns hin? Zu einer, in der wir radikale Unsicherheit akzeptieren und entsprechen handeln, oder einer, wo wir uns immer mehr der Illusion von Kontrolle, Vorhersagbarkeit und Steuerbarkeit verlieren?

»In einer Welt, in der Technik (vermeintlich) smart wird, brauchen wir vor allem eines, nämlich Menschen, die auch smart werden. Also Menschen, die mitdenken, die sich nicht zurücklehnen und konsumieren; die sich nicht auf das reduzieren lassen, was man ihnen empfiehlt.«

Und zum Ende macht Prof. Gigerenzer noch den wichtigsten Aufruf der heutigen Zeit:

Mitdenken!

Denn es gilt:

»The world is inherently uncertain and to pretend otherwise is to create risk, not to minimise it.«, Mervyn King

Referenzen

Andere Episoden

• Episode 121: Künstliche Unintelligenz
• Episode 118: Science and Decision Making under Uncertainty, A Conversation with Prof. John Ioannidis
• Episode 112: Nullius in Verba — oder: Der Müll der Wissenschaft
• Episode 109: Was ist Komplexität? Ein Gespräch mit Dr. Marco Wehr
• Episode 107: How to Organise Complex Societies? A Conversation with Johan Norberg
• Episode 106: Wissenschaft als Ersatzreligion? Ein Gespräch mit  Manfred Glauninger
• Episode 99: Entkopplung, Kopplung, Rückkopplung
• Episode 92: Wissen und Expertise Teil 2
• Episode 80: Wissen, Expertise und Prognose, eine Reflexion
• Episode 79: Escape from Model Land, a Conversation with Dr. Erica Thompson

Prof. Gerd Gigerenzer

• Prof. Gigerenzer amd MPIB-Berlin

Fachliche Referenzen

• Gerd Gigerenzer, Bauchentscheidungen: Die Intelligenz des Unbewussten und die Macht der Intuition, Goldmann (2008)
• Gerd Gigerenzer, Das Einmaleins der Skepsis: Über den richtigen Umgang mit Zahlen und Risiken, Piper (2015)
• Gerd Gigerenzer, Risiko: Wie man die richtigen Entscheidungen trifft, Pantheon (2020)
• Gerd Gigerenzer, Klick: Wie wir in einer digitalen Welt die Kontrolle behalten und die richtigen Entscheidungen treffen, Bertelsmann (2021)
• Gerd Gigerenzer, Smart Management: Mit einfachen Heuristiken gute Entscheidungen treffen, Campus (2025) 
• Daniel Kahnemann, Schnelles Denken, langsames Denken, Siedler Verlag (2012)
• Gerd Gigerenzer, The rationally wars: a personal reflection, BPP (2024)
• Konstantinos Katsikopoulos, Gerd Gigerenzer et al, Transparent modeling of influenza incidence: Big data or a single data point from psychological theory?, International Journal of Forecasting (2022)
• Mervyn King, John Kay, Radical Uncertainty, Bridge Street Press (2021)
• Rory Sutherland, Alchemy, WH Allen (2021)
• Peter Kruse, next practice. Erfolgreiches Management von Instabilität. Veränderung durch Vernetzung, Gabal (2020)
• John P. Ioannidis, Forecasting for COVID-19 has failed, International Journal of Forecasting (2022)

Willkommen zu einer neuen Folge meines Podcasts! In dieser Episode begrüße ich den renommierten Experten Franz Josef Radermacher vor einem besonderen Gast an der Wand: Albert Einstein. Was hat Einstein mit Energie zu tun? Warum ist Energie die Grundlage menschlichen Wohlstands? Und wie gestalten wir eine nachhaltige Zukunft in einer global vernetzten Welt? Dieses Gespräch nimmt uns mit auf eine Reise durch die Geschichte der Energienutzung, die Herausforderungen der Energiewende und die geopolitischen Dimensionen, die oft übersehen werden.

Prof. Radermacher ist Vorstand des Forschungsinstituts für anwendungsorientierte Wissensverarbeitung, stellv. Vorstandsvorsitzender von Global Energy Solutions e. V. (Ulm), emerit. Professor für Informatik, Universität Ulm, 2000 – 2018 Mitglied des Wissenschaftlichen Beirats beim Bundesministerium für Verkehr und digitale Infrastruktur (BMVI); er ist Ehrenpräsident des Ökosozialen Forum Europa, Wien, Mitglied des UN-Council of Engineers for the Energy Transition (CEET) sowie Mitglied des Club of Rome, Winterthur.

Was hat Einstein mit diesem Gespräch zu tun? Wir beginnen mit der Frage, welche Rolle Energie in unserer Gesellschaft spielt sowie der Tatsache, dass vielen Menschen, vermutlich den meisten, nicht klar ist, was unsere Gesellschaft antreibt? So waren 2023 mehr als 81 Prozent des gesamten weltweiten Energieverbrauchs durch fossile Quellen gedeckt, und die Menge an fossilen Energieträgern wächst ständig.

Wie hat Energie die Menschheit geprägt? Welche Energiequellen hatten wir früher und welchen Einfluss hatte die Veränderung der Energieträger auf unsere Gesellschaft und unseren Lebensstandard? Warum dominieren fossile Brennstoffe heute noch? Kann Energie Armut bekämpfen? Ist es Energie, die Wohlstand schafft?

Warum sind zwei oft übersehene Parameter von so großer Bedeutung: Energiedichte und Platzbedarf?  Kernkraftwerke benötigen wenig Fläche im Vergleich zu Windrädern oder Photovoltaik: 

»Da ist ja ein Faktor 100 dazwischen.« […] »Weil auch Fläche ein extrem knappes Gut ist, ist es problematisch, wenn man eine Energie mit ziemlich niedriger Dichte hat.«

Gleichzeitig sind Energie und Emissionen, besonders Treibhausgase, globale Phänomene, die lokal nicht zu lösen sind.

