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Global 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
Big Data = Big Opportunities, also for Science
                                             




                                       How to turn data
                                       into knowledge?
                                       §  theoretically
                                           informed
                                           data-mining
                                       §  models to
                                           understand
Old Problems: External Threats to Society
Our Thinking Determines What We See …
… And What We Can’t See…!
                                   




We need to overcome the
limitations of our conventional
thinking!
We Can‘t Anymore Do Business As Usual

“Our financial, transportation, health
system are broken.”
Sandy Pentland, MIT Media Lab




                                        
                                        “We are seeing an extraordinary
                                        failure of our current political and
                                        economic system.”
                                        Geoffrey West, former president of
                                        the Santa Fe Institute
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.
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
Collateral Damage
1.  Financial crisis: Losses of 2-20 trillion $
2.  Conflict: Global military expenditures
    amount to 1.5 trillion $ annually. 
3.  Terrorism: 9/11 attacks caused 90 billion
    $ lost output of the US economy
4.  Crime and corruption: 2-5% of GDP,
    about 2 trillion $ annually.



                                              5.  Flu: A true influenza pandemic
                                                  infecting 1% of world population
                                                  would cause losses of 1-2 trillion $
                                                  per annum
                                              6.  Cybercrime: 750 billion EUR/a in
                                                  Europe
Are Derivatives Financial Weapons 
                  of Mass Destruction?

Buffett warns on investment 'time bomb'

Derivatives 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 world's second-richest man made the comments in his famous and plain-spoken
"annual letter to shareholders", excerpts of which have been published by Fortune
magazine. 
The derivatives market has exploded in recent years, with investment banks selling
billions of dollars worth of these investments to clients as a way to off-load or manage
market risk. 
But Mr Buffett argues that such highly complex financial instruments are time bombs
and "financial weapons of mass destruction" that could harm not only their buyers
and sellers, but the whole economic system.        (BBC, 4 March, 2003)
The Flash Crash on May 6, 2010
      600 billion dollars evaporated in 20 minutes




The flash crash turned solid assets into penny stocks within minutes.
Was an interaction effect, no criminal act, ‘fat finger’, or error.
Cascading Effects During Financial Crises




         Video by Frank Schweitzer et al.
Need New Science to Fill Knowledge Gaps
For 30 years or so have we globalized our
world and pushed for technological
revolutions, but the global systems science
to understand the resulting complex systems
is lacking.

1.  Science of systemic risks

2.  Practically relevant theory of complex
    systems

3.  New data science

4.  Integrated systems design to manage
    complexity

5.  Coevolution of ICT with society
We Should Not Trust Our Intuition
           Geocentric Picture: 
           Epicycles around the Earth




                                         Heliocentric Picture:
                                         Elliptical paths
                                         around the sun
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 large
self-organized lane formation, 
    densities:
like Adam Smith’s invisible hand
coordination
                                 breaks down
Low Predictability Due to the"
                              Sensitivity to Varying Model Parameters
                                       
                                                           360

                                       
                                                           340

Wet Bench in Semiconductor Production
 
                                                           320

                                       
                                                           300

                                       
                                                           280

                                       
                                                           260


                                      

                                                         DS 240

                                       
                                                           220

                                       
                                                           200

                                       
                                                           180
Chemical   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
Paradoxical Slower-Is-Faster Effect
                 in Chip Production 
                                                 Slower-is-
                                                 faster
                                                 effect




Old recipe:                                  New recipe:
ca. 170/h
                                   ca. 230/h
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
As Coupling Gets Stronger, System Behavior Can
     Change Completely: Crowd Disasters


                                          Love Parade Disaster in Duisburg, 2010




At low densities:
self-organized lane formation, 
like Adam Smith’s invisible hand
   At large densities: coordination breaks down
Hyper-Connected Systems

§    Global ICT = most complex artifact
§    Billions of interacting components
§    Many autonomous decisions 
§    à Artificial social systems!



