Social physics or how ideas flow from my head to your head

social physics

[Français]

Last month I finished an amazing book called “Social Physics | how ideas spread-the lessons from a new science” that describes different research projects trying to understand how human behavior works thanks to a new data-driven (Big Data) science.

[Le mois dernier, j’ai terminé de lire en livre très inspirant appelé « La physique sociale | comment les idées se propagent-leçons d’une nouvelle science » qui décrit différents projets de recherche qui tentent de comprendre comment le comportement humain fonctionne grâce à une nouvelle science basée sur de données quantifiables (Big Data).]

The “social physics” concept comes from sociology, specifically from Auguste Compte and others who in the 19th century tried to explain social reality with the development of universal laws. Alex Pentland along with an interdisciplinary team of scientists, doctoral and post doctoral students and engineers, borrowed the concept to develop a new data-driven mathematical model of social behavior.

[Le concept de « physique sociale » vient de la sociologie, particulièrement d’Auguste Comte et autres qui, au 19ème siècle ont tenté d’expliquer la réalité sociale avec le développement de lois universelles. Alex Pentland avec une équipe interdisciplinaire de chercheurs, des doctorants et post-doctorants et des ingénieurs, a emprunté le concept de « physique sociale » pour développer un nouveau modèle mathématique du comportement social, qui utilise des données massives (Big Data).]

social interactions

What Pentland and his team are trying to do, is to quantify what previously was not quantifiable (the flow of ideas that determine human behavior). The most important part of the book is that the overall structure of a given network of interaction, rather than the content that people exchange through that network, determines the quality of what Pentland calls “Idea Flow”: the way that behaviors and beliefs spread across a web of interpersonal relationships.

[Ce que Pentland et son équipe essaient de faire, c’est de quantifier ce qui était auparavant impossible de quantifier (la circulation d’idées qui déterminent le comportement humain). La partie la plus importante du livre montre que la structure globale d’un réseau d’interaction, plutôt que le contenu que les gens échangent par le biais de ce réseau, détermine la qualité de ce que Pentland appelle « flux d’idées » : la façon dont les comportements et les croyances ou convictions sont répartis dans un réseau de relations interpersonnelles.]

In this context, the experiments of the scientific research shows that there are network structures that are more conducive than others to the emergence of innovative ideas (inventive ideas in my opinion). Many ideas in which Pentlands theory is based are not new, what is amazing about “social physics” is the volume and the diversity of the data used in the experiments, as well as the mathematical model proposed to quantify these data and predict human behavior, this is an example of the potential of Big Data that we didn’t have before in social sciences.

[Dans ce contexte, les expériences de recherche scientifique illustrées dans le livre montrent qu’il existe des structures de réseau qui sont plus propices que d’autres à l’émergence d’idées innovants (inventives à mon avis). Beaucoup d’idées dans lesquelles la théorie de Pentland se fonde ne sont pas nouvelles, ce qui est étonnant au sujet de la théorie de la « physique sociale » développé par Pentland et son équipe, est le volume et la diversité des données utilisées dans les expériences, ainsi que le modèle mathématique proposé pour quantifier ces données et pour prédire le comportement humain, ceci est un exemple du potentiel du Big Data dans les sciences sociales, potentiel que nous ne disposions pas auparavant.]

The book, the research, the experiments, the data publicly available and the theory were very inspiring for me, so I’m developing a new hypothesis based on Pentlands theory where I introduce the variables of collaboration, cooperation and invention and that I will explain in my next post where I will be also explaining the project in which I’m working on to test this hypothesis: the REMASCO project.

[Le livre, la recherche, les expériences, les données (qui sont publiques) et la théorie m’ont beaucoup inspiré, donc je suis en train de développer une nouvelle hypothèse basée sur la théorie de Pentland où j’utilise les variables de la collaboration, de la coopération, ainsi que de l’invention, hypothèse que je vais expliquer plus en détail dans mon prochain post où j’expliquerai également le projet dans lequel je travaille actuellement : le projet REMASCO.]

My experience at the SenseCamp Berlin 2016

sensecampBerlin

[Français]

I just came back from a fantastic trip to Berlin. Among other things, I went to a SenseCamp organized by MakeSense. Everything started at a sunny Friday noon at the Evangelische Schule Berlin Mitte, a place that was like a co-working space inside a school. A SenseCamp is an unconference for social entrepreneurship and innovation. The main objective was to bring together the global MakeSense network and Berlin social startup ecosystem to boost action and engagement. You can feel a little bit of the experience in this video.

[Je viens de rentrer d’un voyage fantastique à Berlin. Entre autres choses, je suis allé à un SenseCamp organisé par MakeSense. Tout a commencé un ensoleillé vendredi midi au Evangelische Schule Berlin Mitte, un endroit qui était comme un espace de co-working à l’intérieur d’une école. Un SenseCamp est un unconference pour l’entrepreneuriat social et l’innovation. L’objectif principal était de réunir le réseau MakeSense mondial et l’écosystème des startups sociales de Berlin  pour stimuler l’action et l’engagement. Vous pouvez vivre un peu l’expérience dans cette vidéo.]

boders

The theme for this year was “Questioning Borders”, like those that we create in maps, but also and specially those that we create in our minds in different ways. That Friday, I arrived without knowing anyone, not even one person, and ready to exchange new ideas, to see if I could help in some initiatives and specially to learn in the process.

[Le thème de cette année était “Questioning Boderders” (Questionner les frontières), comme ceux que nous créons dans les cartes, mais aussi et surtout ceux que nous créons de différentes manières dans nos esprits. Ce vendredi, je suis arrivé sans connaître personne, pas même une seule personne, et prêt à échanger de nouvelles idées, pour voir si je pouvais aider dans certaines initiatives et surtout pour apprendre de l’expérience.]

At the end, they were 3 days full of good energy and amazing people from probably more than 20 nationalities, on Friday we made a SenseTour to know more about the initiatives that involved refugees that left me thinking how important is design in every aspect of our lives. Saturday was the main SenseCamp day, with a lot of different workshops in different fields, with a lot of participation, projects, ideas, and the “zero waste” premise, ending the day with a DiscoSoup and an amazing party. On Sunday we received more good energies from our interactions, yoga, healthy food and the last workshops.

[A la fin, on avait passé 3 jours pleins de bonnes énergies avec de gens extraordinaires de probablement plus de 20 nationalités. Le vendredi, nous avons fait un SenseTour pour connaître plus sur les initiatives impliquant les réfugiés, cette expérience m’avait laissé dans l’esprit l’importance que le design joue dans tous les aspects de nos vies. Samedi était le jour principal du SenseCamp, avec des ateliers dans différents domaines, des projets et des idées, et avec la prémisse de “zero waste” (zéro déchet), terminant la journée avec une DiscoSoup et une super fête. Le dimanche, c’était une journée active mais aussi de récupération où nous avons reçu encore de bonnes énergies grâce à nos interactions, au yoga, avec un déjeuner délicieux et bonne santé et grâce aux derniers ateliers.]

workshops

I’m back in France full of good vibes, ideas, insights and specially new and amazing friends from all over the world, and now more than ever I’m convinced that we need to start a global education system that rethinks how people collaborate and interact to invent new solutions for this new and transformed creative world post industrial era, for me this is the main tool that we have as citizens of the world to respond to the great challenges that we are facing today like terrorism, discrimination, pollution, waste and specially to understand the equilibrium of the global and local economies of the present and the future.

[Je suis de retour en France avec plein des ondes positives, des idées et spécialement de super nouveaux amis de différents pays du monde, et maintenant plus que jamais, je suis convaincu que nous devons commencer à concevoir et créer un système d’éducation global pour repenser la façon dont les êtres humains collaborent et interagissent pour inventer de nouvelles solutions aux challenges de cette nouvelle et créative ère post-industrielle, pour moi cela est le principal outil que nous avons dans les mains en tant que citoyens du monde pour répondre aux grands défis auxquels nous sommes confrontés aujourd’hui, comme le terrorisme, la discrimination, la pollution, les déchets et surtout pour comprendre l’équilibre des économies globales et locales du présent et du futur.]

Thinking about humanity in the era of exponential technological growth inside the secrets of the “Amphithéâtre Richelieu”

Sorbonne

[Français]

Last Saturday I assisted at the TEDx organized by the Sorbonne University in Paris, the subject was something like “Humanity E-real”. I appreciate when universities organize this type of events to exchange and debate around new ideas.

[Samedi dernier j’ai assisté au TEDx organisé par l’Université de la Sorbonne à Paris, le sujet était « l’humanité e-réelle ». J’ai apprécié le fait que cet événement conçu pour échanger et débattre autour de nouvelles idées sur le lien entre l’humain et la technologie était organisé par les étudiants de la Sorbonne.]

Amphi_Richelieu

I can summarize the event and the exchanges as the search for an equilibrium between Human and Technology, trying to unravel the secrets to find this equilibrium towards the future of humanity. It was interesting to think about this in the amphitheater Richelieu, place which has the potential to transport people in time, because this place is exactly the same as it was in 1901.