»Von 2004 bis 2023 haben die globalen Investitionen in Wind und Solar rund 4 Billionen Dollar ausgemacht, und trotzdem sind die fossilen Energieträger dreimal schneller gewachsen.“ Zudem: „In den großen Industrienationen […] eine Reduktion der CO2-Emissionen, aber gleichzeitig einen Zuwachs in Indien und China, der diese Reduktionen um das Faktor 5 überschattet.«, Robert Bryce

Überrascht uns China? China hat mittlerweile die EU auch in den Pro-Kopf-Emissionen überholt. Was passiert, wenn Schwellenländer folgen?

»An China kann man erkennen, was passiert, wenn ein armes Land versucht, Wohlstand aufzubauen. Und das geht bis heute nur mit fossilen Energieträgern.«

Sind schnelle Lösungen gefährlich? Großinfrastruktur, Energiesysteme sind immer eine Frage von Jahrzehnten. Wenn wir versuchen, Dinge hier über das Knie zu brechen, ist die Wahrscheinlichkeit, dass Sie große und extrem teure Fehler machen, enorm. Außerdem stellt sich die Frage, welche Relevanz Europa überhaupt noch hat?

Welche Maßnahmen gegen den Klimawandel könnten erfolgreich sein? Was wurde etwa in Baku beschlossen? Funktionieren Transferzahlungen? Warum scheitert eine Renewables Only Strategie zwangsläufig?

»Die Idee, Renewables Only, ist ja eine von Deutschland immer wieder propagierte Idee.[… Es] ist nur eine Methode, [Entwicklungsländer] arm zu halten«

Aber was ist die Alternative? Was ist Carbon Capture? Was ist die Rolle von Kernkraft? Welche Mischung verschiedener Verfahren ist sinnvoll?

Zuletzt diskutieren wir über Strom vs. Moleküle und den All-Electric-Irrtum. Damit verbunden ist der Irrglaube, Wasserstoff könnte das Renable-Desaster lösen. 

Welche geopolitischen Herausforderungen sind mit diesen Themen verknüpft? Ist Prof. Radermacher optimistisch — für Europa, die Welt? Was könnte man jungen Menschen empfehlen?

Referenzen

Andere Episoden

• Episode 109: Was ist Komplexität? Ein Gespräch mit Dr. Marco Wehr
• Episode 107: How to Organise Complex Societies? A Conversation with Johan Norberg
• Episode 95: Geopolitik und Militär, ein Gespräch mit Brigadier Prof. Walter Feichtinger
• Episode 94: Systemisches Denken und gesellschaftliche Verwundbarkeit, ein Gespräch mit Herbert Saurugg
• Episode 86: Climate Uncertainty and Risk, a conversation with Dr. Judith Curry
• Episode 81: Energie und Ressourcen, ein Gespräch mit Dr. Lars Schernikau
• Episode 73: Ökorealismus, ein Gespräch mit Björn Peters
• Episode 70: Future of Farming, a conversation with Padraic Flood
• Episode 62: Wirtschaft und Umwelt, ein Gespräch mit Prof. Hans-Werner Sinn

Prof. Radermacher

• Forschungsinstitut für anwendungsorientierte Wissensverarbeitung/n
• Global Energy Solutions
• Prof. Radermacher im Vorstand der Global Energy Solutions
• All In: Energie und Wohlstand für eine wachsende Welt, Murmann (2024)

Fachliche Referenzen

• Vaclav Smil, How the World Really Works, Penguin (2022)
• Vaclav Smil, Net Zero 2050, Fraser Institute (2024)
• Robert Bryce, The Energy Transition Isn't (2023)
• Robert Bryce, Numbers Don’t Lie (2024)

In this episode, I had the privilege of speaking with John Ioannidis, a renowned scientist and meta-researcher whose groundbreaking work has shaped our understanding of scientific reliability and its societal implications. We dive into his influential 2005 paper, Why Most Published Research Findings Are False, explore the evolution of scientific challenges over the past two decades, and reflect on how science intersects with policy and public trust—especially in times of crisis like COVID-19.

We begin with John taking us back to 2005, when he published his paper in PLOS Medicine. He explains how it emerged from decades of empirical evidence on biases and false positives in research, considering factors like study size, statistical power, and competition that can distort findings, and why building on shaky foundations wastes time and resources.

“It was one effort to try to put together some possibilities, of calculating what are the chances that once we think we have come up with a scientific discovery with some statistical inference suggesting that we have a statistically significant result, how likely is that not to be so?”

I propose a distinction between “honest” and “dishonest” scientific failures, and John refines this. What does failure really mean, and how can they be categorised?

The discussion turns to the rise of fraud, with John revealing a startling shift: while fraud once required artistry, today’s “paper mills” churn out fake studies at scale. We touch on cases like Jan-Hendrik Schön, who published prolifically in top journals before being exposed, and how modern hyper-productivity, such as a paper every five days, raises red flags yet often goes unchecked.

“Perhaps an estimate for what is going on now is that it accounts for about 10%, not just 1%, because we have new ways of massive… outright fraud.”

This leads to a broader question about science’s efficiency. When we observe scientific output—papers, funding—grows exponentially but does breakthroughs lag? John is cautiously optimistic, acknowledging progress, but agrees efficiency isn’t what it could be. We reference Max Perutz’s recipe for success:

“No politics, no committees, no reports, no referees, no interviews; just gifted, highly motivated people, picked by a few men of good judgement.”

Could this be replicated in today's world or are we stuck in red tape?

“It is true that the progress is not proportional to the massive increase in some of the other numbers.”

We then pivot to nutrition, a field John describes as “messy.” How is it possible that with millions of papers, results are mosty based on shaky correlations rather than solid causal evidence? What are the reasons for this situation and what consequences does it have, e.g. in people trusting scientific results?

“Most of these recommendations are built on thin air. They have no solid science behind them.”