                                            §  Too much data?
                                            §  Too much speed?
                                            §  Too much complexity?
                                            
                                            ICT seems part of the problem,
                                            but also key to the solution! Need
                                            to understand socially interacting
                          Source: WEF
                                            systems!
Too Much Networking Can Cause Self-
    Destabilization: Breakdown of Cooperation





    Different recipes, new solutions, and a paradigm shift in
           our understanding of the world are needed.
Strongly Coupled and Complex System Behave
               Fundamentally Different
1.  Faster dynamics
2.  Increased frequency of extreme
    events – can have any size
3.  Self-organization dominates
    system dynamics
4.  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!
Instruments to Explore the World




Connect web experiments with data mining and
modelling tools to reach an acceleration of knowledge
generation as in the Human Genome Project
                                                        Hubble, Nasa
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
                                                                 predict

Turn data into information
                                          Turn information into 
                                                                     knowledge
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
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
Crowd-Sourcing 3D Environments
                                          


Thanks to
Marc
Pollefeys




              See also Open Streetmap - the free Wiki world map
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 mining

Requires a ‘Planetary Nervous System’
                                        Painting by Maurits Cornelis Escher
to answer ‘what is’ questions and a
                                        Examples: Open streetmap,
‘Living Earth Simulator’ to answer
                                        earthquake sensing and warning
‘what if’ questions.
New Compasses for Decision-Makers
                                        
                                                   Consider social capital:
                                                   §    Solidarity, cooperativeness,
                                                   §    compliance,
                                                   §    reputation, trust, 
GDP
                                               §    attention, curiosity,
                                                   §    happiness, health,
                                                   §    environmental care…

Goal: Create
indices better 
than GDP/capita, 
considering health,   Green = Happiest
                      Blue
environment, social   Purple
well-being, …
        Orange
to promote 
          Red = Least Happy
sustainability
       Grey = Data not available
          Happiness
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
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
                                                                          models


scenario
               predictions                          §  Integrate data and models
analysis                      Validation
                                                    §  Scale them up to global scale
                                                    §  Make them more accurate

priorities       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.
Modelling the global spread of H1N1,"
                                                      
combining models of epidemiology and global travel data
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,…)
Interactive Virtual Worlds for Exploration
                                         




   Multi-player serious online games "
       across diverse platforms
Interactive Virtual Worlds as Experimental Testbed




      For example different financial architectures, voting rules, 
      transparency and privacy settings, etc.
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
How to Utilize Properties of Complex Systems?
  Don‘t Fight the System, Go With the Flow!
Managing Complexity: Modifying Interactions
Allows to Promote Favorable Self-Organization
Self-Control of Traffic Lights: Making More Out of
                 Scarce Resources  
    Smarter Cities
Inspiration: Self-organized
oscillations at bottlenecks




Measurement
input
                         Optimal
                               compromise
                               between
                               coordination and
 Licensing Opportunity
        local flexibility
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
                              40
Conflict in the Middle East: Possible Future
                 Scenarios




   ‘Business as Usual’     Clinton Parameters
Social Norms and Conflict
                                                            
                                                                    People sanction



                                                                    and suppress each


                                                                    other every day to


                                                                   create social order 


                                                                   Computer simulations:
                                Population 1 
    Strength of population 1






                                                                   

                               sets the norm
                      Red = individuals



                                                                    preferring behavior 1

                                                                   

                                                 Everyone tends

                                                                   Yellow = individuals

                                                 to do what 
                                                                    adjusting to behavior 1

                                                 he/she likes
     

                                                 (anomie)
         Blue = individuals
                                                                    preferring behavior 2
                                 Population 2 
                     
                                                                    Green = individuals 
                                 sets the norm
                                                                    adjusting to behavior 2 



    Reward of showing preferred behavior / Reward of conforming
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
Big Data = Big Challenges
                        




                             Cybercrime
                             -  Privacy
                             -  Data security
                      3 workshops on ethics,
                      own research focus.
Surveillance as Go(o)d Solution?
                                           
“The internet has totalitarian potential.”




                                              §  The Internet cannot be controlled
                                                  top down (we cannot even control
                                                  the financial system)
                                              §  Rather apply principles of
                                                  decentralized self-regulation (as in
                                                  our immune system)
                                              §  Build on transparency, reputation
                                                  systems
Are These Really Twitter Revolutions?
                                    




            The Arabic Blogosphere
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
Food Prices as Triggers of Social Unrests
An Open, Transparent Platform for Everyone
                                                
§    Goal: A ‘data and model commons’,
      an open platform for everyone

§    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
Why Privacy Is Important
Example: My diary and trust
       §    Public and private are two sides of the
                                         same medal

                                   §    Privacy is a pressure relief system that
                                         allows people to adapt to expectation
                                         of others during public exposure

                                   §    Protection of minorities, protection of
                                         socio-diversity

                                   §    Reduction of conflict 

                                   §    If there is no protected private space,
                                         people will stop thinking independently,
                                         which undermines the wisdom of
                                         crowds
Free space is needed for           §    If there is no privacy, there is no
individuals to recover and for           intimacy, i.e. partnerships and
society to innovate and evolve.
         friendships as we know them
Computers Thinking for Us: The Filter Bubble
                                           




                      Risk of manipulation and                 Eli
                      over-confidence.
                         Pariser
                      Supporting egocentric
                      consensus may promote
                      segregation and conflict
                      between groups with
                      different preferences. 
These questions may have fundamental societal implications.
They deserve and require scientific study!
Diversity-Preserving Recommender Systems
                                       
Avoid conformity and herding effects, protect socio-diversity




                                        Source: Yi-Cheng Zhang et al.