[Si je dois résumer l’événement, tous les échanges ont été autour de comment chercher un équilibre entre l’humanité et la technologie, en essayant de percer les secrets de trouver cet équilibre vers l’avenir. Il est intéressant de réfléchir à ce sujet dans un endroit comme l’amphithéâtre Richelieu, lieu qui a le potentiel de faire voyager les gens dans le temps, parce que aujourd’hui, cet amphithéâtre est exactement le même comme en 1901.]

At the end of the event, I still keep in my head the phrase of Primavera de Filippi during the “Échappée 2016“, that was something like: instead of talking about the Internet of Things, we have to start to talk about the Internet of Humans.

[A la fin de l’événement, je garde toujours dans ma tête la phrase de Primavera de Filippi au cours de « l’échappée 2016 » : au lieu de parler de l’Internet des objets, nous devons commencer à parler de l’Internet des Humains.]

In their essence, the last 2 events that I assisted were related, that’s why I want to share a summary with a short hand of each intervention from 2 weeks ago. Here you can see the speakers of the TEDxSorbonne.

[Dans leur essence, les 2 derniers événements que j’assisté étaient liées, voilà pourquoi je voudrais partager un résumé avec une courte phrase de chaque intervenant de l’événement d’il y a 2 semaines. Ici vous pouvez en savoir plus sur les intervenants de la TEDxSorbonne.]

Speakers “l’échappée 2016”:

[Intervenants « l’échappée 2016 »]

intervenants_1intervenants_2intervenants_3intervenants_4

Trying to invent the future in a castle 40 km from Paris, or actually… trying to invent the present?

chateau_l'echapee

[Français]

Last weekend I was in a beautiful castle 40 km from Paris (look at the picture above!) in an event called “L’échappée“, the objectif was to put in the same place, researchers, entrepreneurs, engineers, designers and creative people in general to try to imagine the world in 2030. After the experience, inside the train coming back to Paris, I started to reflect about everything, and actually what we were doing was trying to invent the present, trying to invent the solutions to everyday problems from oil, corruption and pollution to the education system, refugees and borders and global citizens.

[Le week-end dernier, j’étais dans un magnifique château à 40 km de Paris (regardez la photo ci-dessus !) dans un événement appelé « L’échappée », l’objectif était de mettre dans le même endroit, des chercheurs, des entrepreneurs, des ingénieurs, des designers et des créatifs en général pour essayer d’imaginer notre monde en 2030. Après l’expérience, à l’intérieur du train pour rentrer à Paris, j’ai commencé à réfléchir sur tout ce que j’avais vécu, et en fait ce que nous étions en train de faire c’était d’essayer d’inventer le présent, d’essayer d’inventer les solutions aux problèmes quotidiens de tout les jours comme le pétrole, la corruption, la pollution ou même le système d’éducation, les réfugiés, les frontières et les citoyens du monde.]

In the following lines I will try to tell you the story of last Saturday, the day in which I witnessed the presentation of amazing projects and specially the day in which I exchanged with so many crazy and amazing ideas. Sometimes during the day I have felt that I was inside the french film « Demain ».

[Je vais essayer de vous raconter l’histoire de ce samedi 28 mai dans le château, le jour où j’ai assisté à différentes présentations de projets étonnants et spécialement le jour où j’ai échangé avec tant d’idées folles et étonnantes. Parfois, je sentais que j’étais à l’intérieur du film « Demain »]

Intervenants_1

Let’s start dreaming

[Commençons par rêver]

Inside the train from Paris to the castle I was looking to the city, to the rails, and to every detail that was around me, I was fascinated with the creativity of human beings, of our capacity to identify and solve problems and as Jay Silver used to say, I was fascinated with how inventions are simply the human-made part of the world that we live in.

[A l’intérieur du train de Paris au château, j’étais en train de regarder à travers de la fenêtre la ville, les rails de train, et chaque détail qui était autour de moi, j’étais vraiment fasciné par la créativité des êtres humains, de notre capacité à identifier et résoudre divers problèmes, et comme Jay Silver disait, je suis fasciné par la façon dont les inventions sont tout simplement la partie fait par les humains du monde dans lequel nous vivons.]

Minerva

Marc de Basquiat started the day inside the castle explaining socially and economically an idea that I was following long time ago: a basic income for everybody, it was amazing to see that about 70% of the people that was present thought positively about this idea. Then Marielle Van der Meer from the Minerva project has surprised me with a great idea around education: we live in a global and connected world, we are becoming global citizens, so universities must be global and connected too, students need to be out of the campus and be around the world to experience it. To achieve this, technology is not an end in itself but is there to enhance the learning global experience. Continuing this dream around education, Alyette Tritsch from the Kiron project, is using Big Data to make universities available to refugees, because yes, education is the best way to solve this problem.

[Marc de Basquiat a commencé la journée à l’intérieur du château expliquant socialement et économiquement une idée que je suis depuis longtemps : la revenu de base, c’était étonnant qu’environ 70% des personnes qui étaient présentes avaient une idée positive à propos du sujet. Puis Marielle Van der Meer du projet Minerva m’a surpris avec une idée géniale autour de l’éducation : nous vivons dans un monde global et connecté, aujourd’hui nous sommes des citoyens du monde et les universités doivent être également globales et connectées, les élèves doivent être en dehors du campus et doivent expérimenter le monde, pour y parvenir, la technologie ne constitue pas une fin en soi mais est là pour améliorer l’expérience globale de l’apprentissage. Poursuivant ce rêve autour de l’éducation, Alyette Tritsch du projet Kiron, utilise le Big Data pour rendre les universités à la disposition des réfugiés, parce que oui, l’éducation est la meilleure façon de résoudre ce problème.]

Then a great surprise, Sebastien Kopp has begun to tell his story about sustainable development in a global and connected world and how you can reinvent a product that already exists but with a completely different model: to build shoes that are not based in advertisement and from recycled waste. He and his team did it, and they invented the Vega shoes, Sebastien has reminded us that it is to us to invent new transparent economical models, because transparency depends on each of us. And yes, after the COP21 everybody is talking about how we can create new models that respect our planet, that’s why Eliott Lepers created the 90 days app, a method that has shown us that we have the right to miss, to procrastinate, and that specially has shown us that we can change and create new habits that respect others and our environment, step by step, in 90 days. In this same way, Jean Moreau from the Phenix project demonstrated that in a circular economy, waste is the raw material of the 21st century, and it works! (just look at his project). And talking about the environment, we have to think about the materials that we use everyday, I was fascinated with the project of Timothée Boitouzet, an architect and designer who works with a special wood that he invented for the city of tomorrow, because the construction sector intensely pollutes the earth every day, he created this “augmented” wood for the cities of the future. Lucie Viry did the same thing, but with other material: plastic!. 3D printers could disrupt everything in the next years, the problem is that 3D printers use… plastic!. Do you imagine? we could create a new ecological disaster with the use of 3D printers. To solve this problem, she invented a 3D printer called PAM that uses a new biodegradable material, another surprising feature of this material? With PAM you can make objects that after the biodegradation will become pollen. Finally we received Naziha Mestaoui, probably you saw her and you saw her project during the COP21, this artist works with quantum physics and has shown us that all that surrounds us is immaterial, all is energy, so she tried to express this concept during the COP21 with the project 1 heart 1 tree, where people through a mobile app could project trees in the Eiffel Tour.

[Puis une grande surprise, Sébastien Kopp a commencé à raconter son histoire sur le développement durable dans un monde global et connecté et comment nous pouvons réinventer un produit qui existe déjà, mais avec un modèle complètement différent : pour construire des chaussures qui ne sont pas fondées sur la publicité et faites avec de déchets recyclés. Et lui et ses partenaires l’ont fait, ils ont inventé les chaussures Vega, Sébastien nous rappelle qu’il est à nous d’inventer de nouveaux modèles économiques transparents, parce que la transparence dépend de chacun de nous. Et oui, après la COP21 tout le monde parle de la façon dont nous pourrions créer de nouveaux modèles qui respectent notre environnement, voilà pourquoi Eliott Lepers a créé l’application mobile « 90 jours », une méthode qui nous montre que nous avons le droit de nous tromper et de procastiner, mais surtout elle nous montre que nous pouvons changer et créer de nouvelles habitudes qui respectent les autres et notre environnement, étape par étape, en 90 jours. Dans ce même sens, Jean Moreau du projet Phenix a démontré que dans une économie circulaire, les déchets sont la matière première du 21ème siècle, et que ça marche !. En parlant de l’environnement, nous devons réfléchir sur les matériaux que nous utilisons tous les jours, je suis fasciné par le projet de Timothée Boitouzet, un architecte et un concepteur qui travaille avec un bois spécial qu’il a inventé pour la ville de demain, le problème c’est que le secteur de la construction pollue intensément la terre tous les jours, donc il a créé cette bois « augmentée » pour les villes du futur, impressionnant !. Lucie Viry a fait la même chose, mais avec un autre matériel : le plastique. Les imprimantes 3D ont la capacité de transformation de différents systèmes dans les années qui viennent, le problème c’est que les imprimantes 3D utilisent intensément … le plastique ! vous vous imaginez ? avec les imprimants 3D nous pourrions créer une nouvelle catastrophe écologique ! c’est pour ça que Lucie et son équipe ont inventé une imprimante 3D appelé PAM qui utilise un nouveau matériel biodégradable, une caractéristique étonnante de ce matériel ? Avec PAM vous faites des objets qui après sa biodégradation deviennent pollen. Enfin, nous avons reçu Naziha Mestaoui, probablement vous avez vu son projet au cours de la COP21 à Paris, cet artiste travaille avec la physique quantique et nous montre que tout ce qui nous entoure est immatériel, des énergies, elle a essayé d’exprimer cela pendant la COP21 avec le projet « 1 coeur 1 arbre », où les gens par le biais d’une application mobile avaient la possibilité de mettre des arbres dans une projection sur la Tour Eiffel.]

