John Maynard Keynes Podcasts

  • Hello Interactors,

    The social sciences sometimes unfairly get a bad wrap for being a ‘soft science’. But are they? In pursuit of a better understanding the role uncertainty plays in economic analysis, I stumbled across some research that ties John Maynard Keynes’s embrace of uncertainty with a resolute defense of the ‘soft sciences’ by one of the heroes of the ‘hard sciences.’ And you thought physics was hard.

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    Now let’s go…

    CYBERSAIL

    “The hard sciences are successful because they deal with the soft problems; the soft sciences are struggling because they deal with the hard problems.”

    This quote is by the groundbreaking Austrian American polymath, Heinz von Foerster from his essays on information processing and cognition. He went on to state:

    “If a system is too complex to be understood it is broken up into smaller pieces. If they, in turn, are still too complex, they are broken up into even smaller pieces, and so on, until the pieces are so small that at least one piece can be understood.”

    This strategy, he’s observed, has proven successful in the “hard sciences” like mathematics, physics, and computer science but poses challenges to those in the “soft sciences” like economics, sociology, psychology, linguistics, anthropology, and others.

    He continues,

    “If [social scientists] reduce the complexity of the system of their interest, i.e., society, psyche, culture, language, etc., by breaking it up into smaller parts for further inspection they would soon no longer be able to claim that they are dealing with the original system of their choice.

    This is so, because these scientists are dealing with essentially nonlinear systems whose salient features are represented by the interactions between whatever one may call their “parts” whose properties in isolation add little, if anything, to the understanding of the workings of these systems when each is taken as a whole.

    Consequently, if he wishes to remain in the field of his choice, the scientist who works in the soft sciences is faced with a formidable problem: he cannot afford to lose sight of the full complexity of his system, on the other hand it becomes more and more urgent that his problems be solved.”

    Von Foerster studied physics in Austria and Poland and moved to the United States in 1949. He started his career in 1951 as a professor of electrical engineering at the University of Illinois. In 1958 he received grant funding from various federal government agencies to start a Biological Computer Laboratory.

    Von Foerster understood the cognitive process humans use to break down large complex problems into smaller discrete linear steps. With the advent of computers, they then typed those instructions into punch cards and fed them into the computer to process. A linear process of which humans and computers can both do. He and his lab then devised a way for a computer to do something humans cannot – conduct multiple calculations at the same time by breaking them into smaller and smaller pieces “until the pieces are so small that at least one piece can be understood.” With that they invented the world’s first parallel processor.

    While von Foerster helped to bring about a machine that could do what a human could not, they also discovered what a human can do that a machine cannot. Indeed, a parallel computer can break down and execute calculations across a network of instructions, but it can’t take in additional input from its environment and decide to adjust course depending on the nature of the results. It operates in a closed system with the information it has been given and with limited input.

    I like the metaphor of sailing to better understand this. When I’m at the tiller of a sailboat steering with a course in mind, I must continually monitor the environment (i.e. wind speed, direction, tides, currents, ripples, waves), the sails (angles, pressures, sail shape, obstructions), the crew (safety, comfort, skill, attitude, joy, fear, anxiety) and the course and speed of the boat (too fast, too slow, tack, jibe, steer). I am using all my senses which continually input information as conditions change. My brain is making calculations and judgements resulting in decisions that in turn impact the conditions. For example, a sudden turn and the sails will fail, the water under the boat will be redirected, air and water pressure gradients will shift, and a crew member may fall or go overboard. All these shifts in conditions in turn impact my subsequent calculations and decisions instant by instant. It’s a persistent feedback loop of information created by human interactions with the boat, the crew, and with nature.

    A computer cannot yet steer as a human would in such conditions. They lack the necessary level of sensory input from changing environmental conditions as well as judgement and control over the information these senses provide. The study of the information derived from these complex phenomena derives its name from the Greek word for “navigator”: κυβερνήτης (kubernḗtēs), or as it has come to be called – Cybernetics. How we got from ‘kuber’ to ‘cyber’ I’m not sure, but I have a hunch that is about to be revealed.

    KEYNESIAN BRAIN CHAIN

    One of the founders of Cybernetics in the 1940s, Norbert Weiner, defined it as “the entire field of control and communication theory, whether in the machine or in the animal.” Other founders said it is the study of “circular causal and feedback mechanisms in biological and social systems." Another member of the founding group, the influential cultural anthropologist Margaret Mead, said it’s "a form of cross-disciplinary thought which made it possible for members of many disciplines to communicate with each other easily in a language which all could understand."