The pandemic looms large next. In 2020 Nassim Taleb and John Ioannidis had a dispute about the measures to be taken. What happened in March 2020 and onwards? Did we as society show paranoid overreactions, fuelled by clueless editorials and media hype?

“I gave interviews where I said, that’s fine. We don’t know what we’re facing with. It is okay to start with some very aggressive measures, but what we need is reliable evidence to be obtained as quickly as possible.”

Was the medicine, metaphorically speaking, worse than the disease? How can society balance worst-case scenarios without paralysis.

“We managed to kill far more by doing what we did.”

Who is framing the public narrative of complex questions like climate change or a pandemic? Is it really science driven, based on the best knowledge we have? In recent years influential scientific magazines publish articles by staff writers that have a high impact on the public perception, but are not necessarily well grounded:

“They know everything before we know anything.”

The conversation grows personal as John shares the toll of the COVID era—death threats to him and his family—and mourns the loss of civil debate. He’d rather hear from critics than echo chambers, but the partisan “war” mindset drowned out reason. Can science recover its humility and openness?

“I think very little of that happened. There was no willingness to see opponents as anything but enemies in a war.”

Inspired by Gerd Gigerenzer, who will be a guest in this show very soon, we close on the pitfalls of hyper-complex models in science and policy. How can we handle decision making under radical uncertainty? Which type of models help, which can lead us astray?

“I’m worried that complexity sometimes could be an alibi for confusion.”

This conversation left me both inspired and unsettled. John’s clarity on science’s flaws, paired with his hope for reform, offers a roadmap, but the stakes are high. From nutrition to pandemics, shaky science shapes our lives, and rebuilding trust demands we embrace uncertainty, not dogma. His call for dialogue over destruction is a plea we should not ignore.

Other Episodes

• Episode 116: Science and Politics, A Conversation with Prof. Jessica Weinkle
• Episode 112: Nullius in Verba — oder: Der Müll der Wissenschaft
• Episode 109: Was ist Komplexität? Ein Gespräch mit Dr. Marco Wehr
• Episode 107: How to Organise Complex Societies? A Conversation with Johan Norberg
• Episode 106: Wissenschaft als Ersatzreligion? Ein Gespräch mit  Manfred Glauninger
• Episode 103: Schwarze Schwäne in Extremistan; die Welt des Nassim Taleb, ein Gespräch mit Ralph Zlabinger
• Episode 94: Systemisches Denken und gesellschaftliche Verwundbarkeit, ein Gespräch mit Herbert Saurugg
• Episode 92: Wissen und Expertise Teil 2
• Episode 90: Unintended Consequences (Unerwartete Folgen)
• Episode 86: Climate Uncertainty and Risk, a conversation with Dr. Judith Curry
• Episode 67: Wissenschaft, Hype und Realität — ein Gespräch mit Stephan Schleim

References

• Prof. John Ioannidis at Stanford University 
• John P. A. Ioannidis, Why Most Published Research Findings Are False, PLOS Medicine (2005)
• John Ioannidis, A fiasco in the making? As the coronavirus pandemic takes hold, weare making decisions without reliable data (2020)
• John Ioannidis, The scientists who publish a paper every five days, Nature Comment (2018)
• Hanae Armitage, 5 Questions: John Ioannidis calls for more rigorous nutrition research (2018)
• John Ioannidis, How the Pandemic Is Changing Scientific Norms, Tablet Magazine (2021)
• John Ioannidis et al, Uncertainty and Inconsistency of COVID-19 Non-Pharmaceutical1Intervention Effects with Multiple Competitive Statistical Models (2025)
• John Ioannidis et al, Forecasting for COVID-19 has failed (2022)
• Gerd Gigerenzer, Transparent modeling of influenza incidence: Big data or asingle data point from psychological theory? (2022)
• Sabine Kleinert, Richard Horton, How should medical science change? Lancet Comment (2014)
• Max Perutz quotation taken from Geoffrey West, Scale, Weidenfeld & Nicolson (2017)
• John Ioannidis: Das Gewissen der Wissenschaft, Ö1 Dimensionen (2024)

Todays guest is Jessica Weinkle, Associate Professor of Public Policy at the University of North Carolina Wilmington, and Senior Fellow at The Breakthrough Institute. 

In this episode we explore a range of topics and we start with the question: What is ecomodernism, and how does The Breakthrough Institute and Jessica interpret it? 

“It's not a movement of can'ts”

Why are environmentalists selective about technology acceptance? Why do we assess  ecological impact through bodies like the IPCC and frameworks like Planetary Boundaries? Are simplified indicators of complex systems genuinely helpful or misleading? 

Is contemporary science more about appearances than substance, and do scientific journals serve more and more as advocacy platforms than fact-finding missions? How much should activism and science intersect? To what extent do our beliefs influence science, and vice versa, especially when financial interests are at play in fields like climate science? Can we trust scientific integrity when narratives are tailored for publication, like in the case of Patrick Brown?

What responsibilities do experts have when consulting in political spheres, and should they present options or advocate for specific actions?  How has research publishing turned into big business, and what does this mean for the pursuit of truth? 

“Experts should always say: here are your options A, B, C...; not: I think you should do A”

How does modeling shape global affairs? When we use models for decision-making, are we taking them too literally, or should we focus on their broader implications? 

“To take a model literally is not to take it seriously […] the models are useful to give us some ideas, but the specificity is not where we should focus.”

What's the connection between scenario building, modeling, and risk management? 

“There is an institutional and professional incentive to make big claims, to draw attention. […] That's what we get rewarded for. […] It does create an incentive to push ideas that are not necessarily the most helpful ideas for addressing public problems.”

How does the public venue affect scientists, and does the incentive to make bold claims for attention come at the cost of practical solutions? What lessons should we have learned from cases like Jan Hendrik Schön, and why haven't we? 

“There is an underappreciation for the extent to which scholarly publishing is a business, a big media business. It's not just all good moral virtue around skill and enlightenment. It's money, fame and fortune.”

