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The origins of Sociophysics. What is the minimum model of an individual. The recognition project

The origins of Sociophysics. What is the minimum model of an individual. The recognition project

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  • 1. Discovering the Second Foundation The origins of sociophysics Franco Bagnoli1 Andrea Guazzini1,2 (1) Laboratorio Fisica dei Sistemi Complessi - Dip. Energetica and CSDC, Universit` di Firenze a (2) IIT, CNR, PisaBagnoli, Guazzini (CSDC & IIT) Second Foundation 17 novembre 2011 1 / 32
  • 2. The Foundations Cycle In 1942 Asimov started the Foundations cycle. Inspired by The History of the Decline and Fall of the Roman Empire (Edward Gibbon), the cycle spans about 500 years of history in a far future. The story begins when Hari Seldon, a mathematician, proves the theoretical possibility to predict the future of a society on a mathematical basis. After various vicissitudes, Hari manages to establish two foundations, at the “opposite ends of the galaxy”. The goal is that of shortening the period of chaos after the expected fall of the Galactic Empire from the estimated 30,000 years to only 1,000 years. Bagnoli, Guazzini (CSDC & IIT) Second Foundation 17 novembre 2011 2 / 32
  • 3. The Foundations The two foundations have very different tasks. The first is asked to preserve the technical knowledge, and is destined to dominate the nearby planets (and then the whole ex-empire). The Second Foundation instead must remain secret. It is formed by mathematicians, who have the task of writing the equations which model in detail the future of the humanity, and correcting the “deviations”. Of course not all goes smoothly. The First Foundation must face some Seldon crisis (bifurcation points?), and they succeed with the secret help of the Second Foundation, which has developed psychological methods to manipulate people. There is also a war of the First Foundation against the Second, because the former do not want to be manipulated by the latter. Bagnoli, Guazzini (CSDC & IIT) Second Foundation 17 novembre 2011 3 / 32
  • 4. FuturICTOnly fantasies? The flagship project FuturICT, which could be financedby the European Union with 1 billion euros in 10 years, seeks similar goals. FuturICT will build a sophisticated simulation, visualization and participation platform, called the living earth platform ( planetary-scale data collection and simulations). This platform will power crisis observatories, to detect and mitigate crises, and participatory platforms, to support the decision-making of policy-makers, business people and citizens, and to facilitate a better social, economic and political participation. Bagnoli, Guazzini (CSDC & IIT) Second Foundation 17 novembre 2011 4 / 32
  • 5. The psycohistory The fundamental intuition of Hari Seldon is that the various planets can be considered uncorrelated. Asimov was a chemist, and in fact this approximation is the basis of “chemical” equations (mass law). He says explicity: psycohistory is like the gas law for humans. But we know that microscopic symmetries and constraints reflect on macroscopic behavior. And as happens in chemistry, Asimov-Seldon recommends to apply these equations only to very large populations (and to keep this practice secret!). So, the main question is: which is the simplest model of an human? Bagnoli, Guazzini (CSDC & IIT) Second Foundation 17 novembre 2011 5 / 32
  • 6. Are humans smart? Humans love to think to be intelligent and to take rational decisions. Actually, rational thinking is quite slow and computational demanding. We can discriminate the “usage” of cognitive capabilities by fMRI and response times. For instance, a good ping-pong player never “thinks” to the next move. We cannot avoid unconscious knowledge. Some partially “blind” people (blind sight) can detect movements even if they cannot “understand” what they see. Human recognition needs emotional components, otherwise the subjects cannot even recognise themselves in a mirror. Bagnoli, Guazzini (CSDC & IIT) Second Foundation 17 novembre 2011 6 / 32
  • 7. Heuristics as weak intelligence We have to take a lot of decisions in everyday life. Generally, these decision are satisfactory, but we all experience frustration for having chosen the bad choice, or having been cheated. Twerski and Kahneman pointed out the existence of heuristics: rules of thumb that are used everyday, like for instance “prejudicial judgements” based on appearances. Clearly, if applied to a wrong context, heuristics may fail spectacularly. Bagnoli, Guazzini (CSDC & IIT) Second Foundation 17 novembre 2011 7 / 32
  • 8. Examples of classic heuristics: anchoring When taking a decision, we heavily rely on just one piece of information (the one easier to recall), and only in a second moment we “adjust” the answer according to other factors. A classical example is the question Estimate the probability of death by lung cancer and by vehicle accidents. People tends to assign a higher probability to car accidents (since they are much more commonly reported by press) but lung cancer causes about 3 times more deaths than cars. Bagnoli, Guazzini (CSDC & IIT) Second Foundation 17 novembre 2011 8 / 32