One thing that has stayed in my mind: The relation and the role of our actual systems and models and our global and connected world.

[Une chose qui est resté dans mon esprit : quel rôle pour nos systèmes et nos modèles actuels dans un monde global et connecté ?]

Intervenants_2

In the cyber era: the governed or the governors?

[À l’ère cyber : gouvernés ou gouvernants ?]

We started connecting the last part with a big challenge that we have in the coming years related to the models that were generated during the industrial era: Robots. So Gael Langevin started showing us the first open source robot, publicly available for all of us, with the idea that all the citizens could contribute to the development of artificial intelligence, making this subject more transparent and working with it responsibly. In this same way Alain Bensoussain wondered who governs the algorithms and the robots? the answer is no one. We have to think that virtual things are migrating from virtual environments to physic environments, that’s why we will start to face new problems like cybercrime as Guy-Philippe Goldstein has shown us with all the new complexities and challenges that this represents to the world.

[Nous avons commencé par relier la dernière partie avec un grand défi que nous avons dans les années à venir par rapport aux modèles qui ont été générés au cours de l’ère industrielle: les robots. Gael Langevin a commencé à nous montrer le premier robot open source, disponible pour nous tous, l’objectif c’est que nous pouvons tous contribuer à l’intelligence artificielle, ce qui rend ce sujet plus transparent pour travailler d’une façon plus responsable. De la même manière Alain Bensoussain se demandait qui régit les algorithmes et les robots ? la réponse est personne. Nous devons prendre en compte qu’aujourd’hui les objets virtuelles sont en train de migrer des environnements virtuels aux environnements physiques, pour cette raison, nous allons commencer à faire face à de nouveaux problèmes et défis, justement Guy-Philippe Goldstein nous montrait le grand défi de la cybercriminalité et ses nouvelles complexités.]

Simulticast

But what about politics and democracy in this new context? if we analyse the last french regional election, the first party in France (and in some other countries in the western world) is abstention, we live in a system of distrust where people use social networks and smartphones to express themselves against the distrust of media, politicians and businesses. Facing this, imagine an app to vote every day, to express yourself every day. That’s why Bobby Demri created the app GOV, trying to imagine a world where for exemple, while you are waiting for the bus, you can interpellate your mayor creating the agora of the 21st century. Facing the same problem, Léonore de Roquefeuil created another app called Voxe, with a big challenge for the next presidential French election: the objective is that 5 million people pass just 5 minutes of their time to design the 5 mandates. The thing is that today we have the tools to participate and to connect with the political system to improve democracy.

[Mais qu’en est-il de la politique et de la démocratie dans ce nouveau contexte ? le premier parti politique de la France (et de plusieurs pays du monde occidental) est l’abstention, nous vivons dans un système de méfiance où les gens utilisent les réseaux sociaux et les smartphones pour s’exprimer contre la méfiance des médias, les politiciens et les entreprises. Face à cela, vous vous imaginez une application qui nous donne la possibilité de voter tous les jours ?, de nous exprimer tous les jours ?. C’est pour cette raison que Bobby Demri a créé l’application GOV, en essayant d’imaginer comment il pourrait être un monde où, par exemple, pendant que vous attendez le bus, vous pourriez interpeller votre maire, son objectif c’est de créer l’agora du 21ème siècle. Face au même problème, Léonore de Roquefeuil a créé une autre application: Voxe, avec un grand défi pour la prochaine élection présidentielle française: que 5 millions de personnes passent 5 minutes de leur temps pour concevoir les 5 mandats. Ces examples montrent qu’aujourd’hui nous avons les outils pour participer et connecter avec les politiciens en améliorant notre système démocratique et notre système politique en général.]

All of this is connected with people’s initiatives to change the world and the desire of other people to connect and help these citizens to transform the world, so Nicolas Goudy created the Uber for citizen action, the name of the project is « Je m’engage » (something like “I’m in”), he’s trying to connect citizens depending on their geolocation, interests and time, trying at the same time, to build the world step by step.

[Tout cela est lié à des initiatives des citoyens pour changer le monde et le désir d’autres personnes de connecter avec ces citoyens et leur aider à changer le monde, Nicolas Goudy a créé le Uber pour l’action citoyenne : son projet s’appelle « je me engage », et l’objectif c’est de relier les citoyens en fonction de leur géolocalisation, leur intérêts et leurs temps pour construire et inventer le monde étape par étape.]

One of the most amazing explanations about the new buzzword that is everywhere, was the explanation about the Blockchain that was made by Primavera de Filippi, showing us a sculpture of a plant called Plantoid that can reproduce herself using the Blockchain technology, the plant can react later, giving money on the basis of an economic model. Thanks to the Blockchain we will start to talk about the Internet of Humans instead of the Internet of Things, where collaboration is the most important thing to create value. Continuing this amazing demonstration, Santiago Siri, who’s main gob is hacking governments, created the Democracy Earth Foundation, with the idea that today we (the citizens) can do 10x better than traditional governments, so we don’t have to wait for them to build trust without borders, creating identity, voting and representation for everybody.

[Une des explications les plus étonnantes au sujet d’un nouveau concept qui à l’heure actuelle est partout, a été faite par Primavera de Filippi sur la Blockchain, nous montrant une sculpture d’une plante appelé Plantoid qui peut se reproduire à l’aide de la Blockchain, la plante peut réagir en pleine conscience plus tard, et par exemple, donner de l’argent sur la base d’un modèle économique. Grâce à la Blockchain nous allons commencer à parler de l’Internet des êtres humains au lieu de l’internet des objets, où la collaboration est l’élément le plus important pour créer de la valeur. Poursuivant cette étonnante démonstration, Santiago Siri, qui son travail principal est de hacker les gouvernements, a créé la fondation de la démocratie de la terre (The Democracy Earth Foundation), avec l’idée suivante : aujourd’hui, nous (les citoyens) pouvons faire 10x mieux que les gouvernements traditionnels, donc nous ne devons pas attendre pour eux pour construire une confiance sans frontières, pour créer l’identité, le vote et la représentation pour tout le monde.]

One thing that has stayed in my mind: How the Blockchain can transform the current models, making citizen participation a central part to re-invent our old models.

[Une chose qui est resté dans mon esprit : comment la Blockchain peut transformer les modèles actuels, ce qui pourrait rendre la participation des citoyens une partie centrale pour réinventer nos modèles anciens.]

Intervenants_3

Science in progress

[La science en progrès]

A 17 years old mathematical genius began the third session, the first idea of Ivan Zelich was that mathematics should be explained visually and in a practical way, the problem is that our education systems do exactly the opposite, creating kids (like Ivan, when he was in school) that hates mathematics. This young Australian developed a maths theorem that calculates problems faster than a computer, one thing that he said that touch me was about how computers can not develop the human creativity to find a solution and understand the nature of a problem (thing that our education system don’t understand yet), creativity allows us to see the beauty in mathematics and science that machines can not see. One exemple is the last experience in artificial intelligence made by Google (AlphaGo) with the game Go: It is clear that computers will never understand the beauty of the game. In this same way, Philippe Menei, a doctor that uses virtual reality to map the brain and treat diseases such as autism, showed us how we can use technology to create meaning. Around all of these technologies that impact science, one concept was specially important: open source, Mehdi Benchoufi et Émilie Mayer, demonstrated how today we can build open source tools that before was impossible to build, specially in medicine, where equipments are very expensive, so they are building tools to identify diseases that everybody can have in their homes, the magic of open source objects in medicine is that we can build and improve things faster and transform our lives and society. Following this same idea, Laura Terriou showed us that the problem of gadgets that use the technology of connected objects is that 70% of them are abandoned after 3 months of use, so she has built the Orio app which uses the data of our connected objects to analyze everything individualizing our health diagnoses.