Finally, are narratives about future scenarios fueling climate anxiety, and how should we address this in science communication and policy-making?

“There is a freedom in uncertainty and there is also an opportunity to create decisions that are more robust to an unpredictable future. The more that we say we are certain ... the more vulnerable we become to the uncertainty that we are pretending is not there.”

Other Episodes

• Episode 109: Was ist Komplexität? Ein Gespräch mit Dr. Marco Wehr
• Episode 107: How to Organise Complex Societies? A Conversation with Johan Norberg
• Episode 90: Unintended Consequences (Unerwartete Folgen)
• Episode 86: Climate Uncertainty and Risk, a conversation with Dr. Judith Curry
• Episode 79: Escape from Model Land, a Conversation with Dr. Erica Thompson
• Episode 76: Existentielle Risiken
• Episode 74: Apocalype Always
• Episode 70: Future of Farming, a conversation with Padraic Flood
• Episode 68: Modelle und Realität, ein Gespräch mit Dr. Andreas Windisch
• Episode 60: Wissenschaft und Umwelt — Teil 2
• Episode 59: Wissenschaft und Umwelt — Teil 1

References

• Jessica Weinkle
  • Jessica on Substack
  • Jessica at The Breakthrough Institute
  • Jessica at the Department of Public and International Affairs (UNCW)
• The Breakthrough Journal
• Planetary Boundaries (Stockholm Resilience Centre)
• Patrick T. Brown, I Left Out the Full Truth to Get My Climate Change Paper Published, The FP (2023)
• Roger Pielke Jr., What the media won't tell you about . . . hurricanes (2022)
• Roger Pielke Jr., "When scientific integrity is undermined in pursuit of financial and political gain" (2023)
• Many other excellent articles Roger Pielke on his Substack The Honest Broker
• Jessica Weinkle, Model me this (2024)
• Jessica Weinkle, How Planetary Boundaries Captured Science, Health, and Finance (2024)
• Jessica Weinkle, Bias. Undisclosed conflicts of interest are a serious problem in the climate change literature (2025)
• Marcia McNutt, The beyond-two-degree inferno, Science Editorial (2015)
• Scientific American editor quits after anti-Trump comments, Unherd (2024)
• Erica Thompson, Escape from Model Land, Basic Books (2022)

This is episode 2 with conversations from the Liberty in our Lifetime Conference. Please start with the first part; show notes and references also with episode 1.

This episode is a special one as it brings you my impressions from the Liberty in Our Lifetime Conference held in Prague from November 1 to 3. Unlike my usual format of monologues or single guest interviews, this episode features brief conversations with six presenters from the conference, split into two parts.

In this first part, I speak with Massimo Mazzone about building a blue-collar Free City in Honduras, followed by discussions with urban economist Vera Kichanova, and Tatiana Butanka, who shares insights on the Free Community of Montelibero.

The conference, which generally leans towards libertarian ideas, showcases an astounding range of initiatives aimed at enhancing liberty in society.

I explore why successful societies should embrace explorers and risk-takers, questioning whether today's fear of challenging the status quo contradicts a progressive mindset. This aligns with Tatiana Butanka's appreciation for the variety of projects that are present at this conference and Lauren Razavi's call for the need of

"revolutionary thinking with evolutionary approaches."

Part two (Episode #114) will continue with conversations with Lauren Razavi, who is building an online country for digital nomads, Grant Romundt, discussing his project on floating homes, and Peter Young from the Free Cities Foundation, reflecting on free cities and the conference's outcomes.

I emphasize the importance of experimentation in dynamic societies, suggesting that progress relies on educated experiments and unique ideas, some of which will succeed, fail, or at least inspire. The discussions explore the balance between collective action and individual liberty, questioning if modern democracies have swung too far towards government control.

Two additional remarks:  

• No financial advice is given, despite mentions of new financial instruments in some conversations.
• For full disclosure: I received a free ticket for the conference.

Other Episodes

• Episode 108: Freie Privatstädte Teil 2, ein Gespräch mit Titus Gebel
• Episode 107: How to Organise Complex Societies? A Conversation with Johan Norberg
• Episode 88: Liberalismus und Freiheitsgrade, ein Gespräch mit Prof. Christoph Möllers
• Episode 58: Verwaltung und staatliche Strukturen — ein Gespräch mit Veronika Lévesque
• Episode 77: Freie Privatstädte, ein Gespräch mit Dr. Titus Gebel
• Episode 44: Was ist Fortschritt? Ein Gespräch mit Philipp Blom

References

• Liberty in Our Lifetime Conference
• Massimo Mazzone
  • Massimo on X
  • Ciudad Morazan
• Tatiana Butanka
  • Montelibero Wiki
  • Montelibero
• Vera Kichanova
  • Vera's Homepage
  • Vera on LinkedIn
  • Vera on Facebook
  • Vera on X
• Lauren Razavi
  • Lauren Razavi, Global Natives
  • Plumia
  • Lauren on X
• Grant Romundt
  • Grant on X
  • Oceanbuilders
• Peter Young
  • Peter on LinkedIn
  • Peter on X
• Free Cities Foundation

This is again an exceptional conversation. For a long time, I looked forward to speaking with Prof. David Edgerton. He is currently a Fellow at the Wissenschaftskolleg zu Berlin and Hans Rausing Professor of the History of Science and Technology at King's College London.  He is a noted historian of the United Kingdom as well as historian of technology and science. In the latter field he is best known for the book “Shock of the Old” which has been translated into many languages.  He is also known in the UK for his commentaries on political and historical matters in the press.  He is also a Fellow of the British Academy.

I read this book some years ago, and it left quite an impression on me. We talk about technology, or rather, why the word should not be used, about progress and stagnation; what role technology plays in societal change, if we really live in an age with an unseen pace of innovation, and much more.

