Mind computer societies


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Mind computer societies

  1. 1. Mind, computers and communities How psychology may help computer science, and permit global simulations of societies Franco Bagnoli Laboratorio Fisica dei Sistemi Complessi - Dip. Energetica e CSDC, Universit` di Firenze a www.complexworld.netFranco BagnoliMind, computers and communities
  2. 2. Psychohistory In the year 1951 Asimov published the first volume of the Foundation cycle. The protagonist of the whole opera (7 volumes, 500 years) is Hari Seldon, the inventor of the psychohistory. It is a “science” that permits to combine history, sociology, and statistics to make mathematical predictions about the future behavior of very large groups of people, such as the Galactic Empire. This forecasting possibility allows Seldon and his later followers to change the “future”, and avoid/mitigate crisis.Franco BagnoliMind, computers and communities
  3. 3. Is psychohistory possible? Although Asimov’s novels deals with telepathy and other non-scientific issues, the idea of global simulations and predictions is taken seriously. The European flagship project FuturICT, that might be funded with a billion euros in 10 years, states: 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. Essentially, a global social empowerment program.Franco BagnoliMind, computers and communities
  4. 4. Psychohistory again It is interesting to consider the premises of psychohistory (mathematical sociology). Psycho-history was the quintessence of sociology, it was the science of human behavior reduced to mathematical equations... The laws of history are as absolute as the laws of physics, and if the probabilities of error are greater, it is only because history does not deal with as many humans as physics does atoms, so that individual variations count for more.Franco BagnoliMind, computers and communities
  5. 5. Physics of history Psychohistory is similar to gas theory: The population whose behavior was modeled should be sufficiently large (at least 1010 individuals). The population should remain in ignorance of the results of the application of psychohistorical analyses. It assumes that Human Beings are the only sentient intelligences in the Galaxy (no mutants, robots, etc.).Franco BagnoliMind, computers and communities
  6. 6. Is it only imagination? In the ’50, Asimov considered only “equations”, with an “electronic” device (the Prime Radiant) that helped in visualization and annotation (say, a computer screen..). Asimov probably considered differential equations, say, epidemic modeling. However, after the use of computers, researchers discovered some drawbacks: Differential equations represent a sort of “mean field”, or moment expansions. They are not very appropriate for small numbers (as stated also by Asimov), or very non-linear dynamics. Spatial effects are even more difficult to be captured by partial differential equations. One could resort to agent-based simulations (the current trend): one agent for each person (an “avatar”). Kind of Matrix. But even in this case there are conceptual and practical difficulties.Franco BagnoliMind, computers and communities
  7. 7. Difficulties Noise and chaos: we are not able to simulate an individual with sufficient detail to make the model deterministic, so we have to insert stochastic components. In any case, the resulting dynamics would probably be chaotic. Detailed individual models require a lot of parameters, and therefore a lot of measurements (some of which are quite hard to be performed). Auto-organization: people behavior is extremely sensitive to collective effects. Let think to markets: the price of an item is not due to its value, but to the value attributed by other participants. Such effects are hard to include, ans in any case, if the simulations can affect the behavior of the system, it should be included in a self-consistent way (this the the reason for which Asimov supposed that the foundation had to remain secret). Little knowledge of the individual behavior (to be investigated in the following).Franco BagnoliMind, computers and communities
  8. 8. Good news There are also some arguments in favor of a success Universality: many of the particular details of the individual should not affect the dynamics of a large population. However, microscopic “constraints” may well reflect in the large population dynamics (for instance fermionic Pauli exclusion principle determines the small electron contribution to the specific heat of metals). Global measurement: electronic sensors and devices, electronic transactions, internet, etc. allow to perform detailed measurements on individual behavior, an essential element to validate any model. Delegation to software. Many of our acts are actually delegated to software, often embedded in cars, browsers, phones, etc. This is another point of integration between psychology and computer science (to be explored below), but makes predictions easier.Franco BagnoliMind, computers and communities
  9. 9. Individual behavior The starting point of any analysis should be the individual (i.e., psychology). Evolutionary constraints give the main framework, through genetics, womb gestation and education. The knowledge of these factors is still limited. The brain is a complex multi-level object, not easy to be modeled at a global level. Most of modeling is done statistically using linear models (for instance, factorial analysis). Learning makes individual “state machines”, so that repeating measurements is almost impossible. Learning is generally absent in statistical modeling.Franco BagnoliMind, computers and communities