              Value sensitive design!
Socio-Inspired ICT
Understanding the hidden laws and processes of society

  
Development a new wave of robust, trustworthy and
adaptive information systems based on socially inspired
paradigms.
                                                          Facebook is by now
Fundamental transformational effect on ICT and            one of the most
Computer Science
                                         valuable companies
    
                                                     in the world



                                                      3. Socio-inspired,
 1. Collective awareness
                             bottom-up
                            2. Social adaptiveness
   self-organization
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 
§    culture

Economic benefits!
New solutions to societal problems!
Client Server Systems vs. Peer to Peer Systems
                                             
                             Peer-to-Peer Systems
    Client-Server Systems




            Source                               Application
                                                 example:
The Dilemma of Social Cooperation
                                         
  
The prisoner's dilemma game has served as prime example of
   strategic conflict among individuals. It assumes that, when two
   individuals cooperate, both get the “reward” R, while both receive the
   “punishment” P< R, if they defect. If one of them cooperates (“C”) and
   the other one defects (“D”), the cooperator suffers the “sucker’s
   payoff” S < P, while the payoff T > R for the second individual reflects
   the “tempation” to defect. Additionally, one typically assumes S+T <
   2R. 
                                                Player 2
     For example:
                                         Cooperate Defect
 S = S = S = -5
                                                                1 2
                            Player 1



                               Cooperate
 R1 R2
 S1 T2
       P1 = P2= P = -2
                                                              R1 = R2= R = -1 
                                   Defect
 T1 S2
 P1 P2
                                                              T1 = T2= T = 0
                                                              
Many social dilemmas are of a similar kind (see public goods game)
Emergence of Cooperation in Social Dilemma Situations
                                                     
Overfishing,
global warming,
misuse of social
benefit systems,
tax evasion,
free-riding

Red, yellow:

defectors
(cheaters)
Blue, green:
cooperators




                   Imitation of the best-performing neighbor, success-driven
                   mobility, and trial-and-error together can cause an outbreak of
                   cooperation, but no subset of these social mechanisms
How the Costly Sanctioning of Free-Riders Can Survive "
            and Moral Behavior Spreads  
                                                                   In
                                                                   memoriam
                                                                   of Elinor
                                                                   Ostrom




     D = Defectors (Free-Riders), M = Moralists, I=Immoralists 
     C = Non-punishing Cooperators (Second-Order Free-Riders)
Social Money
                                       



                                    Thanks to Frank Schweitzer 
                                    and Dirk Brockmann




Treat money as nodes 
in a money flow network 
rather than as a one-
dimensional entity (scalar), 
give it multi-dimensionality, memory, history, reputation.
“Data is the new oil” – Clive Humby
         
         … but models are the new gold
         
         … and participation means social capital!




http://www.photoeverywhere.co.uk/west/usa/california/sunset_oil_rigDSC_4701.jpg
Stop Searching Where the Light Is!
Learn to Keep Many Things Going
       at the Same Time …
Demonstrating the Need to Overcome the
  Barriers of Our Conventional Thinking
Thanks for your interest 
and thanks to our supporters!

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FuturICT: New Era of Participatory Global Computing