We start with the question of how the book title “Shock of the Old” came about. What does the term “technology” mean, how does it relate to other terms like “technium” or the German terms “Technologie” and “Technik”, and why is it a problematic term? 

“Technology is a very problematic concept, and if I would write the book again, I would not use the term. […] Technology is a concept that macerates the brain as it conflates multiple concepts.”

What is creole technology? Did we experience 50 years of unseen progress, or rather stagnation? How can we understand the reference of David Deutsch comparing the Solvay Conference 100 years ago with the current state of physics? Are we rather experiencing what Peter Kruse compares to a crab basket:

“There's always a lot of momentum in a crab basket, but on closer inspection, you realise that nothing is really moving forward.”, Peter Kruse

Can the 20th century be considered the playing out of the 19th century? What about the 21st century? Is technological change the driver of all change, or is technical change only one element of change in society? Does the old disappear? For instance, Jean-Baptiste Fressoz describes the global energy consumption in his book More and More and More.

“There has not been an energy transition, there has been a super-imposition of new techniques on old ones. […] We are living in the great age of coal.”

What is the material constitution of our world today? For example, Vaclav Smil makes it apparent, that most people have a quite biased understanding of how our world actually works.

How can change happen? Do we wish for evolution, or rather a revolution?

“The world in which we find ourselves at the start of the new millennium is littered with the debris of utopian projects.”, John Gray

Can technological promise also be a reason for avoiding change?

“Technological revolution can be a way of avoiding change. […] There will be a revolution in the future that will solve our problems. […] Relying only on innovation is a recipe for inaction.”

Do technologists tend to overpromise what their technology might deliver? For instance, the trope that this new technology will bring peace can be found over centuries.

Is maintenance an underestimated topic in out society and at universities? What role does maintenance play in our modern society in comparison to innovation? For example, Cyrus W. Field who built the first transatlantic cable between the US and UK proclaimed in an address to the American Geographical and Statistical Society in 1862

“its value can hardly be estimated to the commerce, and even to the peace, of the world.”

What is university knowledge, where does it come from, and how does it relate to knowledge of a society? How should we think about the idea of university lead innovation?

“There is a systematic overestimation of the university.”

Is there a cult of the entrepreneur? Who is actually driving change in society? Who decides about technical change? Moreover, most innovations are rejected:

“We should reject most of innovation; otherwise we are inundated with stuff.”

Are me even making regressions in society — Cory Doctorow calls it enshittification?

“We’re all living through a great enshittening, in which the services that matter to us, that we rely on, are turning into giant piles of shit. It’s frustrating. It’s demoralising. It’s even terrifying.”, Cory Doctorow

What impact will artificial intelligence have, and who controls the future? 

“Humans are in control already. The question is which human.”

References

Other Episodes

• other English episodes
• Episode 107: How to Organise Complex Societies? A Conversation with Johan Norberg
• Episode 100: Live im MQ, Was ist Wissen. Ein Gespräch mit Philipp Blom
• Episode 92: Wissen und Expertise Teil 2
• Episode 80: Wissen, Expertise und Prognose, eine Reflexion
• Episode 91: Die Heidi-Klum-Universität, ein Gespräch mit Prof. Ehrmann und Prof. Sommer
• Episode 88: Liberalismus und Freiheitsgrade, ein Gespräch mit Prof. Christoph Möllers
• Episode 71: Stagnation oder Fortschritt — eine Reflexion an der Geschichte eines Lebens
• Episode 45: Mit »Reboot« oder Rebellion aus der Krise?
• Episode 38: Eliten, ein Gespräch mit Prof. Michael Hartmann
• Episode 35: Innovation oder: Alle Existenz ist Wartung?
• Episode 18: Gespräch mit Andreas Windisch: Physik, Fortschritt oder Stagnation

Dr. David Edgerton...

• ... at Wissenschaftskolleg zu Berlin
• ... at King's College London
• ... at Centre for the History of Science, Technology and Medicine
• ... at the British Academy
• Personal Website
• ...  on X
• David Edgerton, The Shock Of The Old: Technology and Global History since 1900, Profile Books (2019)

Other References

• David Graeber, Peter Thiel, Where Did the Future Go (2020)
• Conversations with Coleman, Multiverse of Madness with David Deutsch (2023)
• Peter Kruse, next practice. Erfolgreiches Management von Instabilität. Veränderung durch Vernetzung, Gabal (2020)
• Jean-Baptiste Fressoz, More and More and More: An All-Consuming History of Energy, Allen Lane (2024)
• Vaclav Smil, How the World Really Works, Penguin (2022)
• John Gray, Black Mass, Pengui (2008)
• Ainissa Ramirez, A Wire Across the Ocean, American Scientist (2015)
• Thomas Sowell, intellectuals and Society, Basic Books (2010)
• Peter Thiel Fellowship
• Cory Doctorow, ‘Enshittification’ is coming for absolutely everything, Financial Times (2024)

This episode fits perfectly into my longer-lasting quest to understand complex societies and how to handle it. I am thrilled about the opportunity to have a conversation with Johan Norberg. The title of our conversation is: How to organise complex societies?

Johan Norberg is a bestselling author of multiple books, historian of ideas and senior fellow at the Cato Institute. I read his last two books, Open, The Story of Human Progress and The Capitalist Manifesto. Both are excellent books, I can highly recommend. We will discuss both books in the wider bracket of the challenge how to handle complex societies.

The main question we discuss is, how can we handle complex societies? Which approaches work, give people opportunity, freedom and wealth, and which do not work. The question can be inverted too: When systems are more complex, is also more control and commands needed, or the opposite?

»The more complex the society, the less it can be organised—the more complex society gets, the more simple rules we need.«

Knowledge and power behave differently, as Tom Sowell puts it:

“It's much easier to concentrate power than knowledge.”

