Visioneer - Formulating Grand Fundamental Challenges

VISIONEER WP4: Formulating Grand Fundamental Challenges Outcomes of web consultations and workshop discussions Executive Summary Future and Emerging Technologies − Proactive Initiatives (FET − Proactive) is preparing the next work programme for 2011–2012 and later. As part of this process, in order to identify new research challenges, FET has initiated the VISIONEER project with the aim of identifying future grand challenges in the socio-economic sciences, in particular those which can be addressed with complexity science and ICT. This report summarises the contributions related to work package 4 (“Future Grand Challenges”) submitted through the VISIONEER web site and presents the outcomes of the discussions, which took place during a workshop held in Zürich from Jan 13th-15h.

Introduction Throughout history, scientific progress has often been stimulated by directed efforts to tackle challenging questions and problems. Challenges articulating a specific vision help to harness the required energy and to focus broad scientific expertise -- often in areas not initially recognised -- to make decisive breakthroughs, especially those having immediate practical implications. This unit of Visioneer is focused on elaborating a set of grand Future and Emerging Technologies challenges regarding the modelling and integrative design of socio-economic systems with ICT technologies. A list of such grand challenges, described briefly in the following pages, has been produced by consultations with a diverse group of leading scientists, who aimed to identify exceptionally demanding scientific challenges at the interface of ICT and social science, the pursuit of which will likely stimulate both rapid progress in many areas of fundamental and applied ICT and also help addressing issues of great social or economic importance.

The Grand Challenges The following pages describe the 20 Grand Challenges which have been identified. All share a unifying vision in that they aim to tackle key issues which demand both the application of modern ICT (or the development of new technologies) and a much deeper scientific appreciation of the difficulties of understanding and learning to manage or exploit so-called 'complex systems,' including communications networks, computational systems, natural ecologies, traffic or logistics systems, economies and so on, the behaviour of which emerges out of vast webs of interactions and feedbacks. The traditional concepts and perspectives of science often fail to provide much insight into such systems,which demand radical efforts to build new ways of doing science, often by exploiting tools and ideas from ICT.

Grand Challenges List 1. Agent-based models in finance and economics 2. Monitoring and control of urban traffic systems 3. Production and distribution systems inspired by biology 4. Promoting reliable information 5. Self-organizing and adaptive governments and organizations 6. Modelling, detecting and avoiding intergroup conflict 7. Human-machine social networks 8. Ultra-dimensional ICT-enabled case studies for modern social science 9. ICT for understanding human mobility in crisis situations 10. Supporting revolutionary new modes of ICT-enabled value exchange 11. Understanding "irreducible complexity" in global systems 12. Reverse social engineering 13. Working out a "Plan B" to Save our Society 14. Methods for navigating complex societal problems 15. Capturing and Freeing the Academic Meta-Literature 16. Enabling the emergence of ethical ICT 17. Creating an Innovation Accelerator 18. The Self-Organising Web 19. Developing Crisis Observatories 20. A Multi-National Adaptor

Annexes Annex I: Terms of Reference Annex II: VISIONEER Web Site Annex III: Visioneer Workshop Jan 13th -15th Annex IV: Current Shortcomings in Socio-Economic Research

1. Agent-based models in finance and economics It's now widely recognized that traditional methods in economics and finance fail to describe fundamental phenomena of immediate social and economic importance, especially the susceptibility of economic systems to sudden crises and other abrupt transitions between different dynamic regimes. Today's economic models neglect strong interactions between economic agents, or rely on unrealistic assumptions. As participants at the 2008 Dahlem Workshop on Economics concluded, the failure of economics can be traced "...to the profession’s insistence on constructing models that, by design, disregard the key elements driving outcomes in real-world markets."

Today's ICT has now made it possible to overcome these problems, at least in part, through agentbased models -- models allowing direct simulations of the interactions of large numbers of computational agents with plausible behavioural rules in an attempt to re-create and predict complex collective phenomena that emerge from the lower (micro) level of actors. The development of such models could be greatly accelerated by demonstrating the ability of these models to give practical insight into real world problems.

Challenge/Area Two areas appear to be particularly timely for an intense research focus -- first, in modelling of financial systems and their vulnerability to instability, and second, in forecasting macroeconomic variables such as inflation.

Modelling financial crises In the aftermath of the financial crisis, governments and regulators globally stand in great need of methods for measuring and assessing systemic risks -- risks tied not to the well being of any one financial institution, but to the dense webs of interdependence among many institutions. Currently, as numerous experts have recently testified before US congress, such methods simply do not exist; much of contemporary economic theory assumes that markets tend to be inherently stable and selfregulating, despite a string of major market crises over the past few decades.