  • 1. Global 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. Big Data = Big Opportunities, also for Science How to turn data into knowledge? §  theoretically informed data-mining §  models to understand
  • 3. Old Problems: External Threats to Society
  • 4. Our Thinking Determines What We See …
  • 5. … And What We Can’t See…! We need to overcome the limitations of our conventional thinking!
  • 6. We Can‘t Anymore Do Business As Usual “Our financial, transportation, health system are broken.” Sandy Pentland, MIT Media Lab “We are seeing an extraordinary failure of our current political and economic system.” Geoffrey West, former president of the Santa Fe Institute
  • 7. 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.
  • 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. Collateral Damage 1.  Financial crisis: Losses of 2-20 trillion $ 2.  Conflict: Global military expenditures amount to 1.5 trillion $ annually. 3.  Terrorism: 9/11 attacks caused 90 billion $ lost output of the US economy 4.  Crime and corruption: 2-5% of GDP, about 2 trillion $ annually. 5.  Flu: A true influenza pandemic infecting 1% of world population would cause losses of 1-2 trillion $ per annum 6.  Cybercrime: 750 billion EUR/a in Europe
  • 10. Are Derivatives Financial Weapons of Mass Destruction? Buffett warns on investment 'time bomb' Derivatives 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 world's second-richest man made the comments in his famous and plain-spoken "annual letter to shareholders", excerpts of which have been published by Fortune magazine. The derivatives market has exploded in recent years, with investment banks selling billions of dollars worth of these investments to clients as a way to off-load or manage market risk. But Mr Buffett argues that such highly complex financial instruments are time bombs and "financial weapons of mass destruction" that could harm not only their buyers and sellers, but the whole economic system. (BBC, 4 March, 2003)
  • 11. The Flash Crash on May 6, 2010 600 billion dollars evaporated in 20 minutes The flash crash turned solid assets into penny stocks within minutes. Was an interaction effect, no criminal act, ‘fat finger’, or error.
  • 12. Cascading Effects During Financial Crises Video by Frank Schweitzer et al.
  • 13. Need New Science to Fill Knowledge Gaps For 30 years or so have we globalized our world and pushed for technological revolutions, but the global systems science to understand the resulting complex systems is lacking. 1.  Science of systemic risks 2.  Practically relevant theory of complex systems 3.  New data science 4.  Integrated systems design to manage complexity 5.  Coevolution of ICT with society
  • 14. We Should Not Trust Our Intuition 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 large self-organized lane formation, densities: like Adam Smith’s invisible hand coordination breaks down
  • 16. Low Predictability Due to the" Sensitivity to Varying Model Parameters 360 340 Wet Bench in Semiconductor Production 320 300 280 260 DS 240 220 200 180 Chemical 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 effect Old recipe: New recipe: ca. 170/h ca. 230/h
  • 18. 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
  • 19. As Coupling Gets Stronger, System Behavior Can Change Completely: Crowd Disasters Love Parade Disaster in Duisburg, 2010 At low densities: self-organized lane formation, like Adam Smith’s invisible hand At large densities: coordination breaks down
  • 20. Hyper-Connected Systems §  Global ICT = most complex artifact §  Billions of interacting components §  Many autonomous decisions §  à Artificial social systems! §  Too much data? §  Too much speed? §  Too much complexity? ICT seems part of the problem, but also key to the solution! Need to understand socially interacting Source: WEF systems!
  • 21. Too Much Networking Can Cause Self- Destabilization: Breakdown of Cooperation Different recipes, new solutions, and a paradigm shift in our understanding of the world are needed.
  • 22. Strongly Coupled and Complex System Behave Fundamentally Different 1.  Faster dynamics 2.  Increased frequency of extreme events – can have any size 3.  Self-organization dominates system dynamics 4.  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!
  • 23. Instruments to Explore the World Connect web experiments with data mining and modelling tools to reach an acceleration of knowledge generation as in the Human Genome Project Hubble, Nasa
  • 24. 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 predict Turn data into information Turn information into knowledge
  • 25. 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
  • 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 Thanks to Marc Pollefeys 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 mining Requires a ‘Planetary Nervous System’ Painting by Maurits Cornelis Escher to 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: Create indices better than GDP/capita, considering health, Green = Happiest Blue environment, social Purple well-being, … Orange to promote Red = Least Happy sustainability 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 models scenario predictions §  Integrate data and models analysis Validation §  Scale them up to global scale §  Make them more accurate priorities 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. Interactive Virtual Worlds for Exploration Multi-player serious online games " across diverse platforms
  • 35. Interactive Virtual Worlds as Experimental Testbed For example different financial architectures, voting rules, transparency and privacy settings, etc.
  • 36. 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