The consequence seems to be:

“If we centralise power we loose knowledge”

We talk about the historic background of the idea of liberty, for instance John Stewart Mills On liberty, Friedrich Hayek Road to Serfdom. Did we lose our desire for liberty? The Austrian philosopher Konrad Paul Liessmann observes:

“Dass das Volk nicht herrschen kann, sondern erzogen, belehrt, bevormundet und mehr oder weniger sanft in die richtige Richtung gedrängt werden soll, ist überall spürbar. Die ubiquitäre pädagogische Sprache ist verräterisch.”

“The fact that the people cannot rule, but are to be educated, instructed, patronised and more or less gently pushed in the right direction, can be felt everywhere. The ubiquitous pedagogical language is treacherous.”

How then, should we think about liberty and responsibility? 

“There is only one basic human right, the right to do as you damn well please. And with it comes the only basic human duty, the duty to take the consequences.”, P. J. O'Rourke.

That might be an uncomfortable truth for some, though. Freedom has consequences and responsibilities! The trend of the last decades points to a different direction. Every minute detail seems to be regulated by someone who allegedly knows better:

“Large projects are essentially illegal in California and in Europe”, Elon Musk

The consequence is, as I have discussed in previous episodes, stagnation since many decades. Follow the links below to other episodes. Now, did we become an old, risk-averse, dying society? This would not be good news because: 

“With innovation comes the risk of failure”

And the uncomfortable truth is: Our desire to reduce risks might actually increase risks. 

“If we are saying that we should not accept anything until it is perfectly safe, that’s the most unsafe and risky bet we could do.”

How can we muddle out of this mess?

“Nothing comes from a committee, nothing from a single genius fully developed. Innovation comes from a process of experiments, trial and error, feedback and adaptation, changes and more people getting involved.” 

There is no such thing as an immaculate conception of a new technology.

But what about volatility? Is volatility a risk? For whom? The individual, society? Is societal risk decreasing when we reduce volatility? 

What does Johan mean by openness, and why is it Important?

“Openness for me means openness to surprises. This is the only way for societies to thrive and function long term. […] Historically, life was nasty, brutish, and short. We need new things. We need new knowledge, new technological capacity and wealth.”

So why did the industrial revolution happen in the West? What is the connection to openness? What can we learn about control in societies?

“Societies have to be decentralised not top down controlled.”

But Mervyn King discusses in his excellent book Radical Uncertainty the fact, that we cannot predict the future. What happens with innovation that we cannot predict?

“Under open institutions, people will solve more problems  than they create.”

Moreover, the opposite is not true. Not innovating does not reduce risk:

“If we would do nothing, we would also be surprised by unpredictable developments. […] We solved the problems that were existential and created better problems and level up. […] I prefer those problems to the ones that made life nasty, brutish and short.”

In Europe, the precautionary principle is in high regard. Does it work, or is it rather a complete failure of epistemology?

But what about capitalism? Has it failed us or is it the saviour? Does the Matthew principle speak against capitalism?

“Elites have an interest to protect the status quo” which is a reason why free markets were blocked in many societies. This does not speak against free markets, but rather is an argument for free markets.

Is the idea of capitalism and free markets more difficult to grasp on a psychological level? Socialist ideas sound nice (when you are in a family or small group) but they do not scale. And even worse, if you try to scale them, do they create the opposite of the desired effect? In a society, we are the kids, and we have other ideas than some authoritarian figure, and we have the right to our ideas. 

“The only way to organise a complex society of strangers with different interests and different ideas and different vantage points on the world is not to control it, but instead give them the freedom to act according to their own individual creativity and dreams.  […]  You can get rich that way, but only by enriching others.”

Moreover, the distribution problem evidently is not solved by top-down political concepts. In authoritarian systems, poverty is equally distributed, but the elites still enrich themselves. 

But is trade and economy not used as a weapon on an international scale? How does that fit together, and does that not open up massive risks when we stick to free markets?

“If goods don't cross borders, soldiers will.”

Why is diversification, important, and how to reach it? What happened in Argentina, a very timely question after the new presidency of Javier Milei.

“Argentina should be a memento mori for all of us. […] 100 years ago, Argentina was one of the richest countries of the planet. It had the future going for it”. […] If Argentina can fail, so can we, if we make the wrong decisions.”

There are countries on every continent that make rapid progress. What do they have in common?

At the end of the day, this is a hopeful message because wealth and progress can happen everywhere. Since the turn of the millennium, almost 140,000 people have been lifted out of extreme poverty every day. For more than 20 years. Where did that happen and why? What can we learn from Javier Milei?

“I am an incredible optimist once I gaze away from politics and look at society.”

How can we repay the debt to previous generations that gave us the living standards we enjoy today?

References

Other Episodes

• Episode 103: Schwarze Schwäne in Extremistan; die Welt des Nassim Taleb, ein Gespräch mit Ralph Zlabinger
• Episode 101: Live im MQ, Macht und Ohnmacht in der Wissensgesellschaft. Ein Gespräch mit John G. Haas.
• Episode 96: Ist der heutigen Welt nur mehr mit Komödie beizukommen? Ein Gespräch mit Vince Ebert
• Episode 90: Unintended Consequences (Unerwartete Folgen)
• Episode 89: The Myth of Left and Right, a Conversation with Prof. Hyrum Lewis
• Episode 77: Freie Privatstädte, ein Gespräch mit Dr. Titus Gebel
• Episode 71: Stagnation oder Fortschritt — eine Reflexion an der Geschichte eines Lebens
• Episode 70: Future of Farming, a conversation with Padraic Flood
• Episode 65: Getting Nothing Done — Teil 2
• Episode 64: Getting Nothing Done — Teil 1
• Episode 44: Was ist Fortschritt? Ein Gespräch mit Philipp Blom
• Episode 34: Die Übersetzungsbewegung, oder: wie Ideen über Zeiten, Kulturen und Sprachen wandern – Gespräch mit Prof. Rüdiger Lohlker

