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1 The Future Internet as a Global Brain: an update of the theory Francis Heylighen Evolution, Complexity and Cognition group Vrije Universiteit Brussel.

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Presentation on theme: "1 The Future Internet as a Global Brain: an update of the theory Francis Heylighen Evolution, Complexity and Cognition group Vrije Universiteit Brussel."— Presentation transcript:

1 1 The Future Internet as a Global Brain: an update of the theory Francis Heylighen Evolution, Complexity and Cognition group Vrije Universiteit Brussel

2 Definition of the Global Brain Global system of collective intelligence/distributed cognition l Capable of information-processing, problem-solving, decision- making Network of connections between human and artificial agents l Supported by the Internet l Becomes every year more encompassing and more intelligent On the verge of a metasystem transition l To an inconceivably large intelligence l “Singularity” => Nervous system for the planetary superorganism

3 3 The basic analogy

4 4 History of Global Brain Research 19th century l Emile Durkheim, Herbert Spencer –society as organism –“collective consciousness” –No clear structure for social “nervous system” yet First half 20th century l Pierre Teilhard de Chardin: –“noosphere” = planetary layer of thoughts and communications l Paul Otlet: –Belgian founder of information science –Envisaged web-like organization of all knowledge l H.G. Wells: –“World Brain” = global institution to gather and publicize all knowledge

5 1945-1995 Vannevar Bush (1945), Douglas Engelbart (1960), Ted Nelson (1974): l Hypermedia = –Documents connected by direct, associative links –External memory Tim Berners-Lee (1991): l hypermedia + internet = world-wide web l Documents can reside in different locations Peter Russell (1982), Joël de Rosnay (1989), Gottfried Mayer-Kress (1995): l global brain emerging from the internet

6 6 Hypermedia: links between documents

7 7 Web as “Neural” Network The web links mutually relevant information through “hyperlinks”. This is analogous to the way the brain links concepts by associations, and the corresponding assemblies of neurons by synapses. 7

8 The Principia Cybernetica community Valentin Turchin (1970): l Cybernetic analysis of intelligence and neural networks l metasystem transition towards “super-being” Principia Cybernetica Project l Created in 1989 by Turchin and Cliff Joslyn –Joined in 1990 by Francis Heylighen l To develop Turchin’s theory of evolutionary cybernetics l While using the collaborative tools of hypermedia and internet l Website created in 1993 by Heylighen Heylighen & Johan Bollen (1995): l learning and “thinking” website -> brain-like abilities Global Brain Group founded by Heylighen & Ben Goertzel in 1996 l First workshop in 2001

9 9 Global Brain research: 2000s Hectic explosion of the internet l Billions of people joining l Proliferation of mutually incompatible systems “Web 2.0” l Focus on collaborative development l In fact already part of “Web 1.0” l Global Brain idea shifts to the background Principia Cybernetica and Global Brain group increasingly less active l Because of illness and other obligations Tim O’ Reilly, Yuri Milner (2011): l new interest in the Global Brain vision

10 10 Growth of the Internet

11 11 ECCO Research group directed by Francis Heylighen l International, interdisciplinary l Founded in 2004 at the VUB l Present membership: –about 10 core –about 20 affiliated Main research subjects l Self-organization, especially: –of distributed intelligence –of coordinated action l Extending Turchin’s evolutionary cybernetics l With lots of applications on the web l But no explicit focus on the global brain

12 12 ECCO results: Theory Action ontology l Life as an adventure Coordination of agents via l Stigmergy l Connectionist networks l Propagation of challenges Resolves a wide variety of conceptual problems in l complexity science l cognitive science

13 13 ECCO results: some web applications l Hebbian learning of web links l SNURF: intelligent propagation of messages across a social network, l Smartocracy: voting network for democratic decision-making l Gnowsys: conceptual network for knowledge organization and education l Teacherplex: website that stimulates students to learn new material via multiple choice questions l a formalism and set of algorithms for intelligent reasoning across distributed knowledge networks l Stigmergic University: a proposal to integrate these different technologies in order to create a “World Brain”

14 Creation of a Global Brain Institute Yuri Milner l Web billionaire, investor in Facebook, Twitter, Groupon… l Independently came to the Global Brain concept September 2011: meeting of Milner and Heylighen l Milner wants to sponsor Heylighen’s research on the GB l Heylighen proposes to create a GB Institute at the VUB l Milner agrees to provide funding for at least 5 years –Enough to employ about half a dozen PhD researchers –Focus on developing a mathematical theory of the GB GBI should start in January 2012 l And should get first major results by 2014

15 15 Foundations for a Global Brain theory Both people and machines are agents l They perform actions in response to challenges Challenge = information suggesting that action would improve the situation l Pragmatically meaningful information l Examples of a challenge: –problem, question, task, opportunity, proposal, danger… l Challenges stimulate agents to act Ability to tackle challenges (solving problems) = intelligence l Different agents collaboratively tackling challenges → l Distributed or collective intelligence