The current financial sciences do not have the tools to monitor systemic risks, especially those created by complex derivatives and other modern financial innovations. Hence, the emerging consensus of financial experts and scientists from many areas is that new methods are needed to foresee such risks. Agent-based modelling is one method with recognized potential.

Forecasting macroeconomic variables International institutions such as the IMF, national governments and major enterprises all depend on macroeconomic forecasts of quantities such as GDP, inflation and unemployment. These quantities are "measured" by public statistical institutes and other institutions, yet current forecasting methods, based on standard econometrics, have numerous problems. A recent review acknowledges that most forecasters fail to predict recessions in advance, and even to recognize them contemporaneously, and systematically err in their estimates of growth and inflation. (R. Fildes and H. Stekler, The state of macroeconomic forecasting, Journal of Macroeconomics 24 (2002) 435–468.)

Agent-based modelling can capture micro-level details of economic reality and simulate their effects on macro-economic outcomes in a way that goes far beyond traditional economic methods.

Hence, it is an exceptionally promising route to improving macroeconomic forecasting methods.

Topics This research would make a bold effort to apply agent-based models to improving practical management and foresight skills in key areas of economic science. It would involve researchers from areas including finance and economics, as well as computer science, statistics, statistical physics, sociology and history. It would also help transform the nature of agent-based models, as truly large-scale models -- possibly modelling socio-economic processes on a global scale -- will require flexibility going far beyond today's models. They will, for example, allow easy interoperability with large-scale data sets, combine real-time streams of information with historical datasets, and allow models to "self-calibrate" during the simulation, as more data become available with time. A visionary effort in this direction will also help establish coherent and practical standards for interoperability and integration of agent-based modelling systems in general, as well as powerful visualization tools to help people understand model results.

Target Outcome The outcomes envisioned include one or more agent-based models of cascading bankruptcies in, for example, the inter-bank market, and also models of stock exchanges. In macroeconomics, the outcome would be an agent-based macroeconomic forecasting computer program including every known aspect of the economy of a state and running on an appropriate hardware platform. Work along the way would stimulate advances in a range of fields, including computer science (software and hardware for agent-based simulations), macroeconomics (the development of computational economics), statistics (the assessment of forecasting methods with small sample sizes), history (a deeper perspective on the causes of major economic crises) and sociology.

Expected Impact The impact of important advances in this area would be dramatic. Tools for evaluating systemic risks are currently among the most pressing needs in finance. The development of methods able to identify potential systemic risks would allow possible interventions by regulators at an early stage, and also indicate how such interventions could be carried out safely. Methods such as these could literally save trillions of dollars globally by helping to avoid or mitigate a future crisis. Similarly, enormous economic benefits would follow from an improved ability to make accurate macroeconomic predictions. Governments and other public agencies could use better tools to discuss and implement macroeconomic policies, including budget laws.

The impact of success in these challenges would also demonstrate in dramatic fashion the enormous potential for ICT-based tools to further policy making on the basis of sound science. Policy makers often hesitate to use tools they cannot easily understand, yet it's clear that ICT must play a role in helping us penetrate the often forbidding collective complexity of today's economic and financial systems. The proposal has a clear goal and is simple to explain to policy makers.

Suitability for ICT and FET This grand challenge is very well suited to ICT and FET as it will demonstrate the broad potential promise of ICT tools to revolutionize economic science and economic policy making. The work envisioned with also contribute to advances in software tools for agent-based simulations and hardware tools for scientific computing.

Communities

Several communities could be involved in a collaborative effort on macroeconomic forecasting including economists, sociologists, historians, computer scientists, applied mathematicians, statistical physicists and policy makers. This would be a truly cross-disciplinary effort re-designing the European scientific landscape.

There exists an emerging community attempting to build agent-based models of to probe the origins of financial instability. It is quite interdisciplinary (economists, physicists, computer scientists) and scattered in the UK, Italy, Finland and elsewhere.

2. Monitoring and control of urban traffic systems Traffic congestion has an enormous negative impact on the daily lives of millions of people and on our society's productivity and health. Authorities in all European nations struggle to maintain road infrastructure adequate to ever increasing traffic demands. Yet ICT technologies offer tremendous opportunities for improving traffic flow and avoiding congestion by greatly improved monitoring of traffic conditions and automated controls of traffic lights and other mechanisms. This grand challenge is to greatly reduce congestion in large cities through the introduction of Intelligent Transportation Systems (ITS) technologies and new sensing hardware, while still preserving the autonomy of individual drivers.