    Von Foerster’s seminars in Cybernetics grew to be very popular at the University of Illinois in the 1960s and 70s. But these early adopters were not the first to use this term to describe complex social information exchanges creating causal feedback loops. In 1834 the French mathematician, inventor of the telegraph, and namesake of the electrical current measurement Amp, André-Marie Ampère, used the term cybernétique to describe the “the art of governing or the science of government.” Perhaps that’s how we got from ‘kuber’ to ‘cyber’.

    Either way, whether it’s political science, economics, or other social sciences of so-called “soft sciences” these early cross-discipline thinkers felt the urge to find ways to solve hard problems. Problems so complex they become impossible to deal with or track ­– they become intractable. One economics professor emeritus out of the University of Versailles Saint-Quentin-en-Yvelines, Robert Delorme, encountered these intractable problems in his work. He has since sought ways to establish a framework to deal with such problems that draws on the work of von Foerster. But also, on someone we mentioned last week, the famous British economist John Maynard Keynes.

    Delorme was studying institutional patterns in public spending between Great Britain and France over long time periods. This yielded a great deal of quantitative data, but also qualitative data including behavioral differences between how governments and markets interacted with each other and within each country. Delorme also studied traffic fatality data between the two countries and hit the same challenge. While there were mounds of quantitative data, the qualitative data was quite specific to the country, their driving cultures, the individual accident circumstances, and the driver’s individual behavior. In trying to break these complex problems down into smaller and smaller pieces, he hit the dilemma von Forester spoke of. The closer he got understanding the massive mound of data in front of him, the further from his initial research economic question he got.

    To better model the uncertainty that culminated from behaviors and interactions in the system Delorme turned to the tools of complexity economics. He considered real-world simulation tools like complex adaptive systems (CAS), agent-based computational economics (ACE), agent-based models (ABM), and agent-based simulation (ABS). But he realized this tool-first approach reminded him of the orthodox, or ‘classical’ style of economic inquiry Keynes was critical of. While he recognized these tools were necessary and helpful, they were insufficient at explaining the complexity that arises out of the events in “the real world”.

    Delorme quotes Keynes from his 1936 book, The General Theory of Employment, Interest, and Money where he recognizes Keynes’s own need to break complex problems into smaller and smaller pieces while still staying true to the actual problem. Keynes acknowledged, “the extreme complexity of the actual course of events…” He then reveals the need to break the problem down into “less intractable material upon which to work…” to offer understanding “to actual phenomena of the economic system (…) in which we live…”

    According to Delorme, Keynes, his economic philosophy, approach, and writings have been criticized over the years for lacking any kind of formalization of the methodologies he used to arrive at his conclusions and theories. So, Delorme did the work to comb through his writing to uncover an array of consistent patterns and methodological approaches which he’s patched back together and formalized.

    He found that Keynes, like a helmsman of a boat, adapted and adjusted his approach depending on the complexity of the subject matter provided by the economic environment. When faced with intractable problems, he applied a set of principles and priorities Delorme found useful in his own intractable problems. The priority, he found, was to take a ‘problem first’ approach by confronting the reality of the world rather than assuming the perfect conditions of a mythical rational world common in traditional economics.

    Again, using sailing as a metaphor, imagine the compass showing you’re heading north toward your desired destination, but the wind is to your face and slowing you down. It’s time to decide and act in response to the environmental conditions. Disregard the tool for now, angle the boat east or west, fill the sails, and zig zag your way toward your northerly goal while intermittently returning to the tool, the compass.

    What Delorme found next was Keynes’s embrace of uncertainty. Instead of finding comfort in atomizing and categorizing to better assess risk, Keynes found comfort in acknowledging the intricacies of the organic interdependence that comes with interactions within and among irrational people and uncertain systems and environments. He rejected the ‘either-or’ of dualism and embraced the ‘both-and’ open-endedness of uncertainty. In other words, when there is a sudden shift in wind direction, the helmsperson can’t either ram the tiller to one side or adjust the sails. They must both move the tiller and adjust sails.

    REPLICATE TO INVESTIGATE

    To better deal with complex phenomena, and to further form his framework for how to deal with them, Delorme also found inspiration in the work of one of my inspirations, Herb Simon.

    What Delorme borrowed from Simon was a way “in which the subject must gather information of various kinds and process it in different ways in order to arrive at a reasonable course of action, a solution to the problem.” This process, as characterized by the cybernetic loop, takes an input by gathering information and assesses and decides on a reasonable course of action. This solution in turn causes a reaction in the system creating an output that is then sensed and returned into the loop as input. This notion of a looping system made of simple rules to generate variations of itself is reminiscent of the work by a third inspiration for Delorme, John von Neumann.

