complexity and global systems science · business opportunities: facebook’s value, for example,...

| | Dirk Helbing, Professor of Computational Social Science

Dirk Helbing (ETH Zurich)

Complexity and Global Systems Science

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Literature

§  Ball: Why Society Is A Complex Matter §  Helbing: Social Self-Organization §  Helbing: Managing Complexity §  Colander/Kupers: Complexity and the Art of Public Policy §  Mitchell: Complexity §  Buckley: Society – A Complex Adaptive System §  Castellani/Hafferty: Sociology and Complexity Science §  Mikhailov/Calenbuhr: From Cells to Society §  Mainzer: Thinking in Complexity §  Sawyer: Social Emergence §  Books published by the Santa Fe Institute Dirk Helbing, Professor of Computational Social Science


Old Problems: External Threats to Society

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New Problems: Systemic Instabilities

Examples: 1.  Financial, economic and

debt crisis 2.  Social and political

instabilities 3.  Environmental and

climate change 4. Organized crime,

cybercrime 5. Quick spreading of

emerging diseases © 2010 Paresh Nath We must realize that we are living in a new world.

Dirk Helbing, Professor of Computational Social Science

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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 Dirk Helbing, Professor of Computational Social Science

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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

Collatoral Costs and New Opportunities

§ Even a 1% improvement would create

benefits many times higher than project investments

§  For comparison: Weather forecasts cost 10 CHF/citizen, create a 5 times higher benefit

§ Business opportunities: Facebook’s value, for example, amounts to 60-80 billion $



A Daunting Class of Problems §  Large number of interacting system elements

(individuals, companies, countries, cars…)

§  Non-linear or network interactions §  Rich system behavior

§  Dynamic rather than static

§  Probabilistic rather than deterministic §  Surprising, often paradoxical system behavior

(e.g. slower-is-faster effects) §  Hardly predictable

§  Seemingly uncontrollable

§  Challenge our common way of thinking §  Almost everywhere around us

§  Currently a nightmare for decision-makers


Complicated vs. Complex Systems § Example: A car is a complicated system

§ Example: Traffic flows, involving the interaction of many cars, constitute a complex system

§ Phantom traffic jams, many different kinds of congestion patterns

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Lane Formation in Pedestrian Counterflows

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Crowd Turbulence During the Love Parade


§  Large number of non-linearly interacting system components leads to complex dynamics

§  Example: Weather forecast §  Chaotic dynamics/butterfly effect/

sensitivity: Small initial differences can cause very different behavior

Limits of Predictability

Source: J. D. Murray


Complex Systems: Limits of Predictability

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Counter-Intuitive Behavior of Complex Systems



§  Big changes may have small, no, adverse or unexpected effects §  Irreducible randomness: A degree of uncertainty and perturbation

that cannot be eliminated §  Principle of Le Chatelier/Goodhart’s law: A system tends to

counteract external control attempts §  Delays may cause instabilities §  Regime shifts („phase transitions“,

catastrophes): Sometimes small changes have a big impact

§  Unknown unknowns, structural instability

„Cusp catastrophe“

The Illusion of Control

| | Dirk Helbing, Professor of Computational Social Science 15

212022222

2

211011111

1

)(

)(

xxxxcxkdtdx

xxxxcxkdtdx

λ

λ

+−−−=

−−−=

The Lotka-Volterra equations are used to describe, for example, interactions in ecological systems

x1: number of species 1 x2: number of species 2 x0

1,2: attraction point k1,2, c1,2, λ1,2: parameters

The Challenge to Manage Complex Systems

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Instability of Traffic Flow: Stop-and-Go Waves

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Self-Organized Traffic in Hanoi


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Self-Organization as Alternative and Success Principle Self-Organizing Traffic Flow in Kairo

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Unstable Dynamics

in Complex Systems


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Thanks to "Yuki Sugiyama"

At high densities, free traffic flow is unstable:"Despite best efforts, drivers fail to maintain speed"

Capacity drop, when capacity

is most needed!"