16 Challenges are passed on from agent to agent l In parallel and in sequence l While being processed Mechanism l Challenge → action → changed situation → new challenge → new action →… → final solution l Example: message → forward → reply → reply to the reply →… → agreement Similar to information processing in the brain l Spreading activation = activation passed on from neuron to neuron along synapses l “activation” = condition that makes a neuron “act” Propagation of Challenges

17 17 Propagation of challenges in organization input output

18 Self-organizing propagation of challenges No fixed “flowchart” l Challenges can propagate freely Variation and selection dynamics l challenge stimulates action → undergoes variation l Variation stops when situation is no longer challenging l “Solved” challenges are selectively retained –Attractor of the dynamics l “Unsolved” ones continue to undergo variation –Basin leading into attractor

19 Friction and synergy Actions/agents can be in conflict l Action of A perturbs effect of action of B l = Friction between A and B l → continued variation as A counteracts B’s action, and B counteracts A, etc. l Variation stops as compromise or win-win situation is reached Actions/agents can be synergetic l Together they achieve more than the sum of their indivodual achievements: win-win l This situation is preferentially retained → selection

20 20 Example: Wikipedia Nearly empty page on topic → challenges reader to expand text l Revised text challenges further readers to correct/ add/ improve Coordinated Action l Different people collaborate efficiently on the page l Without even knowing each other l Conflicts are eventually solved Propagation of challenges → self-organization of collective intelligence Requires propagation medium l Where challenges are registered for others to see l Here: Wikipedia website

21 21 Example : Social network People connect to their “friends” l Friends automatically see messages (“challenges”) left by their connections l They may forward these messages to other friends (propagation) l Important or popular messages may thus selectively spread through the network This system can be much improved l Different types of connections, e.g. –Friends vs. acquaintances –“Circles” of interest (Google+) l Different strengths of connections –People you know better or less well This would allow a much more intelligent, automatic propagation

22 22 The network of Facebook

23 23 Improving propagation Self-organization and therefore coordination can be facilitated Better medium l Faster l more robust and reliable l easier to edit l More intuitive l more available… l Reaching more agents

24 More efficient network l Learning the most important connections, their strengths and their types l So that challenges can be propagated to the most appropriate targets Automatic propagation l E.g. using spreading activation algorithms + particle grammars This would produce a much more intelligent propagation of “thoughts” in the global brain Directed propagation

25 25 Mobilization systems Making challenges more pleasurable l “flow” = full absorption in activity, if: –Clear goals –Immediate feedback –Challenges in balance with skills l Applied implicitly in gaming environments –The activity is so satisfying that it becomes addictive l Other motivating principles –utility, altruism, authority, incentives, conformity… Motivation + Coordination = mobilization of action l Making people collaborate productively and joyfully

26 26

27 27 Ambient Intelligence Internet of things l Not only people but a variety of devices are connected into the global brain l E.g. sensors, vehicles, thermostats, machines, robots, ovens, … Agents can react “intelligently” to physical challenges l Such artificial agents too must be coordinated l E.g. via stigmergy or the propagation of “particles” Coordinated artificial and human agents l → intelligent environment l E.g. to promote health, sustainability, efficiency, security, …

28 Mining Meaning28

29 29 Towards a theory of the global brain Basic paradigm: Self-organizing propagation of challenges Abstract, “ontological” framework l applicable to all types of agents, actions and communications l Allows mathematical formalization –E.g. via complex dynamic systems or connectionist networks In practice, mathematical models are best explored through simulation l Typically too complex for analytic treatment l Allows exploring a variety of parameter settings, initial conditions, architectures, and effects of random perturbations

30 30 Towards a theory of the global brain An abstract theory must be connected to reality l tested with empirical data –E.g. analysis of data about communication patterns in Facebook l Applied in practical situations –E.g. experiments with prototype applications The theory must explain observed phenomena l It must connect to concrete developments –Social movements –New technologies –Economic pressures –Legal constraints –Ethical and political considerations…

31 Mining Meaning31

32 32 What is needed Developing a global brain theory requires highly qualified researchers l Keeping informed of all potentially relevant developments l Collaborating closely on the theory –face-to-face –Via stigmergic and other technologies Need for coordination l Alignment: agreement on the target: GBI theory l Division of Labor: who does what? l Workflow: efficient interaction between researchers l Aggregation: integrating the fragments into a whole l Regulation: checking whether things move in the right direction

33 Mining Meaning33

34 34 Conclusion The ECCO research group (the future Global Brain Institute) has the necessary expertise to develop a deep and comprehensive theory of the global brain l Based on the paradigm of self-organizing propagation of challenges However, this will require: l A further clarification of the fundamental concepts l A sustained, focused effort l A good method of coordination l openness to the world and what happens there

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