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Toward a Civilization of Collective Intelligence

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Toward a Civilization of Collective Intelligence

  1. 1. Toward a Civiliza-on of   Collec-ve Intelligence  Prof. Pierre Lévy (Twi;er: @plevy)  Fellow of the Royal Society of Canada  Canada Research Chair in Collec-ve Intelligence  University of O;awa 
  2. 2. Evolu-on of Media  (From 2000) Ubiquity, interconnection and animation of cultural signs (software). Social Computing. New sign systems. Knowledge economy. (From 1500) massive technical self-reproduction and diffusion of the alphabet and other cultural signs. New languages (animated images, etc.) Scientific notation progress. Industrial economy. (From - 1000) Digitization and universalization of writing reduced to thirty phonetic signs. Notation of numbers by position, zero. Commercial economy. (From - 3000) Autonomous technical memory of language. Ideographic Signs. Numerals, measurement units. Agricultural economy. (From - 300 000) myths, rites, oral transmission, memory inscribed in matter. Icons. Arts of memory. Hunting-gathering economy.
  3. 3. Social Media / Social Compu-ng Features  •  Global sharing : photo (Flickr), video (Youtube), music / P2P (Bi;orrent),  bookmarks (Delicious), knowledge (Wikipedia, Freebase)  •  Distributed crea3on : user‐generated content, blogs (Wordpress), podcasts,  ci-zen journalism  •  Social networking : social networks (Facebook, Myspace, Linkedin, Xing,  Pulse, NING...), virtual worlds (Second life), instant micro‐blogging (Twi;er)  •  Streaming (Twi;er, Facebook, Friendfeed, Atom or RSS Feeds)   •  Mass collabora3on : wikis, opensourcing, crowdsourcing  •  Collabora3ve assessment : forums, ra-ngs, reviews (Bazaarvoice)  •  Social bookmarking / tagging / categoriza3on (Digg, Delicious, Twine, Diigo,  Stumbleupon, Flickr, YouTube...)  •  Cloud compu3ng : data and applica-ons are on‐line in huge distributed  data‐centers (Google, Yahoo, Facebook, Twi;er, Amazon...). SoZware as a  service. Scalability. 
  4. 4. Web n.0, Social Compu-ng, Crowdsourcing : A Global Conversa-on ?  Yes, the digital conversa-on ! But what about seman-c interoperability:  different languages, folksonomies, classifica-ons, ontologies...? 
  5. 5. Cyberspace Evolution Semantic Space Interconnec-on between ideas (via seman-c tags). " Uniform Seman-c Locator = IEML * concept address ** Collaborative societies of semantic agents, subject-centric computation. 2015  Collective intelligence growth. Augmentation of sense-making. Web Interconnec-on between documents (+ data) Uniform Resource Locator = h;p:// page address. Centralized search engines, browsers. 1995  Global multimedia public sphere. Internet Interconnec-on between computers. Internet Protocol = server address. Routers, user-friendly PC applications 1980  Personal computing. Virtual communities. " Digital media convergence. Computer Interconnec-on between transistors. Computer memory = bit address. " Operating systems, programming languages 1950  Augmentation of arithmetical and logical processing.
  6. 6. Computational Collective Intelligence Seman-c  global meta‐ group of  Space  IEML / USLs  language  concepts  global meta‐ WWW  linked data  HTTP / URLs  database  global meta‐ society of  Internet  computer  automata  TCP / IP  symbolic  pervasive comp.  Compu-ng  Chips / OS  manipula-on  (mobiles, things,  Bits addresses  automata  robots...)   Augmenta-on  Objects in  Addressing  of CI  rela-on  system 
  7. 7. Toward a CI Science  Cyberspace  scien-fic observatory / digital mirror of CI  Reflexive Collec-ve Intelligence  driver of human development  Human Development  prosperity, health, educa-on, security, peace,  environment, cultural heritages, research, innova-on... 
  8. 8. aspiration creation creation collective creation Intelligence creation aspiration Collec-ve Intelligence Dynamics 
  9. 9. Governance / values Rights / duties Will networks ETHICAL CAPITAL  Arts Finance Sciences Competence Knowledge networks Power networks EPISTEMIC  PRACTICAL  CAPITAL   CAPITAL  Collective Intelligence CULTURAL  CAPITAL  BIOPHYSICAL  CAPITAL  Messages Equipment / technology Medias Health / environment Documentary networks Bodily networks SOCIAL CAPITAL  Trust Social roles Personal networks
  10. 10. WILL  COLLECTIVE  Collective INTELLIGENCE  Intelligence PEOPLE 