Phantom Traffic Jams

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Perturbations in demand amplify"

Unstable Supply Chains

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Input output matrix! Related delivery network! Resulting oscillations in the gross domestic product!

" """""""""""""""""" "

Economic Instability: Booms and Recessions

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Network structure Commodity flow (average of FRA, GER, JAP, UK, USA)

D. H., U. Witt, S. Lämmer, T. Brenner, Physical Review E 70, 056118 (2004).

Global Logistic Networks: Recessions Are Like Traffic Jams of the Economy


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

Love Parade Disaster in Duisburg, 2010"

Crowd Disasters

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Spreading of Crime

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Social Dilemma Problem"-  Global Warming"-  (Financial Crisis)"-  Free-Riding"-  Tax Evasion"-  Environmental Pollution"-  Environmental Exploitation"-  Overfishing"

Tragedies of the Commons

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Intifada"(civil war)"

Armed Conflict

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World GNP and fertility

0

5.000

10.000

15.000

20.000

25.000

30.000

35.000

0 1 2 3 4 5 6 7 8fertility f, children per women

GN

P pe

r pe

rson

in U

S $

hierarchies

transition

democracies

transition line

democracies

hierarchies

Source: Jürgen Mimkes"

Revolutions

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Financial Meltdowns

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

The Flash Crash on May 6, 2010 evaporated 600 billion dollars in 20 minutes


| | Source: Dirk Brockmann

Epidemic Spreading

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Many unsolved problems of the world result from

systemic instabilities"

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Cascade Effects

in Complex Networks


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How the Interplay of Risk and Complexity Creates Uncertainty


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Diffusion of Walmart


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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 effects

5.  Predictability goes down 6.  External control is difficult 7.  Larger vulnerability

Change of perspective (from a component- to an interaction-oriented view) will reveal new solutions! Need a science of multi-level complex systems!


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Mousetrap fission, by Gerhard G. Paulus, University of Jena, https://www.youtube.com/watch?v=Wiz1VVLYgl4

Loss of Control through Cascade Effects

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EU project IRRIIS: E. Liuf (2007) Critical Infrastructure protection, R&D view

Failure in the continental European electricity grid on November 4, 2006

Cascade Effect and Blackout in the European Power Grid


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Video by Frank Schweitzer et al. Dirk Helbing, Professor of Computational Social Science

Cascading Effects During Financial Crises

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How the Banking Network Changed

From: Haldane


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Different recipes, new solutions, and a paradigm shift in our understanding of the world are needed.

Too Much Networking Can Cause Self-Destabilization: Breakdown of Cooperation


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Connection density (%)Perc

enta

ge o

f coo

pera

tion

(%)

0.00 0.05 0.10 0.15 0.20 0.25 0.300.0

0.2

0.4

0.6

0.8

1.0

Too Much Connectivity Can Be Bad



Explosive Epidemic Spreading with Budget-Constrained Recovery

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Complex Interdependencies


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We now have a global exchange of people, money, goods, information, ideas…

Network interdependencies create pathways for disaster spreading! Need adaptive decoupling strategies.

Globalization and technological change have created a strongly coupled and interdependent world

Risk Interconnection Map World Economic Forum

Networking Is Good, But Promotes Cascade Effects


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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.


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blackout

gas stations out of order

traffic lights off

public and private transport down

pumps without power

use of candles

wired phone network busy

advisory to boil water

no electricity to boil water

service disruptions of cellular phones

firefighting required

Causality Network for the Blackout in North America 2003 (Detail)


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Secondary and Tertiary Disasters



Causality Network for Earthquakes

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Interdependencies in Energy Supply


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Nuclear Power


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Solar Power


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Gas Supply


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Biofuels


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Food Prices and Social Unrests


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Arab Spring


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The Arab Spring


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transition

democracy

hierarchy

Transition from hierarchies to democracies (source: Jürgen Mimkes)

World GNP and fertility

0

5 . 0 0 0

1 0 . 0 0 0

1 5 . 0 0 0

2 0 . 0 0 0

2 5 . 0 0 0

3 0 . 0 0 0

3 5 . 0 0 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

GN

P p

er

pe

rso

n i

n U

S $

h iera rc hies

tran sition

d em oc ra cies

tran sition lin e

de m o c rac i es

h ie ra rc h ies

Political Cascading Effects


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Could Europe’s History Be Simulated?