Challenge / Area A key objective of this effort will be to improve arterial traffic and congestion monitoring so as to create a wealth of reliable data. Such data are crucial to developing models of traffic flow and required to test the effectiveness of various possible strategies for controlling congestion. The reliable estimation of travel times and other performance measures remains very difficult on urban streets (arterials) as it requires the kind of extensive sensor infrastructure that is normally found only on motorways (where fixed sensors gather data at points separated by no more than about one kilometre). Systems of fixed sensors, moreover, often cannot collect the kind of data necessary for describing the richer dynamics of dense flows on main urban roadways.

For controlling traffic, systems hitherto have generally been pre-programmed and custom-designed with little control over the micro-interventions triggered by specific macroscopic congestion problems. Yet neither centralized nor fully decentralized control of traffic signals can guarantee global optimum solutions in the presence of highly complex urban traffic.

Hence, the key research challenge is to develop and implement a broad strategy for partitioning a large road network into more manageable sub-networks (reservoirs) which can be modelled in detail, and to develop a hierarchical feedback control network operating at multiple levels. This may require different data granularity at each level. Another important issue is to determine the level of monitoring required (penetration rates of sensors, data frequency, etc.) to guarantee “observability” of the state of the system, i.e. accurate estimation of performance measures. Otherwise the controller will never be able to determine accurately the current state of the system nor use this knowledge to reduce traffic congestion.

Topics Our long-term vision is based on a multi-sensory system that with the use of appropriate logic can issue robust and effective traffic signals. As the behavioural uncertainty of any complex road system is extremely high, a fully centralized control may not be efficient and/or effective. Key challenges include: • • •

to learn techniques for partitioning a heterogeneous urban network in neighbourhoods with well-defined representations in a model; to learn how to allocate or locate available sensing resources between different types of sensors (fixed, mobile, etc.) to maximize system observability as a function of the topology, the level of congestion and the types of control required; to develop and test effective multi-level techniques for hierarchical control.

Some examples of more specific control hierarchy and data needs are:

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During periods in which congestion recurs in one region, we generally try to maximize the total output (trip endings per unit time) from this region by controlling traffic flowing from adjacent city sub-regions with traffic signals in their boundaries. At these sub-regions, we zoom in to a finer scale and attempt to maximize the traffic flow on these routes by dynamically changing local traffic signal settings (adjusting green times and offsets).

Control at the finer level requires more detailed data, and will demand systems capable of the accurate estimation of queue lengths at each link versus the average density among all links.

During a special event where thousands of people need to move in a short time, control at the higher level should keep areas around this event uncongested to allow the beginning of the related massive movements. Meanwhile, control at finer scales may need to maximize pedestrian crowd movements and minimize potential crowd-vehicle interactions by decreasing car speeds during this period. Additional sensing technology to identify pedestrian movements may be required in the latter case.

Target Outcome The specific target outcome of this grand challenge is to develop and demonstrate Intelligent Transportation Systems (ITS) technologies and new sensing hardware which can applied to reducing congestion.

Expected Impact The most obvious and important impact from this grand challenge will be significant reductions of traffic congestion in major European cities. This will eliminate a major source of daily irritation and wasted time for millions of people, as well as a principal cause of lost economic production and additional pollution.

This project will also further the development of multi-disciplinary scientific collaborations of the kind necessary to bring ICT-based adaptive management and control techniques to a wide set of modern problems, not only in traffic, but in related areas such as logistics.

Suitability for ICT and FET The management of complex social systems will be a key area of future applied ICT research and development. This challenge is suited to ICT and FET because it will push technology in this area well beyond what is currently possible, and aim for technologies with enormous potential impact on society.

Communities These topics and challenges require multi-disciplinary research with scientists from physics, economics, computer science, transportation engineering, applied mathematics, etc.

3. Production and distribution systems inspired by biology Growing populations, environmental concerns and economic constraints have driven engineers to seek increasingly efficient solutions for logistic systems, especially through the application of modern ICT technologies. Many apparent solutions, however, while seeming superficially optimal, actually show great vulnerability to variations in supply and demand or other system shocks. A recent discovery is that logistic control can be achieved more successfully, and in a more robust and resilient way, by learning to mimic the control principles used by biological systems, which can flexibly adapt to unpredictable, fluctuating conditions. This grand challenge aims to demonstrate the potential for a bio-inspired “BioLogistics” for dynamic organization processes and man-made logistics (including nano-logistics), using principles of modularity, self-assembly, self-organization, and decentralized coordination.