  • 9. Representativeness Although we always assume a probabilistic world, we are insensitive to prior probability of outcomes. We ignore preexisting distribution of categories or base rate frequencies. Bayes’ theorem is not easily understood. We are insensitive to sample size. We tend to draw strong inferences from small number of cases We have a misconception of chance: gambler’s fallacy. We think that chance will “correct” a series of “rare” events. We have a misconception of regression. We deny chance as a factor causing extreme outcome. Bagnoli, Guazzini (CSDC & IIT) Second Foundation 17 novembre 2011 9 / 32
  • 10. Representativeness examples Is the roulette sequence “6, 6, 6” mo- re or less probable than “10, 27, 36”? After six “6”’s, would you prefer to bet on the 6 or on any other number? All kind of stereotypes: black people vs. white people, immigrants, etc. There is a murder in New York, and the DNA test (say 99.99% accuracy both for false positive and false ne- gatives) is positive for the defendant. There are no other cues. Which is the probability that the defendant is guilty? Bagnoli, Guazzini (CSDC & IIT) Second Foundation 17 novembre 2011 10 / 32
  • 11. Heuristics as fast and frugal processing At present, heuristics have a better : they can be considered as optimized methods of saving computational resourced and giving faster answers (Gigerenzer). Many everyday problems would require unbounded rationality to be solved, and a large time for samplig all possibilities. But we do not try every possible partner when choosing a mate (nor a tiny fraction of them...). In a variable world, sometimes the “rules of thumb” are really better then the weighted methods taught by economists. In real world, with redundant information, Bayes’ theorem and “rational” algorithms quickly become mathematically complex and computationally intractable. Bagnoli, Guazzini (CSDC & IIT) Second Foundation 17 novembre 2011 11 / 32
  • 12. Recognition heuristics In 1991 Gigerenzer and Goldstein asked students in California and Germany to estimate whether S. Diego or S. Antonio had a larger population. German students were much more accurate, simply because most of them did not know S. Antonio. The same test was performed on soccer outcome, financial estimates, etc. But Oppenheim (2003) showed Which town has a larger that we use also other cues. If population? asked to judge between a kno- A B wn little city and a fictitious one, Erfurt Witten most of people would choose the Trier Duisburg non-existing city. Bochum Neuss In any case, there is informa- Krefeld Leipzig tion in ignorance (and probably Darmstadt Mannheim advantages in forgetting). Cottbus Rostock Bagnoli, Guazzini (CSDC & IIT) Second Foundation 17 novembre 2011 12 / 32
  • 13. Take the best We often have to choose the best (buy a new car). The most rational thing to do is to maximise a weighted score. The weights can be extracted by past experiences. Example: a man with severe chest pain should be sent to the coronary care unit or a regular nursing bed?. This method based resulted slow, and with a 50% efficiency. A simpler decision tree is much more effective: first consider the most important factor – had the patient experienced hart attacks? If yes, go to intensive unit. Then the second: is the pain localized in chest? If yes, go to intensive unit, etc. etc. This is why advertisers focus on irrelevant details for selling cars... Bagnoli, Guazzini (CSDC & IIT) Second Foundation 17 novembre 2011 13 / 32
  • 14. Darwin’s weighted decision Bagnoli, Guazzini (CSDC & IIT) Second Foundation 17 novembre 2011 14 / 32
  • 15. Where do heuristics come from? Heuristics, like all our brain, is a product of selection. We are at hand with natural selection, i.e., competition for surviving. But in order to select a trait in this way, nature has to literally kill everyone not carrying that trait before reproductive age. A much less cruel but more effective selection is the sexual one. In many species, just a tiny fraction of individuals (the leading male, for instance) do actually reproduce. In others, many have a chance of reproducing, but someone is more successful (bunga bunga!) Bagnoli, Guazzini (CSDC & IIT) Second Foundation 17 novembre 2011 15 / 32
  • 16. Sexual brain Sexual selection is so effective, that a tiny improvement in attracting the opposite sex can result in larger offspring. This is the origin of the extreme sexual ornaments found in all sexually-reproducing species. For humans, the principal ornaments are (probably) power and dexterity (mainly linguistic): poetry, songs,... It has been suggested that our large brain (with art and all useless brain products) is just a sexual ornament. Bagnoli, Guazzini (CSDC & IIT) Second Foundation 17 novembre 2011 16 / 32
  • 17. Viral brain One of the main social (and sexual) attractive character is captive story-telling (like jokes, hoaxes, epic novels...). It is easy to recognize in myths and hoaxes the “eigenvectors” of out mind (the “memes”). For instance, an already interesting fact about a cannon that launches chicken bodies to test aircraft window resistance, and is then rented to test UK high-speed trains becomes ... the frozen chicken myth. Bagnoli, Guazzini (CSDC & IIT) Second Foundation 17 novembre 2011 17 / 32
  • 18. Machiavellic brain Monkey and ape societies are often complex social systems. In such cases, the leading position is conquered by means of alliances, not by pure muscle power. This implies large cognitive power, since one needs to elaborate not only information about others, but also their mutual relationships. Actually, the size of frontal cortex (the “monkey” brain) correlates well with the group size (from which one obtains the Dunbar number). Bagnoli, Guazzini (CSDC & IIT) Second Foundation 17 novembre 2011 18 / 32