Johan Norberg

• Johan Norberg is Senior Fellow at the Cato Institute
• Johan Norberg on Twitter/X
• Johan Norberg on LinkedId
• Johan Norberg, Open. The Story Of Human Progress, Atlantic Books (2021)
• Johan Norberg, The Capitalist Manifesto, Atlantic Books (2023)

Literature, Videos and Links

• John Stuart Mill, On Liberty (1859)
• Friedrich von Hayek, The Road to Serfdom, Routledge (1944)
• Thomas Sowell, intellectuals and Society, Basic Books (2010)
• Johan Norberg, A Conversation with Elon Musk, The Cato Institute (2024)
• Reason TV: Nick Gillespie and Magatte Wade, Don't blame colonialism for African poverty (2024)
• Jason Hickel, The Divide – A Brief Guide to Global Inequality and its Solutions, Windmill (2018)
• Victor Davis Hanson on subsidies and tarifs (2024)
• Konrad Paul Liessmann, Lauter Lügen, Paul Zsolnay (2023)
• P. J. O'Rourke, The Liberty Manifesto; Cato Institute (1993)

Is the political left and right position changing regularly? For many years now, I have been getting more and more uneasy when pundits and journalists use the “left/right” dichotomy. In my lifetime, I have observed numerous political topics that were once at the core of “left” politics that suddenly are named “right” and vice versa.

I then came across the book with the very name “The Myth of Left and Right” and it is a terrific read. So I was very excited that one of the authors, Hyrum Lewis agreed to a conversation.

Hyrum Lewis is a professor of history at BYU-Idaho and was previously a visiting scholar at Stanford University. He received a PhD from the University of Southern California and has written for the Wall Street Journal, Quillette, RealClearPolitics, The Washington Examiner, and other national publications. His most recent book, The Myth of Left and Right (co-authored with Verlan Lewis) was published by Oxford University Press in 2023.

Moreover, this episode fits very nicely with the previous episode with Prof. Möllers on liberalism, so if you are a German speaker, please check this one out as well.

Political realities do not map to a single variable or descriptor—there is no such thing as a political monism. Are “left” and “right” just post-hoc narratives where we try to construct ideologies that are not actually there?

We observe a regular flip-flopping in history; what are prominent examples?

“There is no left and right; there are just two tribes, and what these tribes believe and stand for will change quite radically over time since there is no philosophical core uniting the tribe.”

I, personally, have a profound problem with the term “progressive”, but more generally, what do these terms even mean: progressivism, conservatism, reactionary, liberal? 

“It is a loaded and self-serving term […] what is considered progressive changes from day to day.”

“If you don't agree with every policy we believe in […] then you are obviously on the wrong side of history. You are standing against progress.”

So, are left and right not a philosophy but rather a tribe? 

Is the definition of conservatism maybe easier? There is a nice brief definition: "Conservatism is democracy of the deceased,” Roger Scruton makes the astute observation that there are so many more ways to screw up and so little ways to do right. But does this help in practice? 

“Every person on that planet wants to conserve things that are good and change things that are bad. We are all progressive, and we are all conservative. We just don't agree on what is good and what is bad.”

What are examples where positions are unclear or change over time.

“In 1903, President Theodore Roosevelt visited Yosemite and was guided by naturalist John Muir. The two men spent three memorable nights camping, first under the outstretched arms of the Grizzly Giant in the Mariposa Grove of Giant Sequoias, then in a snowstorm atop five feet of snow near Sentinel Dome, and finally in a meadow near the base of Bridalveil Fall. Their conversations and shared joy with the beauty and magnificence of Yosemite led Roosevelt to expand federal protection of Yosemite, and it inspired him to sign into existence five national parks, 18 national monuments, 55 national bird sanctuaries and wildlife refuges, and 150 national forests.”, Roosevelt, Muir, and the Grace of Place (NPR)

Teddy Roosevelt was a Republican. And here again, a “hiccup”: even though Teddy Roosevelt was a Republican, he called himself a progressive.

In reality, though, if you see someone on the street in a mask, you can predict with high certainty the other political assumptions of this person. How come? Is there now an underlying disposition, or is there not? Or is it much more a phenomenon of tribal or social conformity?

Is the left-right model, at least, useful? What can we learn from past US presidents such as Donald Trump, Bill Clinton, George W. Bush in that regard?

Is the political discourse at least more reasonable at universities and among “elites”? Or maybe even more troubled and more conforming to their very tribe?

If “normal” people are in general “moderate” on important topics (like abortion), why do major political parties play for the few on the extreme ends of the opinion spectrum?

More generally, some educated people describe themselves as “moderate” or “centrist.” Does this even mean anything, and would it be desirable?

What about “realism” vs. “utopianism”?

“Both status quo conservatives and progressive technocrats share a common element: the hostility to open-ended change, guided not by planners but by millions of experiments and trial and error. For both, the goal is stasis, it’s just that one group finds it in the past, the other one in the future.”, Virginia Postrel 

A lot of these errors are made under the more elementary mistake that we can know, predict, or foresee the future, especially when we take actions. What can we learn from Phil Tetlock and Dan Gardners forecasting studies?

“To be a true progressive, you cannot be a progressive”

“Our media does not reward granular, careful, and probabilistic analysis.”

So, is it not more significant to distinguish between authoritarian and non-authoritarian politicians or political methods?

But can we be optimistic about the future when non-tribal podcasters like Joe Rogan or Coleman Hughes have audiences that are larger than most legacy media outlets combined?

Is democracy over time the best way to deal with complex situations and challenges? Is there a value in slowness, and are we not just too impatient?