Challenge / Area Transportation networks bring people and goods to their destinations in a highly organized fashion.

The network of metabolic reactions in a cell is responsible for providing a wide range of substances at the right time in the right proportions. How do these systems ensure robustness with respect to perturbation? How can the systems react rapidly to important changes in their environment?

The challenge is to understand the design principles of natural systems, and to exploit them for purposes of industrial production. Maximizing efficiency and profits in organizations depending on complex logistic systems typically requires the minimization of redundancies and safety margins, while keeping failure rates acceptably low. When connecting such systems into larger networks, the likelihood of coincident failures is often underestimated. This is particularly true for many large and complex logistic systems involving dense webs of non-linear interactions between diverse kinds of elements, where failures often propagate through the system. Such systems -- today the norm in global enterprises -- as a rule exhibit feedback loops and reinforcement effects, while natural fluctuations may trigger instabilities, cascade failures and regime shifts (i.e. transitions to a different state or operation mode).

Biological logistic systems do an excellent job in using, distributing, and recycling sparse resources, and their efficiency and robustness to environmental perturbations are key to their survival.

Millions of years of evolution have created logistic systems of such large variety and astonishing performance that one can hope to reveal a multitude of yet undiscovered functional designs and heuristic solutions. For example, cells have to produce or import, correctly transport, localize and monitor the activity of thousands of different molecules. The human body even represents a “logistic universe” comparable with the phenomenal complexity of man-made global logistics: It manages to transport millions of different materials (nucleic acids, proteins, lipids, carbohydrates and metabolites) to different destinations, establishing billions of molecular and cellular interactions (e.g. neuronal connections). This is done with an incredibly low energy consumption of a 60-100 Watts bulb (<2,000 kCal/day) and at very high reliability.

Topics Systems biology and logistics have a strong natural resonance as both depend on dynamical processes in complex networks. Abstracting cellular processes in terms of networks will allow for re-scaling the microscopic processes to the macroscopic application. Lessons learned from the logistics applications will feed back into systems biology and help ask refined questions about the evolutionary shaping of cellular processes.

Common topics of the two disciplines range from robust regulatory devices, the tolerance of networks for damage and noise, architectures with high synchronizability and efficient information transport, searches for optimal steady states under well-defined external conditions to ways of mastering the combinatorial explosion of information inherent in complex systems.

Target Outcome The target outcome of this challenge is to learn design rules for optimized and highly competitive logistics systems based on bio-inspired ideas.

Expected Impact Successful development and implementation of techniques for improved logistic performance will have an enormous economic impact for industries and organizations in Europe and also globally.

Given the importance of such systems to virtually all businesses, even small improvements in efficiency, or in the ability of such systems to avoid break downs and to continue functioning in the face of unexpected fluctuations in supply or demand, would lead to vast cost savings. Success will also have a major influence in furthering the scientific applications of bio-inspired techniques not only in logistics but in many other areas, including the management of telecommunications systems, the Internet and so on.

For systems biology, this project will also provide a valuable test setting for developing a deeper understanding of biological design principles and measures of their efficiency properties.

Suitability for ICT and FET This challenge is strongly driven by the vision of bio-inspiration as a way forward in ICT applications, and hence is very well suited for ICT and FET. It addresses a challenge at the very forefront if modern ICT -- the management of complex systems of interacting components.

Communities Success in this challenge requires the interaction of a wide range of communities including biology, mathematics, control-system engineering, logistics, physics and computer science.

4. Promoting reliable information Information in post-industrial societies is as important as air, water or food. Although the access to various information sources is broader than it was hundred years ago, information is very frequently polluted by useless or non-important messages (spam or advertisements), misleading signals sent by ill-informed sources (tabloids, for example) and other sources that intentionally broadcast invalid or false facts supporting certain aims (e.g. newspapers representing political groups). Even more importantly, we are now witnessing a massive transformation of the way information is selected and presented, which does not guarantee its reliability. Novel forms of social and political interaction mediated by emerging web technologies (writable web, social networking, web2.0) increasingly challenge the traditional authoritative role of professional expertise and cultural institutions in the certification of quality. Such modes operate outside of -- and sometimes in conflict with -traditional mechanisms of knowledge production and dissemination.

The web as a whole, for example, is a source of non-certificated information. The lack of certification departs from the history of Western civilization, in which quality was often guaranteed by professional expertise and on the institutions of culture, education and science. The web replaces traditional "certifying" institutions with a number of social architectures said to harness the virtues of the mythical collective intelligence and the wisdom of crowds. These platforms (Google's PageRank, for example, the numerous collective content filters, social bookmarking sites, microbroadcasting applications, etc.) have emerged to provide shortcuts to information in the overloaded peer-production web. These engineering tools play a crucial epistemic function by providing a distributed classification and organization of knowledge; in so doing, they also act to undermine, or displace, the role of respected institutional authorities.