  • 37. How to Utilize Properties of Complex Systems? Don‘t Fight the System, Go With the Flow!
  • 38. Managing Complexity: Modifying Interactions Allows to Promote Favorable Self-Organization
  • 39. Self-Control of Traffic Lights: Making More Out of Scarce Resources Smarter Cities Inspiration: Self-organized oscillations at bottlenecks Measurement input Optimal compromise between coordination and Licensing Opportunity local flexibility
  • 40. 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 40
  • 41. Conflict in the Middle East: Possible Future Scenarios ‘Business as Usual’ Clinton Parameters
  • 42. Social Norms and Conflict People sanction and suppress each other every day to create social order Computer simulations: Population 1 Strength of population 1 sets the norm Red = individuals preferring behavior 1 Everyone tends Yellow = individuals to do what adjusting to behavior 1 he/she likes (anomie) Blue = individuals preferring behavior 2 Population 2 Green = individuals sets the norm adjusting to behavior 2 Reward of showing preferred behavior / Reward of conforming
  • 43. 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
  • 44. Big Data = Big Challenges Cybercrime -  Privacy -  Data security 3 workshops on ethics, own research focus.
  • 45. Surveillance as Go(o)d Solution? “The internet has totalitarian potential.” §  The Internet cannot be controlled top down (we cannot even control the financial system) §  Rather apply principles of decentralized self-regulation (as in our immune system) §  Build on transparency, reputation systems
  • 46. Are These Really Twitter Revolutions? The Arabic Blogosphere
  • 47. 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
  • 48. Food Prices as Triggers of Social Unrests
  • 49. An Open, Transparent Platform for Everyone §  Goal: A ‘data and model commons’, an open platform for everyone §  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
  • 50. Why Privacy Is Important Example: My diary and trust §  Public and private are two sides of the same medal §  Privacy is a pressure relief system that allows people to adapt to expectation of others during public exposure §  Protection of minorities, protection of socio-diversity §  Reduction of conflict §  If there is no protected private space, people will stop thinking independently, which undermines the wisdom of crowds Free space is needed for §  If there is no privacy, there is no individuals to recover and for intimacy, i.e. partnerships and society to innovate and evolve. friendships as we know them
  • 51. Computers Thinking for Us: The Filter Bubble Risk of manipulation and Eli over-confidence. Pariser Supporting egocentric consensus may promote segregation and conflict between groups with different preferences. These questions may have fundamental societal implications. They deserve and require scientific study!
  • 52. Diversity-Preserving Recommender Systems Avoid conformity and herding effects, protect socio-diversity Source: Yi-Cheng Zhang et al. Value sensitive design!
  • 53. Socio-Inspired ICT Understanding the hidden laws and processes of society Development a new wave of robust, trustworthy and adaptive information systems based on socially inspired paradigms. Facebook is by now Fundamental transformational effect on ICT and one of the most Computer Science valuable companies in the world 3. Socio-inspired, 1. Collective awareness bottom-up 2. Social adaptiveness self-organization
  • 54. 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 §  culture Economic benefits! New solutions to societal problems!
  • 55. Client Server Systems vs. Peer to Peer Systems Peer-to-Peer Systems Client-Server Systems Source Application example:
  • 56. The Dilemma of Social Cooperation The prisoner's dilemma game has served as prime example of strategic conflict among individuals. It assumes that, when two individuals cooperate, both get the “reward” R, while both receive the “punishment” P< R, if they defect. If one of them cooperates (“C”) and the other one defects (“D”), the cooperator suffers the “sucker’s payoff” S < P, while the payoff T > R for the second individual reflects the “tempation” to defect. Additionally, one typically assumes S+T < 2R. Player 2 For example: Cooperate Defect S = S = S = -5 1 2 Player 1 Cooperate R1 R2 S1 T2 P1 = P2= P = -2 R1 = R2= R = -1 Defect T1 S2 P1 P2 T1 = T2= T = 0 Many social dilemmas are of a similar kind (see public goods game)
  • 57. Emergence of Cooperation in Social Dilemma Situations Overfishing, global warming, misuse of social benefit systems, tax evasion, free-riding Red, yellow: defectors (cheaters) Blue, green: cooperators Imitation of the best-performing neighbor, success-driven mobility, and trial-and-error together can cause an outbreak of cooperation, but no subset of these social mechanisms
  • 58. How the Costly Sanctioning of Free-Riders Can Survive " and Moral Behavior Spreads In memoriam of Elinor Ostrom D = Defectors (Free-Riders), M = Moralists, I=Immoralists C = Non-punishing Cooperators (Second-Order Free-Riders)
  • 59. Social Money Thanks to Frank Schweitzer and Dirk Brockmann Treat money as nodes in a money flow network rather than as a one- dimensional entity (scalar), give it multi-dimensionality, memory, history, reputation.
  • 60. “Data is the new oil” – Clive Humby … but models are the new gold … and participation means social capital! http://www.photoeverywhere.co.uk/west/usa/california/sunset_oil_rigDSC_4701.jpg
  • 61. Stop Searching Where the Light Is!
  • 62. Learn to Keep Many Things Going at the Same Time …
  • 63. Demonstrating the Need to Overcome the Barriers of Our Conventional Thinking
  • 64. Thanks for your interest and thanks to our supporters!