  10. 10. Evolutionary constraints Our brain was not selected to cope with algebra, path integrals or TV recording programs. Some recent investigation suggests: Probability reasoning, in terms of natural frequencies (one case over ten, not 0.1). Social tasks (see Wason selection task), not abstract reasoning. Speech-oriented interactions (mainly recreational). Mating behavior (indeed the strongest selection factor). Social conformism (fashion, religion, politics) vs individualism, a with a “bonus” for small innovations (fashion innovation). Kin, mutual and reputation cooperation, leading to group selection (strong cooperation inside a group, racism against other groups. Cross-over (synesthesia) among tasks. This could be the origin of innovation.Franco BagnoliMind, computers and communities
  11. 11. Mechanisms Human mind is not rational (unless forced). As revealed by response times, we can classify the level of mental involvement as reflexes, mental scheme, heuristics, meta-heuristics... Heuristics (say: fast and frugal, anchoring, etc.) allows quick responses with bounded resources in uncertain contexts. We can learn a lot from them, and apply the outcome to ICT. Clearly, they sometimes fail spectacularly... That’s so human... The implementation of human heuristic is particularly appreciated in devices that has to interact with humans (or be delegated..)Franco BagnoliMind, computers and communities
  12. 12. Failures Epidemic spreading is one of the biggest failures of psychohistory.. In classical epidemic modeling, there is a threshold related to the infectivity of the disease and the average number of contacts. Most of human social networks are scale-free, with a diverging connectivity. So, for any infectivity rate, a disease should become a pandemy (like bubonic pest in medieval times). But actually (modern) people react to epidemics by changing the social network so to prevent pandemies. Risk perception acts as a main factor..Franco BagnoliMind, computers and communities
  13. 13. Delegation People like to delegate boring tasks to machines (computers, devices). So we can expect more and more delegation to cars, domotic,, web searches and mainly to portable devices (e.g. smarthphones, audio devices). Let’s think to music for instance: people like to have a portable radio station that select the “right” music. “Right” of course depends on the individual, past and recent experiences, mood, status, available clips (copyright), etc. This is prototypic of future home use of ICT. Trading is another crucial playground for human heuristics (it depends on other human reactions, even if economic schools try to make it inhuman..)Franco BagnoliMind, computers and communities
  14. 14. Human social scales As said, most of human-generated networks exhibit a certain degree of scale independence, with long tails. However, there are a certain number of “magical” numbers in human activities: the size of a chatting group (around four, as most of card games), the size of a small group (from a chatting group to around twelve, as apostols – thirteen is already too many), the size of a community (about 150, Dunbar’s number, the presumable size of a good-knowledge memory). To my knowledge, little is known about the actual dynamics of such groups (and how they could be modeled starting from cognitive assumptions).Franco BagnoliMind, computers and communities
  15. 15. Small group dynamics In particular, small group dynamics is interesting: Temporally quite complex, while community-size dynamics is statistically much better determined. A small group has only a short time horizon. It is however the “drive” of a community, together with chatting groups and couple communication. Interactions are mainly non-informative and somewhat ritual.Franco BagnoliMind, computers and communities
  16. 16. The RECOGNITION project It is part of the AWARENESS Fet proactive initiative. It aims at porting the knowledge about humans (psychology) to the ICT domain and implementing awareness at the device. Implementation of human heuristics in ICT world, in particular the “fast and frugal” protocol with bounded rationality. Developing and implementing the concept of data centric approach (data should not be separated by their elaboration structures). Implementation of elaboration “at the device” (saY: cars, smartphones), not relying on central servers.Franco BagnoliMind, computers and communities
  17. 17. Web measurement In order to quantitative study human dynamics we need a lot of data. One of the sources is the web sphere People reveal a lot of personal data to Internet (say, facebook). we can have quite a good timing measurements (mental activation). Moreover, data are already in digital form. However, a compromize is needed between non-verbal content and environental control (think to second life vs. textual chat). A good semantic analyzer would be useful (but quite hard to be developed): most of effective data analysis is done by humans (see Google page rank mechanism).Franco BagnoliMind, computers and communities
  18. 18. Implementation It is not easy to implement such a approach. We are working on the following topics: Role of risk perception in epidemics. Opinion dynamics, role of affinity, peace makers and anticonformism. Opinion anticipation, origin of personality factors, extension to nonlinear predictors [De Gustibus] From attractor dynamcs to feed forward networks and the origin of synsthesia. Heuristics for community detection [RECOGNITION]. Personalized audio suggestions - wikiradio [RECOGNITION].Franco BagnoliMind, computers and communities
  19. 19. Conclusions Psychology (from cognitive science to sociology) could become a central (quantitative) discipline for ICT. The field of human-inspired computing includes also physics of complex systems, biology, evolutionary theory, computer science, linguistics and is related to all humanities (they are product of the human mind..) Unfortunately, no school offers such a study program...Franco BagnoliMind, computers and communities