Consequently, there is an urgent need to create methods for information cleaning that would be cheap, reliable and commonly accessible. The mechanics of such tools need to be investigated, as well as the cognitive practices associated with the attribution of authority to them (sometimes referred to as 'deference'). Field research must also address the inherent epistemic and cognitive biases associated with such applications. Research should especially show the way to the design of more robust, theory-driven systems for the attribution and recognition of authority in the absence of centralized certifying institutions.

Challenge / Area Spam filters only act crudely to prevent limited kinds of information pollution. But more generally, there exist no global tools able to counter this effect. More importantly, we lack a common understanding of the danger of information pollution, as well as an understanding of how we might be able to produce "clean" information.

The challenge is to develop methods able to identify reliable information sources, and to do so with technologies suited to massive deployment in the web environment. Methods to be explored include data mining, machine learning, complex networks, diffusion processes, correlation measures, time series analysis as well as models of collective effects and avalanche phenomena.

Topics The central challenge of this project is information cleaning. The results will be useful for development of novel ICT services able to provide reliable information to ordinary citizens.

The project will increase social confidence in the information quality provided by ICT media. The research will exert a substantial impact on:

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single users, who will be released from the interference of spam-like information, markets, which work more efficiently given clean information on products and services, society, which will benefit from less manipulation by misleading information.

Target Outcome The target outcome is development of a system able to extract clean information from noisy/corrupted signals provided by ICT media. End-users of the system would be ordinary citizens.

Expected Impact Our societies are now changing under the pressure of a huge transformation in the way information is selected and presented. New information technologies influence human social practices, and may undermine hitherto trusted methods of knowledge production and dissemination. The potential impact of this grand challenge is hard to overstate given the importance of reliable knowledge to the proper functioning of individuals within society and for the governing process itself. Revolutionary progress in this area could be the key to providing a more stable future for all societies as they undergo further massive technology driven changes.

Suitability for ICT and FET This vision-driven challenge targets one of the most important issues for modern ICT and requires the development of completely novel IC technologies able to 'clean' information in some effective way. Hence, it is appropriate for ICT and FET in focusing on visionary issues in ICT with very broad relevance to social well being.

Communities The topic is addressed to communities working on information spreading, data mining, modelling complex systems, artificial intelligence systems and social scientists interested in impact ICT on modern societies. Strong interdisciplinary collaboration would be expected.

5. Self-organizing and adaptive governments and organizations Most of our current organizations have a centralized, top-down structure. This limits the complexity of problems that organizations can cope with, and also limits their adaptability. Self-organization can provide adaptivity in social systems and enable them to cope with more complex situations.

Challenge / Area ICT can be a tool for supporting the self-organization and adaptivity of governments and organizations. Current technologies can be extended to reduce delays, increase accountability, detect bottlenecks, and suggest improvements in service, among other aspects (Gershenson, 2008).

There are several domains in which self-organization could improve the performance of organizations, including: Education Traditional educational systems try to standardize teaching. This is the only option with a limited number of teachers. However, every student has different learning requirements. ICT systems can contribute to personalize education according to the needs of each student, without increasing its cost.

Healthcare Healthcare in developed countries accounts for more than 10% of the national expenses, and these costs will rise in coming years. Yet organizational deficiencies undermine healthcare effectiveness. ICT could greatly improve the management of complex healthcare demands, yielding a lower cost-to-result ratio.

Governance The complexity of national and international relations has increased considerably in recent decades, especially in Europe, given the diversity of scales at which governance must take action (e.g. districts, cities, regions, countries, international organizations). ICT could be used to better facilitate governance and enhance democratic aspects of societies (Rodriguez and Watkins, 2009), as well as to allow the more direct participation of citizens in decision-making processes (Rodriguez et al., 2007), to increase government accountability and to improve the efficiency of organizations.

A primary feature of today's emerging technologies, especially those facilitating social interaction, is the role of 'decentralized individual action'. Along with new forms of participation, new styles of governance are emerging to self-regulate decentralized, networked communities, showing unique ways for attribution of authority (for example, in the merit-based boards of regulators of free software projects). Ambitious research should explore decentralized networks not only as tools for increasing the participation in traditional institutions, but in supporting completely new styles of governance that naturally encourage social norms and trust among strangers, provide clear mechanisms for sanctioning cheaters and serve as a baseline for reforming or building new political institutions.