References

Other Episodes

• Episode 88: Liberalismus und Freiheitsgrade, ein Gespräch mit Prof. Christoph Möllers
• Episode 84: (Epistemische) Krisen? Ein Gespräch mit Jan David Zimmermann
• Episode 80: Wissen, Expertise und Prognose, eine Reflexion
• Episode 57: Konservativ UND Progressiv

Hyrum Lewis

• Hyrum Lewis at BYU-Idaho
• Hyrum Lewis, Verlan Lewis, The Myth of Left and Right, Oxford University Press (2022)
• Hyrum Lewis, It's Time to Retire the Political Spectrum, Quillette (2017)
• Hyrum Lews Blog

Other References

• Roger Scruton, How to be a conservative, Bloomsbury Continuum (2019)
• Johan Norberg, Open: The Story of Human Progress, Atlantic Books (2021)
• Karl Popper, The Poverty of Historicism, Routledge Classic
• Phil Tetlock, Dan Gardner, Superforecasting, Cornerstone Digital (2015)
• Tim Urban, What's Our Problem?: A Self-Help Book for Societies (2023)
• Nicholas Carr, The Shallows, Atlantic Books (2020)
• Roosevelt, Muir, and the Grace of Place
• Joe Rogan Podcast
• Coleman Hughes Podcast

Todays guest is Dr. Erica Thompson who wrote the excellent book "Escape from Model Land", which I strongly recommend for reading.

Dr. Thompson is Associate Professor of Modelling for Decision Making at UCL’s Department of Science, Technology, Engineering and Public Policy. She is also a Fellow of the London Mathematical Laboratory, where she leads the research programme on Inference from Models, and a Visiting Senior Fellow at the LSE Data Science Institute.

She is working on the appropriate application of mathematical modelling in supporting real-world decisions, including ethical and methodological questions. For instance, what is the best use of models in climate change, public health and economics. 

Making and using models in the real world is — as it turns out — quite a tricky business and in our conversation we go deep into the question: what constitutes model land and how can we escape model land to achieve good results for our society from what we learned in model land.

I covered similar topics in other podcast episodes, because this question can be tackled from a number of different perspectives. 

The first question I ask Dr. Thompson is the obvious one: What is model land?

“Nobody actually cares at all about what happens in your model. […] unless you make a claim that what happens within that model land has some relationship to what happens in the real world. So, how to transfer your judgement about the model to the judgement about the real world, is the key question?”

What does Steven Wolfram mean with irreducibility of nature? Why do we have to treat different types of models differently?

What is the difference between interpolation and extrapolation, and why is this crucially important? Many models of complex systems incorporate significant amounts of expert judgement, especially when models are extrapolating. How should we deal with such models?

“All of these decisions about model construction imply value judgements about what we think to be important.”

Value judgements per se are not the problem — but are they shared by the people affected by the model? How did you get to those judegements? Are the transparent enough? Do the decision makers know and agree with these judgements?

Under what conditions can we assess the reliability of a model? In which category do models that are discussed in public fall, for instance climate models? What are the butterfly and hawkmoth effect? What is the difference between data driven vs. “expert driven” models and what role does data quality play in practice?

Most models also are partial models. What is incorporated in a model? What is left out? What conclusions are we allowed to draw from complex models? Do they highly successful data driven models distort our expections in the more assumption driven ones?

“The model is then very much part of the story. It is not just a prediction engine.”

There are models that influence the world and the world feeds back opposed to models that “just” describe the world, and performative models that actually create the reality they describe and counter-performative models. Why is it important to distinguish among these different types? 

“Those [counter-performative models] were not made with the aim to be accurate models and correctly predicting the future. They were made with the aim of showing what could happen if we didn't action which would then avoid these worst case scenarios.”

What is the difference between a (conditional or unconditional) prediction and a scenario?

Models are tools and cannot replace judgement. But did we use these tools accordingly? Or did models in the recent past (e.g. Covid) inflict more harm than good on our society?

“This is exactly what models are for—to serve as working hypotheses for further research.”, Ludwig von Bertalanffy

and

“Build a society that is resistant to model errors”, Nassim Taleb

Is this true?

Models as narrative generating devices and communication tools and collective thinking — do we want that? Under what conditions — like flatten the curve? And, how to avoid group think and be captured by models?

“Plans are worthless but planning is everything”, Dwight D. Eisenhower
“Kein Plan überlebt die erste Feindberührung”, Helmuth Graf von Moltke

So, there is a significant amount of expert judgement in building models, but do people know that and which expert do we trust?

“Trust is a social process and expertise is socially determined. […]
You must follow the science is saying you must agree with my value judgements.[…]

A decision can never be science based.”

Thus, science is never value free.

Finally we talk about regulation in complex systems and how those relate to models, the long and short term perspectives and what skin in the game means. Is Niall Ferguson right when he says:

 “Surely, once we have written a regulation for every possible misdeed, then good behaviour will ensue. This is just an amazing illustration of our ability as  human beeings to keep doing the wrong thing in the face of all experience. […] the big players are actually protected by complex regulation. […] 

Regulation is the disease of which it pretends to be the cure.”

Then, how should we regulate complex systems? Should every politician be a scientist in the Platonic sense?

»Ultimately the definition of an expert is somebody who's judegements you are willing to accept as your own.«

References

Other Episodes

• Episode 68: Modelle und Realität, ein Gespräch mit Dr. Andreas Windisch
• Episode 67: Wissenschaft, Hype und Realität — ein Gespräch mit Stephan Schleim
• Episode 53: Data Science und Machine Learning, Hype und Realität — Teil 1
• Episode 54: Data Science und Machine Learning, Hype und Realität — Teil 2
• Episode 39: Follow the Science?
• Episode 37: Probleme und Lösungen
• Episode 2: Was wissen wir?

• Personal Website of Dr. Thompson
• UCL’s Department of Science, Technology, Engineering and Public Policy
• London Mathematical Laboratory
• LSE Data Science Institute

Other References

• Erica Thompson, Escape from Model Land, Basic Books (2022)
• Lex Fridman #376 in conversation with Steven Wolfram (2023)
• Ludwig von Bertalanffy, General Systems Theory (1969)
• Cathy O’Neil, Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy, Penguin (2017)
• Niall Ferguson on Regulation in conversation with John Anderson (2023)