[Un génie de mathématiques de 17 ans a commencé la troisième session, la première idée d’Ivan Zelich était que les mathématiques doivent être expliquées visuellement et de façon pratique, le problème est que nos systèmes éducatifs font exactement le contraire, formant des enfants (comme Ivan quand il était à l’école) qui détestent les mathématiques. Ce jeune australien a développé un théorème de mathématique qui calcule les problèmes plus rapidement qu’un ordinateur. Une chose qu’il avait dit et que m’avait particulièrement marqué était sur la façon dont les ordinateurs ne peuvent pas développer la créativité humaine pour trouver une solution et pour comprendre la nature d’un problème (chose que notre système d’éducation ne comprennent pas encore), la créativité nous permet de voir la beauté que les machines ne peuvent pas voir des mathématiques et des sciences. Un exemple c’est la dernière expérience sur l’intelligence artificielle développé par Google (AlphaGo) sur le jeu Go: les ordinateurs ne comprendront jamais la beauté du jeu. Dans ce même sens Philippe Menei, un médecin qui utilise la réalité virtuelle pour cartographier le cerveau et le traitement de maladies telles que l’autisme, nous montrait comment nous pouvons utiliser la technologie pour créer du sens. Autour de toutes ces technologies que impactent la science, un concept a été particulièrement important : l’open source, Mehdi Benchoufi et Émilie Mayer ont montré comment nous pouvons aujourd’hui construire des outils open source qu’avant ont n’avaient pas la possibilité de construire, spécialement dans le domaine de la médecine, où les équipements sont très coûteux, ces deux chercheurs sont en train de construire des instruments que tout le monde peut avoir dans leurs maisons visant à identifier des maladies, la magie des objets open source en médecine est que nous pouvons construire et améliorer les choses plus rapidement en transformant nos vies et nos sociétés. Suite à cette même idée, Laura Terriou nous montrait que le problème de gadgets qui utilisent la technologie des objets connectés est que 70% d’entre eux sont abandonnés au bout de 3 mois d’utilisation, c’est pour cette raison qu’elle a construit l’application Orio qui utilise les données de nos objets connectés pour tout analyser et pour individualiser nos diagnostics de santé.]

Maths

But what about nutrition? a very important issue today which raises many questions, how we produce our food?, what are we eating? what food companies are doing with our health? how we transport food? Bernard Sacy created the project Spiris after he discovered the spirulina, a micro algae with a lot of benefits for our health, but Bernard found a problem in its production in Europe: is very expensive, so the purpose of Bernard is to create the first european sustainable farm to produce spirulina at an industrial scale.

[Et qu’est-ce qu’il passe avec notre alimentation ? une question très importante aujourd’hui en parallèle avec des questions comme comment produisons-nous la nourriture ?, quels aliments mangeons-nous ? Qu’est-ce que les entreprises font avec les aliments et notre santé ? comment transportons-nous la nourriture ? pour répondre à ces questions, Bernard Sacy a créé le projet Spiris, la spiruline est une micro-algue avec beaucoup de propriétés pour notre santé, mais Bernard a trouvé un problème dans sa production en Europe, elle est très cher et n’est pas durable, donc le but de Bernard est de créer la première ferme durable européen pour produire de la spiruline à l’échelle industrielle.]

Then it was the turn of Julie Legault and an amazing project that has the potential to transform completely the world through bacteria, because now we can make textiles or leather without the use of animals in a sustainable and renewable way, we can also produce smart clothes or even build houses thanks to bacteria. Julie is working in the Amino project, a desktop bioengineering for everyone, an easy way to create and take care of living cells. In the other side of this subject, Pierre Bélichard has shown us the dangers of bacteria living in our bodies, because of the disequilibrium produced by all the antibiotics that we eat.

[Puis ce fut le tour de Julie Legault et un projet étonnant qui a le potentiel de transformer complètement le monde à travers les bactéries, parce que maintenant nous pouvons fabriquer des textiles ou du cuir sans l’utilisation des animaux d’une manière durable et renouvelable, mais nous pouvons aussi produire des vêtements connectés et intelligents ou même des maisons, tout avec des bactéries, Julie travaille dans le projet Amino, un projet de bioingénierie pour tout le monde, un moyen facile de créer et prendre soin des cellules vivantes dans nos bureaus. Mais dans ce même sujet, Pierre Bélichard nous montrait les dangers de bactéries vivant dans notre corps, en raison du déséquilibre produit par tous les antibiotiques que nous mangeons.]

This session was closed by an amazing person, Bebop Gresta and the Hyperloop project, showing the problem of transportation, explaining why this sector is broken and questioning why we have to wait a lot of hours in airports? Or be forced to endure the traffic of big cities?, today we have the tools to solve these problems, what is amazing is that to understand the future you have to look at the past, in 1904 scientists tried to create the Hyperloop, but  science was not at the same time than human imagination. With this project, they are trying to imagine how it would be if you can go from Paris to Milan in 50 minutes, connecting the whole world with green and efficient transportation, today this is possible and the team of the Hyperloop project is working on that (in France the SNCF (the company trains) already invested in the project).

[Cette session a été clôturée par une personne incroyable, Bebop Gresta du projet Hyperloop, montrant le problème du transport est que ce secteur est cassé : pourquoi devons-nous attendre beaucoup d’heures dans les aéroports ? Ou être forcés à supporter le trafic des grandes villes ?, nous avons aujourd’hui les outils pour résoudre ces problèmes, ce qui est étonnant est que, pour comprendre l’avenir, nous devons regarder le passé, en 1904, des scientifiques ont essayé de créer le projet Hyperloop, mais la science n’était pas dans le même temps que l’imagination humaine. Alors, imaginez si vous pourriez aller de Paris à Milan en 50 minutes, reliant le monde entier avec du transport durable, efficient et propre, aujourd’hui cela est possible et l’équipe du projet Hyperloop travaille actuellement sur ce sujet (en France, la SNCF a déjà investi dans le projet).]

One thing that has stayed in my mind: Humans have imagination and creativity, machines don’t, but we have to create an equilibrium to advance science, I found fascinating the development of Biotechnology and I strongly believe that this could be the future of science and other fields.

[Une chose qui est resté dans mon esprit : les humains ont de l’imagination et de la créativité, les machines ne l’ont pas, mais nous devons créer un équilibre pour faire avancer la science, je trouve fascinant le développement de la biotechnologie et je croient fermement que ça pourrait être l’avenir de la science et d’autres domaines.]

Intervenants_4

Humanities in question

[Humanités en question]

We ended the day putting in question not only the relation and the interactions between humans and machines, but how both are merging. Hannes Sjoblad started the session, his a body hacker from Sweden that has shown us how connected objects can be inside us, gathering and generating information from the inside, we even had the opportunity to make an experimentation to see how this can works implanting an NFC chip in the hand of a participant that volunteered to do that. After this crazy moment, Laurent Alexandre, a french surgeon interested in the transhumanist movement and Jean-Michel Besnier, a french philosopher and professor of philosophy at the University of Paris-Sorbonne (Paris IV) and author of the book “Un cerveau très prometteur : Conversation autour des neurosciences” (A very promising brain: A conversation about neuroscience), closed the event with an amazing and very tense and intense debate that we can catalogue as a debate between the right and the left view of the society, but I think it went beyond the political views that we used to have, probably because I tried to see the debate and my whole experience during the day with the eyes of a little child.

[Nous avons terminé la journée en mettant en cause non seulement la relation et les interactions entre les humains et les machines, mais comment les deux se fusionnent. Hannes Sjoblad, un hacker du corps suédois a commencé par nous montrer comment les objets connectés peuvent être à l’intérieur de nous, et la collecte et la production d’informations à partir de l’intérieur de notre corps, nous avons même fait une expérimentation avec l’implantation d’une puce NFC dans la main d’une participante de l’événement pour vérifier comment cela peut fonctionner. Après ce moment fou et étonnant, Laurent Alexandre, un chirurgien français intéressé par le mouvement transhumaniste et Jean-Michel Besnier, philosophe français et professeur de philosophie à l’Université de Paris-Sorbonne (Paris IV) et auteur du livre « Un cerveau très prometteur : conversation autour des neurosciences », ont clôturé l’événement avec un débat incroyable et très tendue et intense, que nous pouvons cataloguer comme un débat classique entre la droite et la gauche, mais personnellement je pense qu’il est allé au-delà de ces deux visions politiques, probablement parce que j’essayé de voir le débat et toute mon expérience au cours de la journée avec les yeux d’un petit enfant.]

Virtuel_Reel

The last surprise was Miguel Benasayag, a Franco-Argentinian researcher in epistemology. The objective was to put on doubt and deconstruct what was said during the day, with the touch of criticism and humor of Miguel.

[La dernière surprise fut Miguel Benasayag, un chercheur franco-argentin en épistémologie. L’objectif était de mettre sur le doute et de déconstruire ce qui a été dit au cours de la journée, avec bien sûr, la touche de la critique et l’humour de Miguel.]