    Von Neumann was a Hungarian American polymath who made significant contributions to mathematics, physics, economics, and computer science. He developed the mathematical models behind game theory, invented the merge-sort algorithm in computer science, and was the first known person to create self-replicating cellular automata. And for all you grid paper doodlers out there, he first did it first on grid paper with a pencil. Now these simple processes are done on the computer.

    By assigning very simple ‘black and white’ rules to cells in a grid (for example, make a cell white or black based on whether neighboring cells are black or white) one can produce surprisingly complex animate and self-replicating behavior. One popular example is Gosper’s gliding gun. It features two simple cellular arrows that traverse back and forth left to right across the screen on a shared path. When they collide, they produce animated smaller and simpler cellular offspring, an automaton, that rotate as they animate themselves diagonally to the lower right corner of the page or screen.

    Delorme noticed von Neumann used this self-replication phenomena to describe a fundamental property of complex systems. If the complexity of automata is under a certain threshold of complexity, the automaton it produces will be less complex or degenerative – as is the case with Gosper’s arrow. However, if the threshold of complexity is exceeded it can over produce. Or, in the words of von Neumann, “if properly arranged, can become explosive.”

    What Delorme’s research suggests, I think, is that to address complex intractable economic problems one must devise a looping recursive system of inquiry that self-replicates output intended to affect the next decision by the researcher. This makes the researcher both an observer and a participant in the search for solutions. The trick is to maintain a certain threshold of complexity such that the output doesn’t, again, become overwhelming or explosive.

    In other words, instead of pointing tools at a mound of data in attempts to describe a static snapshot of what is in the world, create a circular participatory system that recursively produces something that affects how one might adjust what it produces in near real time.

    As Delorme writes, “Complexity is not inherent to reality but to our knowledge of reality, it is derivative rather than inherent.” He then quotes science philosopher Lee McIntyre, who offers, “complexity exists ‘not merely as a feature of the world, but as a feature of our attempts to understand the world.”

    I’m not sure what this kind of system looks like practically speaking, but I think the software tool developed by the economist Steve Keen, Minsky, is a start. Keen created this dynamic simulation software to model approaches to macroeconomics after he predicted the 2008 financial crisis. He hopes to entice people away from the static, equilibrium-fixated style of economics taught and practiced today.

    The amount of data available to dynamically assess economic outcomes involving complex human behavior, human-made systems, and the natural world continues to push thresholds of complexity. We are creators, observers, and interactors of information in our own self-perpetuating recursive constructions of reality. But as von Forester suggested, even as we break down complex problems into parts, we can’t lose sight of the whole.

    That reminds me of a quote from another ‘von’ the linguist and philosopher Wilhelm von Humboldt – the younger brother of the famous naturalist Alexander von Humboldt. In 1788 he wrote,

    "Nothing stands isolated in nature, for everything is combined, everything forms a whole, but with a thousand different and manifold sides. The researcher must first decompose and look at each part singly and for itself and then consider it as a part of a whole. But here, as often happens, he cannot stop. He has to combine them together again, re-create the whole as it earlier appeared before his eyes."



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  • Få fenomen har blivit så omdiskuterade de senaste åren som liberalismens kris. I den här essän funderar författaren Per Wirtén på om utvägen ur krisen kanske ligger dold i liberalismens historia.

    Lyssna på alla avsnitt i Sveriges Radio Play.

    ESSÄ: Detta är en text där skribenten reflekterar över ett ämne eller ett verk. Åsikter som uttrycks är skribentens egna.

    De senaste trettio åren har varit liberalismens epok. Den har vunnit på alla fronter. Men om man ska vara mer korrekt, och det är viktigt i sammanhanget, så är det en specifik riktning inom den annars vittförgrenade liberalismen som dominerat, den så kallade nyliberalismen. Huvuddragen är vid det här laget välbekanta: privatiseringar, fria självreglerande marknader, individuell valfrihet i alla lägen och en krympande statsmakt.

    Men sedan några år har allt fler noterat att det liberala projektet drabbats av osäkerhet och förvirring. Liberalismens kris har blivit ett etablerat begrepp. Det som för trettio år sedan verkade så nytt och lovande uppfattas nu av många som slitet och tilltufsat. Först kom finanskraschen 2008 och sedan eurokrisen. Men det är så mycket mer som bidragit till diskussionerna om en liberalismens kris: envist hög arbetslöshet, växande inkomstskillnader och en utbredd känsla av att det gemensamma – själva samhällsprojektet – upplösts till förmån för ett race där de enskilda vinnarna tar allt.