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Visualizing Empires Decline


| | http://www.sueddeutsche.de/politik/streit-beigelegt-einigung-ueber-foederalismusreform-1.413140"

Source: ddp images/Marcus Brandt"

The Problems of the World Are Complex"

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Cascading Effects During Financial Crises"

Social Dilemma Problem"-  Global Warming"-  (Financial Crisis)"-  Free-Riding"-  Tax Evasion"-  Environmental Pollution"-  Environmental Exploitation"-  Overfishing"

Climate Change"

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Financial Crisis"

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War in Ukraine"

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"

PERSPECTIVEdoi:10.1038/nature12047

Globally networked risks and howto respondDirk Helbing1,2

Today’s strongly connected, global networks have produced highly interdependent systems that we do not understandand cannot control well. These systems are vulnerable to failure at all scales, posing serious threats to society, even whenexternal shocks are absent. As the complexity and interaction strengths in our networked world increase, man-madesystems can become unstable, creating uncontrollable situations even when decision-makers are well-skilled, have alldata and technology at their disposal, and do their best. To make these systems manageable, a fundamental redesign isneeded. A ‘Global Systems Science’ might create the required knowledge and paradigm shift in thinking.

G lobalization and technological revolutions are changing our pla-net. Today we have a worldwide exchange of people, goods,money, information, and ideas, which has produced many new

opportunities, services and benefits for humanity. At the same time,however, the underlying networks have created pathways along whichdangerous and damaging events can spread rapidly and globally. This hasincreased systemic risks1 (see Box 1). The related societal costs are huge.

When analysing today’s environmental, health and financial systemsor our supply chains and information and communication systems, onefinds that these systems have become vulnerable on a planetary scale.They are challenged by the disruptive influences of global warming,disease outbreaks, food (distribution) shortages, financial crashes, heavysolar storms, organized (cyber-)crime, or cyberwar. Our world is alreadyfacing some of the consequences: global problems such as fiscal andeconomic crises, global migration, and an explosive mix of incompatibleinterests and cultures, coming along with social unrests, internationaland civil wars, and global terrorism.

In this Perspective, I argue that systemic failures and extreme events areconsequences of the highly interconnected systems and networked riskshumans have created. When networks are interdependent2,3, this makesthem even more vulnerable to abrupt failures4–6. Such interdependenciesin our ‘‘hyper-connected world’’1 establish ‘‘hyper-risks’’ (see Fig. 1). Forexample, today’s quick spreading of emergent epidemics is largely a resultof global air traffic, and may have serious impacts on our global health,social and economic systems6–9. I also argue that initially beneficialtrends such as globalization, increasing network densities, sparse use ofresources, higher complexity, and an acceleration of institutional decisionprocesses may ultimately push our anthropogenic (man-made or human-influenced) systems10 towards systemic instability—a state in which thingswill inevitably get out of control sooner or later.

Many disasters in anthropogenic systems should not be seen as ‘bad luck’,but as the results of inappropriate interactions and institutional settings. Evenworse, they are often the consequences of a wrong understanding due to thecounter-intuitive nature of the underlying system behaviour. Hence, conven-tional thinking can cause fateful decisions and the repetition of previousmistakes. This calls for a paradigm shift in thinking: systemic instabilitiescan be understood by a change in perspective from a component-oriented toan interaction- and network-oriented view. This also implies a fundamentalchange in the design and management of complex dynamical systems.

The FuturICT community11 (see http://www.futurict.eu), which involvesthousands of scientists worldwide, is now engaged in establishing a

‘Global Systems Science’, in order to understand better our informationsociety with its close co-evolution of information and communicationtechnology (ICT) and society. This effort is allied with the ‘‘Earth systemscience’’10 that now provides the prevailing approach to studying thephysics, chemistry and biology of our planet. Global Systems Sciencewants to make the theory of complex systems applicable to the solutionof global-scale problems. It will take a massively data-driven approachthat builds on a serious collaboration between the natural, engineering,and social sciences, aiming at a grand integration of knowledge. Thisapproach to real-life techno-socio-economic-environmental systems8 isexpected to enable new response strategies to a number of twenty-firstcentury challenges.