At the end I found myself taking the train after an amazing experience, I’m still assimilating all of the things that I saw and experienced, all the projects, all the labs and all the exchanges with so many people from different backgrounds and cultures. Life is made of experiences, of all types, we suppose to be in the castle to imagine the future, but we were experiencing the invention of the present, dreaming about how the present it is, and in this way, again, I was reflecting on how mindfulness plays an essential role in our lives and in society in general, we don’t need to imagine the future, we just need to be in the present moment and observe all the experiences around us to enjoy life.

[A la fin, je me trouvait encore une fois dans le train de retour à Paris et après avoir vécu une expérience incroyable, je suis toujours en train d’assimiler toutes les choses que j’ai vu et que j’ai expérimenté, tous les projets, tous les laboratoires et tous les échanges avec tant de gens de différents milieux et cultures. Finalement, la vie est faite d’expériences, de tous les types, normalement, nous devons être dans le château pour imaginer l’avenir, mais nous étions là pour experimenter l’invention du présent, pour rêver sur le présent. De cette façon, encore une fois, j’ai réfléchi sur comment la pleine conscience joue un rôle essentiel dans nos vies et dans nos sociétés, on n’a pas besoin d’imaginer l’avenir, nous avons juste besoin d’être dans le moment présent et d’observer les expériences autour de nous pour profiter de la vie.]

A fascinating book about human judgment and how we think: “Thinking Fast and Slow”

Thinking-Fast-and-Slow

[Français]

I just finish this fascinating book called “Thinking Fast and Slow” by the Nobel Prize in Economics Daniel Kahneman about decades of his research on cognitive biases and prospect theory. Basically the book describes two modes of thought: “System 1” is fast, instinctive and emotional; and “System 2” is slower, more deliberative, and more logical.

[Je viens de terminer ce livre fascinant intitulé « Système 1 / Système 2 : Les deux vitesses de la pensée » (Thinking Fast and Slow en anglais) du prix Nobel en économie Daniel Kahneman sur ses recherches tout au long des dernières décennies sur les biais cognitifs et la théorie de la perspective. Fondamentalement, le livre décrit deux modes de pensée: « Système 1 », rapide, instinctive et émotionnelle; et « Système 2 », plus lent, plus délibérative, et plus logique.]

Below you have some notes from each chapter that Michael Parker has taken, to have everything about this book you have to read it, the book is very extensive and very rich in fascinating research exemples, I think every researcher should read it.

[Vous avez ci-dessous quelques notes sur chaque chapitre que Michael Parker a pris (en anglais). Il vaut la peine de lire l’ensemble du livre, il est très vaste et très riche en exemples de recherche fascinants, personnellement je pense que tous ceux qui travaillent dans la recherche devraient le lire.]

Introduction

  • We use resemblance as a simplifying heuristic to make difficult judgment, causing predictable biases in predictions.
  • Social scientists in the 1970s broadly accepted that people are generally rational, and emotions such as fear, affection, and hatred explain departures from rationality.
  • People tend to assess the relative importance of issues by the ease with which they are retrieved from memory, which is largely determined by the media.
  • Accurate intuitions of experts are better explained by the effects of prolonged practice than by heuristics.
  • Valid intuitions develop when experts have learned to recognize familiar elements in a new situation and to act in a manner that is appropriate to it.
  • When faced with a difficult question, we often answer an easier one instead, usually without noticing the substitution.
  • When intuition fails, because neither an expert solution nor a heuristic answer comes to mind, we resort to slower, deliberate, and effortful thinking.

Part 1: Two Systems

Ch 1: The Characters of the Story

  • System 1 operates automatically and quickly, with no effort and no voluntary control.
  • System 2 allocates attention to effortful mental activities. It’s associated with the subjective experience of agency, choice, and concentration.
  • All operations of System 2 require attention and are disrupted when attention is drawn away.
  • System 2 has some ability to change the way System 1 works, by programming the normally automatic functions of attention and memory.
  • System 1 generates impressions, intuitions, intentions, and feelings. Those endorsed by System 2 turn into beliefs and voluntary actions.
  • Most of what System 2 thinks and does originates in your System 1, but System 2 takes over when things get difficult, and it normally has the last word.
  • One of the tasks of System 2 is to overcome the impulses of System 1. System 2 is in charge of self-control.
  • System 2 is too slow and inefficient to substitute for System 1. The best we can do is to recognize when mistakes are likely, and to try harder to avoid significant mistakes when the stakes are high.

Ch 2: Attention and Effort

  • Pupils are sensitive indicators of mental effort. The more System 2 exerts mental effort, the more they dilate.
  • We decide what to do, but we have limited control over the effort of doing it. The task at hand decides this.
  • Orienting and responding quickly to the gravest threats or most promising situations improved the chance of survival.
  • In the economy of action, effort is a cost, and the acquisition of skill is driven by balancing benefits and costs. Laziness is in our nature.
  • System 2 is the only one that can follow rules, compare objects on several attributes, and make deliberate choices between objects.
  • A crucial capability of System 2 is that it can program memory to obey an instruction that overrides habitual responses.
  • Multitasking is effortful. Time pressure is another driver. Any task that requires keeping several ideas in mind simultaneously has the same hurried character.

Ch 3: The Lazy Controller

  • Mihaly’s flow is a state of effortless concentration so deep that people lose a sense of time, of themselves, and of their problems.
  • This flow separates the two forms of effort: Concentration on the task and the deliberate control of attention.
  • People who are cognitively busy are more likely to yield to temptation, make selfish choices, use sexist language, and make superficial judgments in social situations.
  • Controlling thoughts and behaviors is one of the tasks that System 2 performs.
    If you exert self-control for a task, then you are less willing or able to exert self-control for a following task. This is called ego depletion.
  • When you are thinking hard or exerting self-control, your blood glucose level drops. The implication is that you can undo ego depletion by ingesting glucose.
  • When people believe a conclusion is true, they are also very likely to believe arguments that appear to support it, even when those arguments are unsound.
  • Intelligence is not only the ability to reason; it is also the ability to find relevant material in memory and to deploy attention when needed.
  • “Engaged” people are more alert, less willing to be satisfied with superficially attractive answers, and more skeptical about their intuitions.
  • People who are not “engaged” are impulsive, impatient, and keen to receive immediate gratification.

Ch 4: The Associative Machine

  • The responses by System 1 are associatively coherent, yielding a self-reinforcing pattern of cognitive, emotional, and physical responses.
  • Cognition is embodied. You think with your body, not only with your brain.
  • Ideas are nodes in a vast network called associative memory, where causes link to effects, things to their properties, and things to their categories.
  • Priming is not restricted to concepts and words. Events that you are not even aware of prime your actions and emotions.
  • The influence of an action by the idea is called the ideomotor effect. It also works in reverse. For example, thinking of old age makes you act old, and vice versa.
  • Money primes individualism: a reluctance to be involved with others, to depend on others, or to accept demands from others.
  • Feeling that one’s soul is stained triggers a desire to cleanse one’s body, an impulse that is dubbed the Lady Macbeth Effect.
  • System 1 provides the impressions that often turn into your beliefs, and is the source of impulses that often become the choices of our actions.

Ch 5: Cognitive Ease

  • Cognitive strain is affected by both the current level of effort and the presence of unmet demands. This mobilizes System 2.
  • A repeated experience, clear display, primed idea, and good mood all increase cognitive ease. This in turn makes things feel familiar, true, good, and effortless.
  • When strained, you are vigilant, suspicious, invest more effort, feel less comfortable, and make fewer errors. But you are less intuitive and less creative.
  • Predictable illusions occur if judgment is based on an impression of cognitive ease or strain. For example, frequent repetition makes people believe lies.
  • To craft a persuasive message, use high quality paper, bright colors, simple words, memorable verse, and quote the source with the simpler name.
  • Cognitive strain, whatever the source, mobilizes System 2, which is more likely to reject the intuitive answer suggested by System 1.
  • The mere exposure effect links the repetition of an arbitrary stimulus and the mild affection that people have for it. It’s stronger for stimuli that we don’t consciously see.
  • Mood affects the operation of System 1. When we are uncomfortable and unhappy, we lose touch with our intuition.

Ch 6: Norms, Surprises, and Causes

  • The main function of System 1 is to maintain and update a model of your personal world, which represents what is normal in it.
  • Norm theory is when a surprising event happens, and subsequent surprising events will appear more normal because they are interpreted in conjunction with it.
  • We have norms for a vast number of categories, which provide the background for the immediate detection of anomalies.
  • System 1 is adept at finding a coherent causal story that links the fragments of knowledge at its disposal.
  • We are ready from birth to have impressions of causality, which do not depend on reasoning about patterns or causation. They are products of System 1.
  • We are prone to apply causal thinking to situations that require statistical reasoning, but System 1 cannot do this, and System 2 requires necessary training.

