1. Participatory Computing for Our Complex World Dirk Helbing (ETH Zurich) New science and technology to understand and manage our complex world in a more sustainable and resilient way
2. What It Means to Live in an Information Age§ Global ICT = most complex artifact§ Billions of interacting components§ Many autonomous decisions § à Artiﬁcial social systems!§ Example: Computer-based automated ﬁnancial trading § Too much data § Too much speed § Too much complexity ICT is part of the problem, but also key to the solution! Need to understand socially interacting systems!
3. Alex (‚Sandy‘) Pentland of the MIT Media Lab Says: § Our ﬁnancial, transportation, health system are broken § We need to develop a decentralized adaptive approach § Managing complexity requires real- time data mining The more complex our systems become, the more do we need a decentralized management concept based on facilitating favorable self- organization. This requires real-time data to allow for ﬂexible, adaptive response.
4. Networking is Good … But Promotes Cascading Effects § We now have a global exchange of people, money, goods, information, ideas…§ Globalization and technological change have created a strongly coupled and interdependent world Network infrastructures create pathways for disaster spreading! Need adaptive decoupling strategies.
5. Are Derivatives Financial Weapons of Mass Destruction?Buffett warns on investment time bombDerivatives are ﬁnancial weapons of mass destruction "Warren Buffett The rapidly growing trade in derivatives poses a "mega-catastrophic risk" for the economy ..., legendary investor Warren Buffett has warned. The worlds second-richest man made the comments in his famous and plain-spoken"annual letter to shareholders", excerpts of which have been published by Fortunemagazine. The derivatives market has exploded in recent years, with investment banks sellingbillions of dollars worth of these investments to clients as a way to off-load or managemarket risk. But Mr Buffett argues that such highly complex ﬁnancial instruments are time bombsand "ﬁnancial weapons of mass destruction" that could harm not only their buyersand sellers, but the whole economic system. (BBC, 4 March, 2003)
6. The Flash Crash on May 6, 2010 600 billion dollars evaporated in 20 minutesThe ﬂash crash turned solid assets into penny stocks within minutes.Was an interaction effect, no criminal act, ‘fat ﬁnger’, or error.
7. Cascading Effects During Financial Crises Video by Frank Schweitzer et al.
8. Cascading Effect and Blackout in the European Power Grid Failure in the continental European electricity grid on November 4, 2006 EU project IRRIIS: E. Liuf (2007) Critical Infrastructure protection, R&D view
9. Revolutions: Another Cascading Effect ? ? The Arabic Blogosphere
10. Political Cascading Effects Transition from hierarchies to democracies (source: Jürgen Mimkes) hierarchy transition democracy W orl d GNP and f ertility G N P pe r p e r s on in US $ 35 .0 00 h iera rc hies 30 .0 00 tran sitio n 25 .0 00 d em oc ra cies 20 .0 00 tran sitio n lin e 15 .0 00 de m o c r ac i es 10 .0 00 5 .0 00 h i e ra r c h i es 0 0 1 2 3 4 5 6 7 8 fe rt i li t y f, c h i ld re n p e r w o m e n
11. Need New Science to Fill Knowledge GapsFor 30 years or so have we globalized ourworld and pushed for technologicalrevolutions, but the global systems scienceto understand the resulting complex systemsis lacking.1. Science of systemic risks2. Practically relevant theory of complex systems3. New data science4. Integrated systems design to manage complexity5. Coevolution of ICT with society
12. Our Thinking Determines What We See …
13. …And What We Can’t See…! We need to overcome thelimitations of our conventionalthinking!