    I början av 1900-talet stod liberalismen inför en lika djup kris som nu. Den ansågs uttjänt och omodern, svarslös inför dåtidens uppflammande klasskonflikter. Det utlöste en omtolkning av det liberala uppdraget på båda sidor om Atlanten.

    I USA skedde det genom den så kallade progressiva rörelsen där intellektuella och politiker gemensamt drog slutsatsen att i det storindustriella samhället behövde de liberala frihetsidealen garanteras och försvaras av en stark stat, ett nytt slags fördelningspolitik med progressiva skatter och en arbetslagstiftning som garanterade arbetarna viktiga rättigheter. Liberalerna lämnade helt enkelt sina tidigare dominerande doktriner om en minimal stat, fria marknader och begränsad rösträtt.

    Kanske kommer de som i framtiden ser tillbaka på vår tids samhällsomvandlingar ta fasta på de lika stora förändringar som skakade världen vid det förra sekelskiftet. Kanske kommer de att leta samband och undersöka skillnader mellan de utmaningar liberalismens idéer stod inför i början av 1900-talet och den hårda kritik den möter i dag. Då kom utmaningen från socialismen och arbetarrörelsen. Nu kommer den från ett helt annat håll: från den hårda konservatismens återkomst, från nationalismen och från auktoritära politiker.

    En del liberaler vill inte se några som helst problem i den förda politiken. De vill möta utmaningen med ännu fler avregleringar och skattesänkningar. Andra anpassar sig efter den nya konservativa nationalismens vindriktningar. Men inget av de båda vägvalen verkar kunna häva den liberala krisen.

    Möjligen är det något helt annat som behövs: en kritisk omorientering inifrån det liberala idéarvet, i likhet med den som skedde för drygt hundra år sedan. Det finns en pågående internationell debatt i den riktningen. För några år sedan drog till exempel den amerikanska journalisten James Traub en besk slutsats i boken "What was Liberalism?" om att det är liberalismen, så som den utformats under de här trettio åren, som berett vägen för den illiberala revolten. Som passionerad liberal menade Traub att räddningen ligger gömd i de liberala idéernas mångfacetterade historia.

    Liberalismen är ju som ett stort hus med många rum. Där har det alltid funnits konflikter och strider om hur den ska tolkas. Om de individuella friheterna är viktigare än demokratins majoritetsstyre. Om principen om fria marknader ska vara starkare än politikens försök att tämja dem.

    Nyliberalerna har i trettio år haft tolkningsmonopol på vad liberalism egentligen är. Men för att komma ur sin kris behöver liberaler antagligen gå tillbaka in i sitt eget hus, för att identifiera andra röster, andra texter och historiska erfarenheter.

    Ett viktigt bidrag finns i historikern Helena Rosenblatts uppmärksammade "The Lost History of Liberalism" där hon vänder sig till 1800-talets franska och tyska liberaler för en sådan omorientering. Hon framhåller till exempel de liberala pionjärerna Benjamin Constant och Madame de Staël. Hon visar hur de förkastade det individuella egenintresset – som de kallade egoism – till förmån för allmänintresset och det gemensamma ansvaret.

    Titeln på Rosenblatts bok är en riktningsgivare för nyorienteringen: Liberalismens förlorade historia. Något har tappats bort, eller i själva verket målmedvetet trängts undan, som nu behöver återfinnas. Det gäller framtiden.

    En liknande utgrävning gör holländska Annelien De Dijn i sin otroligt rika idéhistoria "Freedom" om det liberala frihetsbegreppet. Hon följer liberalernas långa brottning med idén om ett demokratiskt folkstyre, som de länge hade förvånansvärt svårt att acceptera. Hon ställer många frågor om vad begreppet liberal demokrati kan vara, men inte alltid varit.

    Så vad finns det då för liberala värderingar som kan omvärderas, men på fortsatt liberal grund? Poängen är inte att liberalismen ska förkastas utan återigen omtolkas i ny riktning – ungefär som skedde i början av 1900-talet.

    Den första punkten är det meritokratiska idealet om att ge alla samma start i livet, för att sedan acceptera uppkomna ojämlikheter. Detta i motsats till socialdemokratin som kontinuerligt vill rätta till ojämlikheter under livscykeln. Men utan effektiva arvsskatter och enhetlig skola har ju den meritokratiska modellen tömts på reellt innehåll. I stället framträder nu en ny aristokrati som vilar på ärvda förmögenheter.