Ch 7: A Machine for Jumping to Conclusions

  • Jumping to conclusions is efficient if the jump saves time and effort, the conclusion is likely correct, and the cost of an occasional mistake is acceptable.
  • System 1 bets on answers, where recent events and the current context have the most weight in determining and interpretation. Otherwise, more distant memories govern.
  • System 1 is gullible and biased to believe, while System 2 is in charge of doubting and unbelieving, but System 2 is sometimes busy and often lazy.
  • Unlike scientists, which test hypotheses by trying to refute them, we seek data that are likely to be compatible with the beliefs that we currently hold.
  • The tendency to like or dislike everything about a person, including things you have not observed, is known as the halo effect.
  • The halo effect increases the weight of first impressions, sometimes to the point that subsequent information is mostly wasted.
  • To derive the most useful information from multiple sources of evidence, you should always try to make these sources independent of each other.
  • The standard practice of open discussion gives too much weight to the opinions of those who speak early and assertively, causing others to line up behind them.
  • System 1 excels at constructing the best possible story that incorporates ideas currently activated, but it cannot allow for information that it does not have.
  • Jumping to conclusions facilitates the achievement of coherence and of the cognitive ease that causes us to accept a statement as true. It explains overconfidence.

Ch 8: How Judgments Happen

  • System 1 continually assesses the problems that an organism must solve to survive. We equate good mood and cognitive ease with safety and familiarity.
  • Faces with a strong chin and a slight confident-appearing smile exude confidence.
  • A judgment heuristic is falling back on a simpler assessment that is made quickly and automatically and is available when System 2 must make its decision.
  • Because System 1 represents categories by a prototype or a set of typical exemplars, it deals well with averages but poorly with sums.
  • System 1 allows matching intensity across diverse and unrelated dimensions. This mode of prediction by matching is statistically wrong, although acceptable to both systems.
  • The control over intended computations is far from precise, and we often compute much more than we want or need. This is called the mental shotgun.

Ch 9: Answering an Easier Question

  • If we can’t satisfactorily answer a hard target question, then System 1 invokes substitution by recalling and answering an easier heuristic question.
  • After answering a heuristic question, System 1 uses intensity matching to translate this answer to an answer of the target question.
  • The dominance of conclusions over arguments is most pronounced when emotions are involved.
  • An affect heuristic is when people let their likes and dislikes determine their beliefs about the world.
  • While self-criticism is one of the functions of System 2, it is more of an apologist for than a critic of the emotions of System 1.

Part 2: Heuristics and Biases

Ch 10: The Law of Small Numbers

  • System 1 is inept when faced with statistical facts, which change the probability of outcomes but do not cause them to happen.
  • Extreme outcomes, both high and low, are most likely to be found in small than in large samples.
  • Even statistical experts pay insufficient attention to sample size, and have poor intuitions of sampling effects.
  • System 2 is capable of doubt, but sustaining doubt is harder work than sliding into certainty.
  • System 1 runs ahead of the facts and constructs a rich image based on scraps of evidence, causing us to exaggerate the consistency and coherence of what we see.
  • The associative machine seeks causes. But instead of focusing on how the event came to be, the statistical view relates it to what could have happened instead.
  • We do not expect to see regularity produced by a random process. When we detect what appears to be a rule, we quickly reject the idea that the process is truly random.
  • We pay more attention to the content of messages than to information about their reliability.
  • Consequently we view the world in a simpler and more coherent way than the data justify.

Ch 11: Anchors

  • An anchoring effect occurs when people consider a particular value for an unknown quantity before estimating that quantity.
  • Adjusting your estimate away from the anchor is an effortful activity. Insufficient adjustment, where we accept the anchor, is a sign of a weak or lazy System 2.
  • Anchoring is also a priming effect, which selectively evokes compatible evidence. This is the automatic operation of System 1.
  • The anchoring index is 100% for people who adopt the anchor as an estimate, and zero for people who are able to ignore the anchor altogether.
  • Anchors that are obviously random can be just as effective as potentially informative anchors.
  • When negotiating, don’t make an outrageous counteroffer to an outrageous proposal, but make a scene and make it clear that you won’t continue with that number on the table.
  • To resist anchoring effects, search your memory for arguments against the anchor. This negates the biased recruitment of thoughts that produces these effects.
  • System 2 is susceptible to the biasing effect of some anchors that makes some information easier to retrieve. It has control over or knowledge of the effect.

Ch 12: The Science of Availability

  • The availability heuristic replaces estimating the size of a category or frequency of an event with the ease with which instances come to mind.
  • Salient events, dramatic events, and personal experiences versus experiences by others bias the ease with which instances come to mind.
  • This explains why everyone in a group may feel as though he or she does more than his or her fair share.
  • By asking people to provide more instances of a given behavior, you increase their struggle, and consequently they conclude that they don’t adopt that behavior.
  • Judgment is influenced more by the ease of retrieval than the number of instances retrieved. Increasing the number of requested instances therefore weakens judgment.
  • When you provide a spurious reason for the difficulty of retrieving a large number of instances, judgment is again strengthened. The surprise is eliminated.
  • People who are personally involved in the judgment are more likely to consider the number of instances and less likely to go by fluency.
  • Fluency of instances is a System 1 heuristic, which is replaced by a focus on content when System 2 engages.
  • Merely reminding people of a time when they had power increases their apparent trust in their own intuition.

Ch 13: Availability, Emotion, and Risk

  • Our expectations about the frequency of events are distorted by the prevalence and emotional intensity of the messages to which we are exposed.
  • Jonathan Haidt said “the emotional tail wags the rational dog.”
  • An availability cascade is the self-sustaining chain of events through which a minor event leads to public panic and large-scale government action.
  • Policy is about what people want and what is best for them. The availability cascade is the mechanism through which biases flow into policy.
  • When dealing with small risks, we either ignore them or give them far too much weight, with no middle ground.
  • Availability cascades may have a long-term benefit of calling attention to classes of risks and by increasing the risk-reduction budget.

Ch 14: Tom W’s Speciality

  • The proportion of a particular class in a population is called the base rate of that class.
    How much an instance conforms to the stereotype of a particular class is called the representativeness of that instance.
  • To determine how likely an instance belongs to a class, we ignore the base rate of the class and focus on the representativeness of the instance.
  • Probability by representativeness is more accurate than chance guesses, but neglecting base rate information that points in another direction is a statistical sin.
  • When endorsing representativeness, System 1 will automatically process the available information as if it were true, unless you decide immediately to reject it.
  • Bayesian statistics govern how we should adjust the base rates given an account of representativeness.

Ch 15: Linda: Less is More

  • A conjunction fallacy is when we judge a conjunction of two events to be more probable than one of the events in a direct comparison.
  • The most coherent stories are not the most probable, but they are plausible. And we confuse the notions of coherence, plausibility, and probability.
  • Consequently, adding details to a scenario can make it more persuasive, but less likely to come true.
  • When performing single evaluation instead of joint evaluation, the less is more principle evaluates a collection of items by its average and not its sum.
  • The sum-like nature of a variable is less obvious for probability than something more enumerable like money.
  • A question phrased as “how many” makes you think of individuals, while “what percentage” does not. This decreases the incidence of the conjunction fallacy.

Ch 16: Causes Trump Statistics

  • Statistical base rates are facts about a population to which a case belongs, but they are not relevant to the individual case.
  • Causal base rates change your view of how the case came to be.
  • We neglect statistical base rates, and we easily combine causal base rates with other case-specific information.
  • Resistance to stereotyping is a laudable moral position, but neglecting valid stereotypes inevitably leads to suboptimal judgments.
  • System 1 can deal with stores in which the elements are causally linked, but it is weak in statistical reasoning.
  • Individuals feel relieved of responsibility when they know that others have heard the same request for help.
  • When the outcome surprises us, we are unwilling to deduce the particular from the general, but are willing to infer the general from the particular.
  • Consequently, we are more likely to learn something by finding surprises in our own behavior than by hearing surprising facts about people in general.

Ch 17: Regression to the Mean

  • Regression to the mean is when poor performance is followed by improvement, and good performance is followed by deterioration.
  • We tend to be nice to other people when they please us and nasty when they do not, we are statistically punished for being nice and rewarded for being nasty.
  • The discrepancies between two trials does not need a causal explanation. Often luck explains why one is a significant outlier.
  • The correlation coefficient between two measures is a measure of the relative weight of the factors they share.
  • Whenever the correlation between two scores is imperfect, there will be regression to the mean.
  • Causal explanations will be evoked when we detect regression, but they will be wrong because regression to the mean has an explanation but does not have a cause.