14. The Need to Look Behind What Our Senses Tell Us Geocentric Picture: Epicycles around the Earth Heliocentric Picture: Elliptical paths around the sun
15. Emergent Phenomena in Pedestrian Crowds At high densities, several people may compete for the same gap and block each other. This constitutes a conﬂict and causes intermittent outﬂows and a faster-is-slower effect.At low densities: At largeself-organized lane formation, densities:like Adam Smith’s invisible handcoordination breaks down
16. Low Predictability Due to the" Sensitivity to Varying Model Parameters 360 340Wet Bench in Semiconductor Production 320 300 280 260 DS 240 220 200 180Chemical Water Chemical Water GC Chemical Water Dryer Park Positions Input, 160 Output 140 120 100 89 180 240 01-DHF critical ontime 01-ST_dhf 380460540620 300 360 420 02-QDR_1 03-SC_1 380460540620 300 360 420 04-QDR_2 06-SC_2 380 460540620 07-QDR_3 510 570 08-DMG Throughput TEST_1 TEST_2 TEST_3 Analyse software 266,8 255,9 246,1 Production machine 150,9 155,5 178,4 Difference in w/h 115,9 100,4 67,7
17. Paradoxical Slower-Is-Faster Effect in Chip Production Slower-is- faster effectOld recipe: New recipe:ca. 170/h ca. 230/h
18. Instability: John D. Sterman’s Beer Game Perturbations in demand amplify
19. As Coupling Gets Stronger, System Behavior Can Change Completely: Trafﬁc Breakdowns Thanks to Yuki Sugiyama Capacity drop, when capacity is most needed! At high densities, free trafﬁc ﬂow is unstable: Despite best efforts, drivers fail to maintain speed
20. As Coupling Gets Stronger, System Behavior Can Change Completely: Crowd Disasters Love Parade Disaster in Duisburg, 2010At low densities:self-organized lane formation, like Adam Smith’s invisible hand At large densities: coordination breaks down
21. Strongly Coupled and Complex System Behave Fundamentally Different1. Faster dynamics2. Increased frequency of extreme events – can have any size3. Self-organization dominates system dynamics4. Emergent and counterintuitive system behavior, unwanted feedback, cascade and side Change of perspective (from a effects component- to an interaction-5. Predictability goes down oriented view) will reveal new solutions!6. External control is difﬁcult 7. Larger vulnerability Need a science of multi-level complex systems!
22. Instruments to Explore the WorldConnect web experiments with data mining andmodelling tools to reach an acceleration of knowledgegeneration as in the Human Genome Project Hubble, Nasa
23. Build platforms to explore & interact What for? Turn knowledge into wisdom People What is? What if? Create systems Data provide data Models Develop models to sense & create new technology to simulate & understand predictTurn data into information Turn information into knowledge
24. Platforms to explore & interact Global Participatory Platform Innovation Accelerator Planetary Living Systems Nervous provide data Earth Models to sense & System create new technology Simulator to simulate &understand predict
25. The FuturICT Knowledge Accelerator Thanks to Michael Mäs Humanities Qualitative Quantitative Economics Sociology Sociology Crowd Computational Data Science Complexity Sourcing Social Science PNS Science GPP LESIntegrating the best knowledge from the social, natural, and engineeringsciences, particulary social sciences, complexity sciences, and ICT
26. Platforms to explore & interact Global Participatory Platform Innovation Accelerator Planetary Living Systems Nervous provide data Earth Models to sense & System create new technology Simulator to simulate &understand predict
27. Crowd-Sourcing 3D Environments See also Open Streetmap - the free Wiki world map
28. More Sustainability and Resilience through Collective, ICT-Enabled (Self-)Awareness 1. Goal: Measure the world’s state and ‘social footprint’ in real time, detect possible threats and opportunities 2. Use smartphones, social media, digital news sources, sensors… 3. Incentives to provide data 4. Control over own data 5. Privacy-respecting data miningRequires a ‘Planetary Nervous System’ Painting by Maurits Cornelis Escherto answer ‘what is’ questions and a Examples: Open streetmap,‘Living Earth Simulator’ to answer earthquake sensing and warning‘what if’ questions.
29. New Compasses for Decision-Makers Consider social capital: § Solidarity, cooperativeness, § compliance, § reputation, trust, GDP § attention, curiosity, § happiness, health, § environmental care…Goal: Createindices better than GDP/capita, considering health, Green = Happiest Blueenvironment, social Purplewell-being, … Orangeto promote Red = Least Happysustainability Grey = Data not available Happiness
30. Platforms to explore & interact Global Participatory Platform Innovation Accelerator Planetary Living Systems Nervous provide data Earth Models to sense & System create new technology Simulator to simulate &understand predict
31. Building FuturICT’s Living Earth Simulator " Analysis of “What if …” Scenarios Data Models Forecasts demographic infection data contact network models transport + = data multi- scale geographic models ...complexity... data agent- based modelsscenario predictions § Integrate data and modelsanalysis Validation § Scale them up to global scale § Make them more accuratepriorities policies (thanks to Alex Vespignani) Possibilities are limited, but even short-term prediction can be useful, as weather forecasts or new trafﬁc light controls show.