1ETH Zurich, Clausiusstrasse 50, 8092 Zurich, Switzerland. 2Risk Center, ETH Zurich, Swiss Federal Institute of Technology, Scheuchzerstrasse 7, 8092 Zurich, Switzerland.

BOX 1

Risk, systemic risk and hyper-riskAccording to the standard ISO 31000 (2009; http://www.iso.org/iso/catalogue_detail?csnumber543170), risk is defined as ‘‘effect ofuncertainty on objectives’’. It is often quantified as the probability ofoccurrence of an (adverse) event, times its (negative) impact(damage), but it should be kept in mind that risks might also createpositive impacts, such as opportunities for some stakeholders.

Compared to this, systemic risk is the risk of having not juststatistically independent failures, but interdependent, so-called‘cascading’ failures in a network of N interconnected systemcomponents. That is, systemic risks result from connections betweenrisks (‘networked risks’). In such cases, a localized initial failure(‘perturbation’) could have disastrous effects and cause, in principle,unbounded damage as N goes to infinity. For example, a large-scalepower blackout can hit millions of people. In economics, a systemicrisk could mean the possible collapse of a market or of the wholefinancial system. The potential damage here is largely determined bythe size N of the networked system.

Even higher risks are implied by networks of networks4,5, that is, bythe coupling of different kinds of systems. In fact, new vulnerabilitiesresult from the increasing interdependencies between our energy,food and water systems, global supply chains, communication andfinancial systems, ecosystems and climate10. The World EconomicForum has described this situation as a hyper-connected world1, andwe therefore refer to the associated risks as ‘hyper-risks’.

2 M A Y 2 0 1 3 | V O L 4 9 7 | N A T U R E | 5 1

Macmillan Publishers Limited. All rights reserved©2013

Global Systems Science

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Humans have created tightly connected systems and networked risks, which has led to a world we do not understand and cannot control well. Systemic risks and extreme events are consequences of this. " "However, systemic instabilities can be understood by a change in perspective from a component-oriented to an interaction- and network-oriented view. This also entails a fundamental change in the design and management of complex dynamical systems. Establishing a "Global Systems Science" will allow us to better understand our information society with its close co-evolution of information and communication technology (ICT) and society. This effort is allied with the "earth system science" that now provides the prevailing approach to studying the physics, chemistry and biology of our planet." "Global Systems Science makes current theories of crises and disasters applicable to the solution of global-scale problems, taking a massively data-driven approach that builds on a serious collaboration between the natural, engineering, and social sciences, i.e. a grand integration of knowledge."

Global Systems Science

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Global Participatory

Platform

Living Earth

Simulator create new technology provide data

Pluralistic Reputation

System

Planetary Nervous System

Create systems to sense & understand

Turn data into information

What is?

Develop models to simulate &

predict

Turn information into knowledge

What if?

Build Platforms to Explore & Interact

Turn knowledge into wisdom What for?



§  Complex systems are difficult to understand, predict, and control"

§  But they tend to self-organize emergent structures, properties, and functions"

§  The interactions within the system determine the outcome of self-organization"

§  With the right kinds of interaction rules, everything works wonderfully and efficiently (“invisible hand”)"

§  How to find suitable interaction rules? (computer simulations, experiments, interactive virtual worlds, exploratories)"

§  How to change them? (real-time data and real-time feedback)"

§  How to gain these data? (Nervousnet)"§  How to produce the feedbacks? (multi-

dimensional finance/value exchange)" multi-dimensional real-time feedback"

real-time measurement"

How to Make Complex Systems Work

| | (Image: dmd/ADAC)

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Any Questions?


complexity and global systems science · business opportunities: facebook’s value, for example,...

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