  11. 11. Layers of Seman-c Processing  Points (USLs): 6 primi-ves, sequences of 3L primi-ves (0⩽L⩽6),   categories, catsets, USLs  FORM  (syntax)  Perspec-ves: series, matrices, trees  Terms: dic-onary = correspondence points/natural language +  network of seman-c rela-ons between terms  COLOR  (seman-cs)  Texts (USLs with a meaning): Gramma-cal rules for the  genera-on of texts automa-cally transl. into nat. languages   Circuits: networks of texts  LUMINOSITY  (pragma-cs)  Flows: circula-on of seman-c energyn in circuits, following the  rules of informa-on economy games 
  12. 12. The Bodies of Collec-ve Intelligence  SEMANTIC BODY   Forms: Sets of USLs and perspec-ves  Colors: Meaning of the USLs  ENERGY BODY  Circuits: graphs of USLs  Flows: economic, electric, neural,... models  DATA BODY  Data  Mul-‐Media  3D+t. Addresses  Rep of VB  User‐controlled  automatable  func-ons 
  13. 13. The Nature of Collec-ve Intelligence  group of transforma-on  seman-c space  DIGITAL MEDIA  form : virtual essence  ECOSYSTEM  color : actual essence  (self‐observa-on)  symbolic bodies  luminosity : virtual existence  data : actual existence  SYMBOLIC  CI  COGNITION  subjec-ve experience : virtual presence   GAMES  (observer)  objec-vity : actual presence  techno‐biological environment  material bodies  3D MATERIAL  molecular machines  ECOSYSTEM  par-cles / waves  (phenomena)  group of transforma-on  unified field 
  14. 14. IEML and the « Seman-c Web » 
  15. 15. Differences of nature between   IEML and XML / RDF / OWL  •  OWL has no seman3c content in itself: no verbs, nouns, adjec-ves,  adverbs, preposi-ons, inflec-ons, etc. OWL is rather a file format for  descrip-on logics.  •  IEML has a seman3c content in itself. Users can generate proposi-ons,  complex phrases with several proposi-ons and « texts » from the  syntax and dic-onary of IEML.   •  IEML can be expressed in any file format, including XML, RDF and  OWL. There is currently  an automa-c translator from a cursive  nota-on of IEML (called STAR), to binary and XML nota-ons of IEML.  IEML is not a data format!  •  It is indeed possible to use IEML to describe OWL ontologies (and so  to decompartmentalize dis-nct ontologies), or to describe in OWL the  complex network of concepts of the IEML dic-onary (like wordnet has  – almost ‐ done for the english language). 
  16. 16. Differences of goals between   IEML and XML / RDF / OWL  •  1) Seman-c interoperability  –  Standardizing data formats is already done by the W3C and other standardiza-on  ins-tu-ons.  –  But diversity of data formats is not the only obstacle to seman-c interoperability :  diversity of ontologies, folksonomies, classifica-on systems, natural languages...   –  IEML can be used in the context of ontologies with very different hierarchies of  concepts  –  Once expressed in IEML, a complex concept ‐ the meaning of a *tag ‐ can be  automa-cally translated to any natural language supported by the IEML dic3onary.  •  2) Transparency of seman-c addressing system  •  3) Empowerment of wri-ng / reading  •  4) Symbolic tool for self‐observa-on and self‐reference of collec-ve  intelligence  These goals have to be addressed by humani-es and social sciences, but  these sciences need the help of soZware engineering.  
  17. 17. Toward a transparent   seman-c addressing system (1)  •  Opacity by design of the URIs  –   h;p://www.w3.org/TR/webarch/#uri‐opacity  •  By contrast, IEML expressions form a group of  transforma3ons. Automatable algebraic transforma-ons  on IEML symbols correspond to automatable algebraic  transforma-ons on significa-ons (on “seman-cs”).  •  The IEML seman-c space (the immense set of IEML  « texts », called USLs ) is in principle independent of the  URI address space just as it is independent of any physical  or telecommunica-on addressing system. 
  18. 18. Toward a transparent   seman-c addressing system (2)  •  IEML can bring to the system of URIs a general seman3c  interconnec3on and a full group of transforma3on on  seman3cs. IEML‐URIs can be directly used as concepts in  RDF or OWL. The IEML research program can offer an  alterna-ve grounding to the en--es of the Web of data,  mapping URIs to such IEML‐URIs.  •  The power of IEML can be leveraged by the exis-ng  standards of the Web of data. Symmetrically, the  expressive and algebraic proper-es of IEML can leverage  the current Web of data by providing it with a novel  grounding that can make it more seman-c. 

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