32. Modelling the global spread of H1N1," combining models of epidemiology and global travel data
33. Building FuturICT’s Living Earth Simulator § Integrate existing models (trafﬁc, production, economic system, crowd behavior, social cooperation, social norms, social conﬂict, crime, war…)§ Scale them up to global scale§ Increase degree of detail, accuracy (statistical and sensitivity analysis, calibration, validation, identiﬁcation of crucial and questionable modeling assumptions,…)
34. Managing Complexity: Is It a Lost Battle?§ In a strongly varying world, strict stability and control is not possible anymore or excessively expensive § Example: Public spending deﬁcits§ Hierarchically organized structures have a critical size, beyond which they become unstable§ Examples: Decay of Soviet Union; many failed mergers in the last decade (Daimler-Chrysler, BMW-Rover, Allianz-Dresdner Bank, …) § A paradigm shift towards ﬂexible, agile, adaptive systems is needed, possible - and overdue! Boeing 747: Constructed for stable ﬂight Su-47: Utilizes dynamic instability
35. How to Utilize Properties of Complex Systems?
36. Managing Complexity: Modifying InteractionsAllows to Promote Favorable Self-Organization
37. Self-Control of Trafﬁc Lights: Making More Out of Scarce Resources Smarter CitiesInspiration: Self-organizedoscillations at bottlenecksMeasurementinput Optimal compromise between coordination and Licensing Opportunity local ﬂexibility
38. Avoiding Crowd Disasters Flow Monitoring in 2007 Situation in 2006§ Avoiding crossing and counter-ﬂows§ Real-time ﬂow monitoring Beneﬁcial for all mode§ Adaptive rerouting of transport and for the environment§ Contingency plans October, 3rd, 2011 Resilient Flow Organization in 2007 STS Forum, 8th Annual Meeting, Kyoto 38
39. Conﬂict in the Middle East: Possible Future Scenarios ‘Business as Usual’ Clinton Parameters
40. Platforms to explore & interact Global Participatory Platform Innovation Accelerator Planetary Living Systems Nervous provide data Earth Models to sense & System create new technology Simulator to simulate &understand predict
41. An Open, Transparent Platform for Everyone § Goal: An open platform for everyone, overcome “black holes” for data and data fragmentation§ Transparent data sources and quality, transparent algorithms, transparent results§ Potentials: New services and jobs, less barriers for social, economic and political participation§ Problem: A new public good, requiring mechanisms to avoid data pollution, manipulation, misuse, privacy intrusion, cybercrime§ How to promote responsible use? § Need to develop a Trustable Web, a self-regulating information ecosystem
42. Decision-Making Support Debate Platforms & " Argument Maps
43. World of Modelling for Simulation App Developer Toolkit & Computational Modeling App Store, incl. Commercial Software/Services
44. Interactive Virtual Worlds for Exploration Multi-player serious online games " across diverse platforms
45. Interactive Virtual Worlds as Experimental Testbed For example different ﬁnancial architectures, voting rules, transparency and privacy settings, etc.
46. Platforms to explore & interact Global Participatory Platform Innovation Accelerator Planetary Living Systems Nervous provide data Earth Models to sense & System create new technology Simulator to simulate &understand predict
47. Sparking Off Innovations by ‚Hilbert Programs‘??? + Funding
48. Socio-Inspired ICTUnderstanding the hidden laws and processes of society Development a new wave of robust, trustworthy andadaptive information systems based on socially inspiredparadigms. Facebook is by nowFundamental transformational effect on ICT and one of the mostComputer Science valuable companies in the world (65 billion $) 3. Socio-inspired, 1. Collective awareness bottom-up 2. Social adaptiveness self-organization
49. Coming Era of Socio-Inspired Innovations Understanding socially interactive systems facilitates socio-inspired ICT§ Cooperation, Example: A ‘Trustable Web’,§ adaptability and self-regulation, reputation-based and self-§ conﬂict resolution, regulating, to keep§ resilience, cybercrime low§ trust, § reputation, § social norms, § values, ethics, and § cultureEconomic beneﬁts!New solutions to societal problems!
50. Social Money Thanks to Frank Schweitzer and Dirk BrockmannTreat money as nodes in a money ﬂow network rather than as a one-dimensional entity (scalar), give it multi-dimensionality, memory, history, reputation.
51. The Challenge of InnovationEvery revolutionary idea seems to evoke three stagesof reaction. They may be summed up by the phrases: 1- Its completely impossible. 2- Its possible, but its not worth doing. 3- I said it was a good idea all along. Arthur C. ClarkeThe ﬁve stages of innovation People deny that the innovation is required. People deny that the innovation is effective. People deny that the innovation is important. People deny that the innovation will justify the effort required to adopt it. People accept and adopt the innovation, enjoy its beneﬁts, attribute it to peopleother than the innovator, and deny the existence of stages 1 to 4.Inspired by Alexander von Humboldts Three Stages Of Scientiﬁc Discovery