Ch 18: Taming Intuitive Predictions

  • We are capable of rejecting information as irrelevant and false, but adjusting for smaller weaknesses in the evidence is not something System 1 can do.
  • If we are asked for a prediction but substitute an evaluation of the evidence, we generate biased predictions that completely ignore regression to the mean.
  • To create an unbiased prediction, start with a baseline estimate and an estimate derived from the evidence, and choose the value between them that is proportional to your estimate of correlation.
  • Such unbiased predictions make errors, but they are smaller and do not favor either higher or lower outcomes.
  • Unbiased predictions permit predicting rare or extreme cases only when the information is very good, so you’ll never have the satisfaction of calling an extreme case.
  • Unbiased predictions are less preferred when error has varying types and severity, and extreme cases must be called correctly even if it accumulates error elsewhere.
  • Your intuitions will deliver predictions that are too extreme and you will be inclined to put far too much faith into them.

Part 3: Overconfidence

Ch 19: The Illusion of Understanding

  • We are always ready to interpret behavior as a manifestation of general propensities and personality traits, or causes that you readily match to effects.
  • In a story, many of the important events that involve choices tempts us to exaggerate the role of skill and underestimate the part of luck.
  • When you adopt a new view of the world, you immediately lose much of your ability to recall what you used to believe before your mind changed.
  • This causes us to underestimate the extent to which we were surprise by past events, also known as hindsight bias.
  • Hindsight bias leads us to asses the quality of a decision not by whether the process was sound but by whether its outcome was good or bad.
  • The sense-making System 1 makes us see the world as more tidy, simple, predictable, and coherent than it really is. So we think that we can predict the future.
  • The comparison of firms that have been more or less successful is to a significant extent a comparison between firms that have been more or less lucky.

Ch 20: The Illusion of Validity

  • Declarations of high confidence tell you that an individual has constructed a coherent story in his or her mind, not necessarily that the story is true.
  • The persistence of individual differences in achievement is the measure by which we confirm the existence of skill in someone.
  • Facts that challenge basic assumptions, and thereby threaten our livelihood and self-esteem, are simply not absorbed. The mind does not digest them.
  • People can maintain an unshakeable faith, however absurd, when they are surrounded by a community of like-minded believers.
  • A person who acquires more knowledge develops an enhanced illusion of skill and becomes unrealistically overconfident. They have many excuses ready when proven wrong.
  • Errors in prediction are inevitable because the world is unpredictable. And high subjective confidence is not an indicator of accuracy.

Ch 21: Intuitions vs Formulas

  • Roughly 60% of studies have shown significantly better accuracy for algorithms in comparisons of clinical and statistical predictions.
  • One reason experts may be inferior is that they try to be clever, think outside the box, and consider complex combinations of features. This actually reduces validity.
  • Another reason is that when asked to evaluate the same information twice, we frequently give different answers. Unnoticed stimuli can substantially influence System 1.
  • Assigning equal weights to all predictors is often superior than varying weights found by multiple regression, because it’s not affected by accidents of sampling.
  • Consequently, we can develop useful algorithms without any prior statistical research. And back of the envelope judgments are often good enough.
  • The aversion to algorithms making decisions is rooted in the strong preference that many people have for the natural over the synthetic or artificial.
  • Intuition adds value, but only after a disciplined collection of objective information and disciplined scoring of separate traits.
  • When creating your own formula for an interview procedure, pick at most six dimensions, and develop a 1 to 5 scale for each one.

Ch 22: Expert Intuition: When Can We Trust It?

  • In the recognition-primed decision model, System 1 comes up with a plan. System 2 simulates it. If it works, it’s implemented. Otherwise it’s tweaked or discarded.
  • Emotional learning may be quick, but expertise takes time to develop because it requires building a large collection of mini-skills.
  • Confidence does not imply truth. The associative machine suppresses doubt and evokes ideas that are compatible with the current dominant story.
  • Skilled intuitions come from environments where the environment is sufficiently regular to be predictable, and we can learn these regularities through prolonged practice.
  • Human learning is normally efficient. If a strong predictive cue exists, human observers are likely to find it, given a sufficient opportunity to do so.
  • Algorithms perform better in noisy environments because they detect weakly valid cues, and they use such cues consistently.
  • The unrecognized limits of professional skill help explain why experts are often overconfident.
  • Judgments that answer the wrong question can also be made with high confidence.

Ch 23: The Outside View

  • Confidentially collecting the judgment of each person in a group makes better use of the knowledge of its members.
  • Our inside view judgment is overly optimistic, while the outside view judgment rightly adjusts a baseline prediction.
  • We routinely discard statistical information, such as that offered by the outside view, when it’s incompatible with personal impressions of a case.
  • A planning fallacy is unrealistically close to a best-case scenario, and could be improved by consulting the statistics of similar cases.
  • To counter the planning fallacy, reference class forecasting uses distributional information to create a baseline prediction. This adopts an outside view.
  • People often, but not always, take on risky projects because they are overly optimistic about the odds they face.

Ch 24: The Engine of Capitalism

  • The people who have the greatest influence on the lives of others are likely to be optimistic and overconfident, and to take more risks than they realize.
  • The optimistic risk taking of entrepreneurs contributes to the economic dynamism of society, even if most risk takers end up disappointed.
  • We rate ourselves below average on any task we find difficult, and so we are overly optimistic about our standing on any activity we do moderately well.
  • Entrepreneurs imagine a future where their actions determine the outcome of the firm, and not their competitors. This is because they know so little about these competitors.
  • This competition neglect begets more competitors than the market can profitably sustain, and so the average outcome is a loss.
  • A wide confidence interval is a confession of ignorance, which is not socially acceptable for someone who is paid to be knowledgeable. So we must be overconfident.
  • Optimism is highly valued, both socially and in the market, and so we reward the providers of dangerously misleading information more than we reward truth tellers.
  • Optimism contributes to resilience by defending one’s self image, where we take credit for successes but little blame for failures.
  • A premortem assumes that a year has passed, you implemented the plan as it exists, and the outcome was a disaster. It explains why.
  • This counters overconfident optimism by escaping groupthink, and unleashing the imagination of knowledgeable individuals in a much needed direction.

Part 4: Choices

Ch 25: Bernoulli’s Errors

  • Choices between simple gambles provide a simple model that shares important features with the more complex decisions that researchers actually aim to understand.
  • Expected utility theory defined axioms of rationality. Prospect theory examines why we deviate this theory under risk.
  • A risk-averse decision maker will choose a sure thing that is less than the expected value of a gamble, paying a premium to avoid uncertainty.
  • Bernoulli proposed that the psychological gamble isn’t the weighted average of the monetary values, but the weighted average of the utility of these outcomes.
  • Prospect theory states that happiness is determined by the recent change in wealth, and not its absolute value. It defines a reference point for happiness.

Ch 26: Prospect Theory

  • You know you have made a theoretical advance when you can no longer reconstruct why you failed for so long to see the obvious.
  • Your personal wealth does not determine your attitudes to gains and losses. We like winning and dislike losing. And we dislike losing more than you like winning.
  • In financial outcomes, the reference point can be the status quo, what you expect, or what you feel entitled to. Better outcomes are gains. Worse outcomes are losses.
  • A principle of diminishing sensitivity applies to changes of wealth, both for gains and losses.
  • We typically only accept a bet if its loss aversion ratio, or its ratio of gains to losses, is a minimum between 1.5 and 2.5.
  • In mixed gambles, where both a gain and a loss are possible, loss aversion causes extremely risk-averse choices.
  • In bad choices, where a sure loss is compared to a larger loss that is merely possible, diminishing sensitivity causes risk seeking.
  • But prospect theory cannot deal with disappointment. It also cannot deal with regret, such as losing the gamble and foregoing the sure option.

Ch 27: The Endowment Effect

  • Indifference curves assume that your utility depends entirely on the present situation, and that the evaluation of a possible job does not depend on your current job.
  • In labor negotiations and bargaining, the reference point and loss aversion is well understood. But their omission in most scenarios is theory-induced blindness.
  • Loss aversions says the disadvantages of a change loom larger than its advantages. This introduces a bias that favors the status quo.
  • Under the endowment effect, owning a good increases its value. Your minimum selling price greatly exceeds your maximum buying price, violating rational economic behavior.
  • The endowment effect applies to goods “for use,” or consumed or enjoyed. It doesn’t apply to goods “for exchange,” or traded for other goods.
  • Loss aversion is built into the automatic evaluations of System 1. Consider the baby who holds on fiercely to a toy and shows agitation when it is taken away.
  • Selling goods activates regions of the brain that are associated with disgust as pain. Buying activates these areas if the price is too high.
  • Veteran traders are unaffected by the endowment effect. They ask “How much do I want to have this good, compared with other things I could have instead?”
  • Being poor is living below one’s reference point. Small amounts of money they receive are a reduced loss, not a gain. All their choices, then, are between losses.