  • 19. Logic brainWe find logic problems hard. How many cards should one turn (at minimum) to check if the following rule is violated? Red cards have an even digit on the back. Bagnoli, Guazzini (CSDC & IIT) Second Foundation 17 novembre 2011 19 / 32
  • 20. Social brainBut social tasks are easier... How many situations should a policeman investigate (at minimum) to check if the following rule is violated? People less than 18 cannot drink alcohol. Bagnoli, Guazzini (CSDC & IIT) Second Foundation 17 novembre 2011 20 / 32
  • 21. Social brain: the ultimatum game In this game, you are given 10$, and you have to decide how many dollars you will offer to a third person. He/she can accept and you share the money, or he/she can refuse and in this case both of you will loose everything. How much would you offer? If you were the third person, up to how much would you accept? What is the most rational thing to do? Bagnoli, Guazzini (CSDC & IIT) Second Foundation 17 novembre 2011 21 / 32
  • 22. Social brain: The dictator game This is the same as the ultimatum, but in this case the third person cannot refuse. How much would you offer in this case? Before answering, consider the following possibilities: This third person is sitting near to you. This third person is somewhere far from you. You personally know this person and you know that in some future time he/she can play you present role. You know that you’ll never meet again this person. You know that your choice will be made public in your school/office. What is the most rational thing to do? Bagnoli, Guazzini (CSDC & IIT) Second Foundation 17 novembre 2011 22 / 32
  • 23. mechanisms: the Recognition project The RECOGNITION project concerns new approaches for embedding self-awareness in ICT systems. This will be based on the cognitive processes that the human species exhibits for self-awareness, seeking to exploit the fact that humans are ultimately the fundamental basis for high performance autonomic processes. This is due to the cognitive ability of the brain to efficiently assert relevance (or irrelevance), extract knowledge and take appropriate decisions, when faced with partial information and disparate stimuli. http://www.recognition-project.eu Bagnoli, Guazzini (CSDC & IIT) Second Foundation 17 novembre 2011 23 / 32
  • 24. Perceptive dissonance How many triangles are there? Bagnoli, Guazzini (CSDC & IIT) Second Foundation 17 novembre 2011 24 / 32
  • 25. Perceptive-cognitive dissonance Name colors as fast as you can Bagnoli, Guazzini (CSDC & IIT) Second Foundation 17 novembre 2011 25 / 32
  • 26. Perceptive-cognitive dissonance Name colors as fast as you canBLUE YELLOW RED GREENGREEN RED YELLOW BLUERED GREEN BLUE YELLOW Bagnoli, Guazzini (CSDC & IIT) Second Foundation 17 novembre 2011 26 / 32
  • 27. Perceptive-cognitive dissonance Name colors as fast as you canBLUE YELLOW GREEN REDGREEN RED BLUE YELLOWRED GREEN YELLOW BLUE Bagnoli, Guazzini (CSDC & IIT) Second Foundation 17 novembre 2011 27 / 32
  • 28. Cognitive dissonance Bagnoli, Guazzini (CSDC & IIT) Second Foundation 17 novembre 2011 28 / 32
  • 29. Cognitive processes of information analysis Timescales (reaction times) Unconscious knowledge (perception and pre-attentive activations): fast (< 0.5 ms). Conscious knowledge (reasoning): medium (from seconds to hours). Learning/development: slow (from minutes to month). Cost (Cognitive Economy Principle - amount of neural activation) Unconscious knowledge: light (small and local activations). Conscious knowledge: heavy (large and diffused activations). Learning/development: very heavy (diffused activations). Evolutionary Features (cognitive development) Unconscious knowledge: critical period and “classical-Hebbian” learning only. Conscious knowledge: trial and error, observation/imitation and induction learning. Learning/development: fixed hard-wired rules. Bagnoli, Guazzini (CSDC & IIT) Second Foundation 17 novembre 2011 29 / 32
  • 30. Schemes and heuristics We denote with the term schemes the procedures that manage information and perform actions, and by heuristics the management of schemes (activation, modification, learning). We classify schemes and heuristics in three modules: in the first one we put the structures that deal with input, in the second the actual management of information and actions and in the third the learning. This division is consistent with the the response times, but we think that there is a common structure of heuristics and schemes Bagnoli, Guazzini (CSDC & IIT) Second Foundation 17 novembre 2011 30 / 32
  • 31. Schemes and heuristics Bagnoli, Guazzini (CSDC & IIT) Second Foundation 17 novembre 2011 31 / 32
  • 32. Other work in progresswith Andrea Guazzini, Duccio Fanelli, Timoteo Carletti, Pietro Li´, oEmanuele Massaro, Alessandro Cini Experiments/models on small groups dynamics. Risk perception & epidemics. Opinion dynamics (chaos). Opinion formation. Community detection. At-the-device (smart phones) implementation of heuristics.You may find some material on www.complexworld.net or you may writeto me franco.bagnoli@unifi.it (franco.bagnoli@complexworld.net) Bagnoli, Guazzini (CSDC & IIT) Second Foundation 17 novembre 2011 32 / 32