Target Outcome One of the most promising scientific approaches to understand complex systems is agent-based modelling (Helbing, 2009), which has its roots firmly in ICT. Because of this, it is natural that ICT will provide the tools required to cope with the complexity of social systems. The decentralization and distribution required to build adaptive, self-organizing systems can be only achieved with ICT. The Cybersyn project in Chile in the early 1970's already proved the usefulness of this approach (Miller-Medina, 2005); the project was unfortunately cancelled following the 1973 military coup.

The target outcome of this challenge lies in specifications and implementations of ICT systems to

assist in the adaptation and self-organization of governments and organizations.

Expected Impact Traditional organizations try to predict the future in order to try to control it. However, the inherent complexity of social systems limits their predictability; in particular, human societies perpetually create new information which changes their future course. Because of this inherent complexity in social systems, adaptation becomes a necessary complement to prediction, as it enables a system to respond to unforeseen situations by itself.

Self-organization can provide systems with this adaptability. In a self-organizing system, elements interact to reach a global configuration. Self-organizing governments and organizations necessarily need to be based on ICT, with the key elements (people, departments, firms and so on) interacting using ICT, so influence of their interactions can be monitored and acted upon. The ICT system can then suggest which behaviours are the most crucial for achieving efficient self-organization and adaptation.

The expected impact would be highly beneficial for society in general. Adaptive governments would be able to respond more efficiently to changes in demand -- from an ageing population, new emerging technologies, rapidly evolving social trends and so on. Also, countries that manage to develop and implement adaptive organizations and governments will likely have competitive advantages over those that continue using traditional approaches which cannot cope with complexity.

Suitability for ICT and FET The study of complex systems has become increasingly relevant to ICT and FET in recent years, because ICT systems themselves have begun to surpass the limits of direct human management, and also because ICT has come to be recognized as the basis for creating systems capable of managing and responding to complexity in real world systems, including economies, ecosystems and climate.

However, we still lack the kind of integrated research framework that would allow achieving the proposed goals. In this regard, necessary lines of research are both theoretical and practical.

On the theoretical side, we need new formalisms to describe, model, study, and understand complex systems. This must start from existing formalisms including agent-based modelling, network theory, data mining, system dynamics, cybernetics and non-linear dynamics, but explore specific issues of how complexity science can support the vision of more adaptive governments and organizations.

More practically, the implementation of adaptive governments and organizations poses several challenges, technical and social. ICT must be further developed to overcome technical challenges in the areas of communication networks, distributed databases, security, user interfaces, on-line collaboration tools, etc. Also, further studies should explore routes to the social acceptance of such a novel approach to governance.

Communities This challenge has a highly interdisciplinary nature, demanding expertise from at least the following areas: computer science, governance, management, healthcare and law, psychology, economics, sociology and political science.

6. Modelling, detecting and avoiding intergroup conflict Political and social interaction increasingly takes place on-line through blogs, on-line fora, websites of political organizations and movements and so on. In general, these sites and their users evolve a world of intense polarization and frequent conflict. Hence, this development offers an unprecedented opportunity for scientists to design, construct and employ ICT based systems that might allow the detailed modelling, detection and (possibly) avoidance of intergroup conflict, not only in the political realm, but also in multi-ethnic societies. To realize this ambitious goal, a range of challenges will need to be addressed in existing theories and methods for the analysis of on-line information ecologies.

Challenge / Area Inter-cultural conflict is a long-standing focus of research in the social sciences. Today such conflicts pose an increasing threat to the stability of western societies, due to an explosion of ethnic and cultural diversity. The rise of ICT-based social and political communication offers an unprecedented opportunity to study the dynamics of such conflict in a data-rich environment, which may allow the development of tools for modelling, detecting and avoiding intergroup conflict in multi-ethnic societies.

Key problems to be addressed include: •

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Develop theory and tools that would allow the automated identification of active communities in large scale on-line networks, especially through contributions to blogs, political websites, or social-networking sites, as well as detailed data capture of these communities' dynamics. Current research on identifying communities in networks typically focus on homogeneous networks, such as records of phone calls or email contacts; we need new techniques for collecting and integrating far more heterogeneous sources of data.

Extend existing tools for community detection so they also analyse the content of interactions. The aim is to identify potential conflicts between existing or newly emergent communities in the web of social-political interactions on the internet. Such methods for community detection need to take into account not only network structure, but also agreement or disagreement between individual nodes on politically or socially relevant issues. Current research on community detection typically neglects the contents of communications. Moving beyond this requires the development of intelligent content analysis methods.