    Den andra punkten är den liberala antropologin, eller människosynen, där människor ses som helt självständiga individer på en valfrihetsmarknad utan några ömsesidiga beroenden. Det leder till just det samhälleliga sönderfall som den liberala pionjären Benjamin Constant befarade för över 200 år sedan. 1800-talets franska liberaler utvecklade därför en idé om mänsklig individualitet i stället för den antropologiska individualismen som de uppfattade som ren egoism. Liberaler behöver helt enkelt återskapa den ofta bortglömda liberala tanken om det gemsamma ansvaret för ett samhällsbygge, för det allmänna.

    Den tredje punkten är en uppgörelse med föreställningen om fria och självreglerande marknader. Där finns ju en lång och rik liberal tradition om en politiskt och socialt inbäddad kapitalism, med till exempel Karl Polanyi, Franklin D Roosevelt och John Maynard Keynes som framträdande representanter.

    Det är några exempel på hur vägen ut ur liberalismens kris kan ligga i en inventering och utvärdering av dess historia. Nycklarna till en möjlig ny liberal guldålder ligger i sådant fall gömda bland gamla historiska erfarenheter.

    En sådan kritisk omorientering behöver göras av just liberaler med sikte på att förändra den liberala politiken. Vi andra kan inskärpa betydelsen av en sådan, till exempel genom att peka på den liberala idéhistoriens rika möjligheter, men inte göra själva jobbet. Liberalismens kris angår alla, men den kan nog bara lösas av liberalerna själva.

    Per Wirtén, författare

    Litteratur

    Helena Rosenblatt: The Lost History of Liberalism: From Ancient Rome to the Twenty-First Century. Princeton University Press, 2018.

    Annelien de Dijn: Freedom: An Unruly History. Harvard University Press, 2020.

    James Traub: What Was Liberalism? The Past, Present, and Promise of a Noble Idea. Basic Books, 2019.

    Bilden

    Sex förgrundsfigurer ur liberalismens historia:

    James Madison: https://en.wikipedia.org/wiki/File:James_Madison(cropped)(c).jpg

    Madame de Staël: https://en.wikipedia.org/wiki/File:Marie_El%C3%A9onore_Godefroid_-_Portrait_of_Mme_de_Sta%C3%ABl.jpg

    Adam Smith: https://commons.wikimedia.org/wiki/File:Adam_Smith_The_Muir_portrait.jpg

    John Stuart Mill: https://en.wikipedia.org/wiki/File:Stuart_Mill_G_F_Watts.jpg

    John Locke: https://en.wikipedia.org/wiki/File:John_Locke.jpg

    Mary Wollstonecraft: https://en.wikipedia.org/wiki/File:Mary_Wollstonecraft_by_John_Opie_(c._1797).jpg

  • Han satt med vid ledarnas förhandlingsbord efter båda världskrigen och revolutionerade nationalekonomin under depressionen på 30-talet. Hela tiden med ett tydligt mål i sikte: En fredlig värld där alla har tid att spela piano och måla tavlor. Kapitalet tar sig äntligen an nationalekonomen John Maynard Keynes.

    Medverkande: Zachary D. Carter, författare till "The Price of peace: Money, Domecracy and the Life och John Maynard Keynes"

  • Han satt med vid ledarnas förhandlingsbord efter båda världskrigen och revolutionerade nationalekonomin under depressionen på 30-talet. Hela tiden med ett tydligt mål i sikte: En fredlig värld där alla har tid att spela piano och måla tavlor. Kapitalet tar sig äntligen an nationalekonomen John Maynard Keynes.

    Medverkande: Zachary D. Carter, författare till "The Price of peace: Money, Domecracy and the Life och John Maynard Keynes"

  • Tänkarna och idéerna är:
    (1) Adam Smith - Osynliga handen + Specialisering
    (2) David Ricardo - Komparativa fördelar
    (3) Frederic Bastiat - Alternativkostnad
    (4) Ronald Coase - Theory of the Firm
    (5) Joseph Schumpeter - Creative Destruction
    (6) John Maynard Keynes - Keynesianism
    (7) Friedrich von Hayek - Price Signalling
    (8) John Kenneth Galbraith - Febezzlement
    (9) Milton Friedman - Fria Marknaden

    Gör en tidig ansökan till Finanskursen Årskull 4 (Start i september) om du vill lära dig värdera aktiebolag: www.Finanskursen.se