Ch 28: Bad Events

  • Our brain prioritizes threats above opportunities. It can process hostile images that we can’t consciously see, and can quickly pick hostile faces out from a crowd.
  • Even symbolic threats evoke in attenuated form many reactions of the real thing, including fractional tendencies to avoid or approach, recoil or lean forward.
  • Given a goal, not achieving it is a loss, while exceeding it is a gain. But the aversion to the failure of not reaching a goal is stronger than the desire to exceed it.
  • Negotiations are difficult because losses by one side induce pain that exceeds the pleasure of the gains by the other side.
  • An existing wage, price, or rent sets a reference point that is entitled. We think that exploiting market power to impose losses on others is unacceptable.
  • A firm has its own entitlement, which is to retain its current profit. But we think it’s not unfair for a firm to reduce its workers’ wages when its profitability is falling.
  • If a merchant lowers the price of a good, customers who bought at the higher price think of themselves as having sustained a loss that is more than appropriate.
  • Punishing one stranger for behaving unfairly to another stranger activates the pleasure centers of the brain.

Ch 29: The Fourfold Pattern

  • When mapping decision weights to outcome probabilities, they are not equal in value, contrary to the expectation principle.
  • We overweight unlikely events, which illustrates the possibility effect. We underweight highly likely events, which illustrates the certainty effect.
  • We also have inadequate sensitivity to intermediate probabilities. The range of decision weights is much smaller than the range of probabilities.
  • Paying a premium to eliminate a worry with certainty is compatible with the psychology of worry but not with the rational model.
  • Between a sure loss and a gamble with a high probability of a larger loss, diminishing sensitivity makes the sure loss more aversive, and the certainty effect reduces the aversiveness of the gamble.
  • This explains why people accept a high probability of making things worse for a small hope of avoiding a large loss, which can turn manageable failures into disasters.
  • These same two factors enhance the attractiveness of the sure thing and reduce the attractiveness of the gamble when the out come is positive.
  • Systematic deviations from expected value are costly in the long run. This rule applies to both risk aversion and to risk seeking.

Ch 30: Rare Events

  • Emotion and vividness influence fluency, availability, and judgments of probability, and thus account for our excessive response to the few rare events we don’t ignore.
  • People overestimate the probabilities of unlikely events, and overweight unlikely events in their decisions.
  • If the event we are asked to estimate is very unlikely, we instead focus on its alternative. We focus on the odd, different, and unusual.
  • A rich and vivid representation of the outcome, whether or not it is emotional, reduces the role of probability in the evaluation of an uncertain prospect.
  • The denominator effect is when your attention is drawn to one outcome that “stands out,” and you do not assess the alternative outcome with the same care.
  • We weight low-probability events more when stated in terms of relative frequencies (how many) than when stated in more abstract terms of “chances,” “risk,” and “probability” (how likely).
  • In choice from experience, instead of choices from description, we are exposed to variable outcomes from the same source, and so we do not overweight rare events.

Ch 31: Risk Policies

  • Every simple choice formulated as gains and losses can be deconstructed in innumerable ways into a combination of choices, yielding preferences that are likely to be inconsistent.
  • If paying a premium for sure gains and to avoid a sure loss come out of the same pocket, the discrepant attitudes are unlikely to be optimal.
  • We prefer narrow framing, or considering a sequence of simple decisions, even when we must entertain broad framing, or considering the decisions jointly.
  • Narrow framing of gambles leads to loss aversion. Broad framing treats each gamble as one of many, blunting the emotional reaction to loss and increasing the tolerance of risk.
  • Closely following daily fluctuations is a losing proposition, because the pain of small losses exceeds the pleasure of equally frequent small gains.
  • A risk policy eliminates the pain of occasional loss by the thought that the policy that left you exposed to it will be advantageous to you over the long run.
  • While an outside view protects you from the exaggerated optimism of the planning fallacy, a risk policy protects you from the exaggerated caution induced by loss aversion.

Ch 32: Keeping Score

  • The emotion that people attach to the state of our mental accounts are not acknowledged in standard economic theory.
  • The disposition effect is the bias in finance to sell winners rather than losers, and is an instance of narrow framing.
  • The sunk-cost fallacy invests additional resources in a losing account when better investments are available. It prefers an unfavorable gamble to a sure loss.
  • Members of a board will replace a CEO with one who does not carry the same mental accounts and is therefore better able to ignore sunk costs of past involvements.
  • A poignant story evokes more regret if it involves unusual events, because such events attract attention and are easier to undo in our imagination.
  • People expect to have stronger emotional reactions to an outcome that is produced by action than to the same reaction when it is produced by inaction.
  • When you deviate from the default, you can easily imagine the norm. If the default is associated with bad consequences, the discrepancy can be a source of painful emotions.
  • You will be more loss averse in situations that are more important than money, and more reluctant to sell important endowments when it might lead to an awful outcome.
  • To inoculate yourself against regret, remind yourself of its possibility and that things can go badly, and preclude any hindsight that might cause it.

Ch 33: Reversals

  • We normally experience situations in which contrasting alternatives are absent, and so moral intuitions that come to your mind in different scenarios are inconsistent.
  • Preference reversal can occur if joint evaluation focuses attention on a situational aspect that is less salient than in single evaluation.
  • The emotional reactions of System 1 likely determine single evaluation, while the comparison and careful evaluation required by joint evaluation calls for System 2.
  • Judgments and preferences are coherent within categories but potentially incoherent when the objects are evaluated belonging to different categories.
  • The evaluability hypothesis states that some attributes are only given weight in a joint evaluation because they are not evaluable on their own.
  • Be wary of joint evaluation when someone who controls what you see has a vested interest in what you choose.

Ch 34: Frames and Reality

  • Losses evoke stronger negative feelings than costs do, and so the cost of a lottery ticket that did not win is more acceptable than losing a gamble.
  • “Rational” subjects, which are least susceptible to framing effects, showed enhanced activity in the frontal area of the brain that is implicated in combining emotion and reasoning.
  • Reframing is effortful and System 2 is normally lazy. Most of us passively accept decisions as they are framed, and so our preferences are frame-bound and not reality-bound.
  • Broader frames and inclusive accounts generally lead to more rational decisions.
  • Opt-in versus opt-out is another framing effect. We check a box if we’ve already decided what we wish to do. But if unprepared for the question, laziness prefers the default.

Part 5: Two Selves

Ch 35: Two Selves

  • The decision maker who pays different amounts to achieve the same gain or be spared the same loss is making a mistake.
  • The peak-end rule states that a global retrospective rating is dominated by the highest score (the peak) and the final score (the end).
  • The duration neglect states that the length of the evaluated activity has no effect whatsoever on its evaluation.
  • The experiencing self, which evaluates each moment, does not have a voice. The remembering self, which keeps score and governs what we learn, makes our decisions.
  • What we learn from the past is to maximize the qualities of our future memories, not necessarily our future experience.
  • This is a feature of System 1, which represents sets by averages, norms, and prototypes. Not by sums.
  • In some cases rats who can stimulate their brain by pressing a lever will die of starvation without taking a break to feed themselves.
  • A memory that neglects duration will not serve our preference for long pleasures and short pains.

Ch 36: Life as a Story

  • Duration neglect is normal in a story. A story is about significant events and memorable events like its ending, not about time passing.
  • The peak-end rule and duration effect also influence our evaluation of others’ lives.
  • Vacation pictures may be important to the remembering self. The photographer does not view the scene as a moment to be savored but as a future memory to be designed.
  • We use the word “memorable” to describe vacation highlights, which explicitly reveals the goal of the experience.

Ch 37: Experienced Well-Being

  • A small fraction of the population endures most of the suffering, whether because of illness, an unhappy temperament, or misfortunes or tragedies.
  • Our emotional state is largely determined by what we attend to, and we are normally focused on our current activity and immediate environment.
  • Less commuting, greater availability of child care, and improved socializing opportunities can reduce the “unhappiness index” of a society.
  • From Gallup data, some life aspects, such as education, is associated with a higher evaluation of one’s life, but not with greater experienced well-being.
  • Religion has favorable impact on both positive affect and stress reduction than on life evaluation, but provides no reduction of feelings of depression or worry.
  • Being poor makes one miserable. A salary beyond $75,000 may enhance one’s life satisfaction, but it does not improve experienced well-being.
  • Higher income allows the purchase of many pleasures, but it also reduces the ability to enjoy the smaller things in life. Therefore the emotional experience is unchanged.

Ch 38: Thinking About Life

  • Affective forecasting is the forecast of one’s personal state in the future. An error happens when you think statistics don’t apply to you.
  • The score you assign to your life is determined by a small sample of highly available ideas, and not a careful weighing of the domains of your life.
  • Both experienced temperament and life satisfaction are largely determined by the genetics of temperament.
  • Setting goals that are especially difficult to attain leads to a dissatisfied adulthood. We must consider what people want in the concept of well-being.
  • The focusing illusion states that nothing in life is as important as you think it is when you are thinking about it.
  • This illusion can cause people to be wrong about their present state of well-being as well as the happiness of others, and about their own happiness in the future.
  • The term miswanting describes bad choices that arise from the errors of affective forecasting. The focusing illusion is a rich source of it.
  • The focusing illusion favors goods or experiences that are initially exciting but may lose their appeal. It appreciates less experiences that retain their attention value.