Develop algorithms to infer from the analysis of the structure and content of on-line interactions the extent to which a network segregates into mutually antagonistic factions.

Theories from social sciences about social integration in diverse groups offer a starting point, notably research on the role of “cross-cutting social ties” and “demographic fault lines” from sociology, social psychology and organizational psychology.

Learn to identify the potential for conflict and/or integration between subgroups with distinct social identities from a network of positive and negative interactions among groups with a common social identity. In particular, based on existing theories about social identity, develop tools able to discern how much a set of on-line actors overlap in positive and negative evaluations of the same political issues, public persons, other groups and so on.

The challenge is to identify when new potentially conflicting identities emerge from other groups (e.g. an "immigrant" identity emerges in a country with many differing cultural backgrounds), or when more inclusive identities emerge that may provide a common basis for agreement between otherwise disconnected factions in a population.

Finally, develop integrated tools to conduct minimally-invasive interventions aimed at

avoiding or reducing the intensity of potential conflicts and to promote social integration.

ICT systems may be able to detect potential bases for agreement between societal communities even if they have very little interaction on-line. Minimally-invasive interventions could involve, for example, displaying links to discussion fora or sites that would tend to attract attention to previously unknown groups with whom a basis for agreement exists, thereby seeding potentially beneficial interactions. The challenge is to develop models predicting whether subgroups with particular sets of opinions and/or norms would likely be “compatible” and how their evaluation of their own group and of other groups might change if new possibilities for interaction were created.

Topics Develop theories and methods to achieve: • • • • •

Identification of communities in heterogeneous networks supporting on-line interaction.

Automated content analysis of political and social communities on-line.

Automated analysis of the potential for integration or segregation in the structure and content of an on-line network of political and social communications.

Tools for detecting emergent group identities and to analyse the potential for subgroups with distinct identities to merge into larger groups with more inclusive social identities.

Tools for simulating the likely influence of minimally invasive techniques on subgroups with distinct identities in the internet. Also, development of automated tools for designing and implementing such interactions if their expected effects on social integration are desirable.

Target Outcome The target outcome is the development of theories and tools for the ICT-based identification of potential or emerging conflicts between subgroups in a multicultural society, and also for minimal interventions to promote better social integration.

Expected Impact The main impact of a breakthrough in this area would be a set of techniques and tools able to foster sustainable social integration in multicultural societies, clearly an aim of great importance for all European nations today. Work on this grand challenge will also have a major impact on ICT through the development of advanced theories and techniques for the collection and analysis of data about large-scale on-line communications, especially in the areas of automated community detection and automated content interpretation.

Suitability for ICT and FET This grand challenge fits very well with ICT and FET as it requires cutting-edge ICT technologies and key advances in the automated analysis of large-scale on-line networks. It aims to develop unprecedented means for analysing the rich structure and content dynamics of highly complex real world ICT-mediated social networks.

Communities Expertise is required from computer sciences, complex system science, cognitive sciences, and various areas of the social sciences (sociology, social psychology).

7. Human-machine social networks The technology for general artificial intelligence is developing rapidly and supporting an explosion of applications in areas such as avatars (human like, animated computer interfaces for facilitating communication) or hardware components and systems (e.g. body sensors or “smart” houses) which have the capability of acting autonomously to carry out certain tasks. The level of "intelligence" in such systems may soon challenge that of humans, at least in some situations such as advanced question answering systems or computer agents/robots participating in games.

The increasing importance of these technologies will likely cause a number of important social, economic and psychological changes as they become more involved in peoples' lives. A key challenge for ICT enabled social science will be to develop a framework of computer simulation, involving both machine and human participation, to help predict and analyse the most important likely changes and to anticipate their long-term consequences for our society. For example, it is important to assess how individuals' ready acceptance of such technologies -- or refusal to use them -- may influence their ability to develop new skills and remain socially connected to others.

Likewise, the proliferation of artificially intelligent agents may have marked influences on communities by altering the frequency and nature of human interactions.

This grand challenge focuses on the crucial meeting point of nano-, bio-, info-, and cognitive technologies and sciences with the aim of foreseeing the most important human and social changes likely to emerge from tomorrow's technology.

Challenge / Area The challenge for social science is to forecast the aforementioned changes and to provide understanding that will help our society change more smoothly. To meet this challenge, a number of specific methods need to be developed, including: • •

Automated technologies for detecting changes in human behaviour or community structure or function; A platform for simulation that will allow the forecasting of likely changes and the exploration of potential scenarios for countermeasures or external control;A range of actuators, including tools for dissemination of insights, which may help to guide a smooth, technology driven evolution.

Studies within this challenge should focus on any area that is expected to see significant changes due to technological advances in general artificial intelligence, including education, healthcare (in particular, elderly care) and consumer behaviour. Studies and simulations should be area-specific as the likely cumulative impact of advancing technology will depend strongly on the field in question, and especially on the scope of the new technologies introduced. For example, autonomous communication systems may greatly expand the spatial range of education, and thereby help level social inequalities based on geography. Or autonomous helper systems may increase the individual freedom of the elderly, thereby freeing up human caregivers or helping to re-integrate the elderly into society.

Topics Within this general framework, the social sciences should play a central and catalytic role in shaping the specific direction of the research efforts. A wide range of ICT technologies and associated applications should be explored, including the following:

• • • •

cognitive, educational, and social neuroscience; ambient and assisted living; body sensor networks, exoskeletons, smart dust, pervasive computing; privacy and personalization, anonymity and data sharing, cryptography and trust.

Target Outcome Short term target outcomes include: • •

novel experimental methods to study the acceptance and consequences of machine intelligence in different communities, age-groups and cultures; novel analytic theories and tools for simulation and modelling the impact of such technologies in the economy and society.

Expected Impact Efforts to meet this challenge could play an enormous role in determining whether new IT technologies will lead largely to socially beneficial changes in human behaviour and community organization, or if it instead stir up damaging surprises. As a recent National Science Foundation publication suggested, "...there is general agreement among leading researchers that we have insufficient scientific understanding of the actual scope and trajectory of these socio-technical transformations... The future and well-being of the Nation depend on the effective integration of Information Technologies into its various enterprises, and social fabric."

The studies in this challenge could could offer valuable insight for policy makers when crafting new policies regarding the spread of the intelligent technology, and help reduce the uncertainty associated with looming socio-technical transformations.

Suitability for ICT and FET This challenge is clearly of immense potential value to both ICT and FET. Although its goal — to study and predict the impacts of technological advances — may seem far-fetched, recent advances in ICT suggest that it is also possible. Success in this area will greatly amplify the social and economic benefits likely to accrue from future technology.

Work on this challenge will also further a number of specific ICT areas. One of the core problems is to measure the level of general artificial intelligence (GAI) involved in some setting in which humans and machines interact. One route to a possible solution has been recently described in the co called Turing Game project (presented at the conference Science Beyond Fiction (FET, 2009, Prague) which looks to the roles humans and machines play in cooperative-competitive games to measure the level of GAI. An advance in this area will impact the application of adaptive and intelligent ICT technologies across the board.

Communities This challenge would demand the participation of diverse communities active in previous calls that share some of the goals. For example, research would benefit from the expertise of researchers supported by the NSF call or by the EU FP6 New Ties project. Since the very nature of the challenge is multidisciplinary, researchers with background in the social sciences, cognitive sciences, mathematics and IT are in need.

8. Ultra-dimensional ICT-enabled case studies for modern social science The computational modelling of complex social phenomena has advanced enormously in recent years. One persisting problem, however, is that useful models often contain many parameters regarding details that cannot be "pinned down" by empirical evidence. This grand challenge envisions a bold effort to tackle this problem by initiating extremely intensive case studies of a number of important social phenomena which can be studied in detail simultaneously with many complementary methods. The creation of such data sets would greatly aid the development of sound social simulations.

Challenge / Area The development, testing and assessment of social simulation techniques is currently hampered by the lack of adequate, multidimensional data. At the moment we simply can't tell whether a given simulation is reliable due to the lack of independent methods for validation. This challenge is to collect enormously rich data sets for a number of important social phenomena, and to do so in conjunction with the identified data requirements of social simulators. The aim, in other words, is to study many specific instances of such target phenomena possible so as to provide an exhaustive data environment within which social simulations offering potentially important insight can be rigorously tested. The kinds of data that will be involved include: • • • • • • •

periodic repeated cross-sectional surveys aggregate time-series data of many aspects audio and/or video recording of key exchanges rich structured as well as open-ended interviews with subjects before and after key events reflective comments by participants on viewing themselves on video measuring bodily positions using electronic tags selected experiments with some subjects

Topics Examples of important social phenomena for which such intensive data collection could provide instrumental value include: • • • •

the collaboration and development of software (including open-source software) the collective decision-making process of groups of people changes in social structure as triggered by new technology (e.g. dating using applications on an IPhone) the spread of positive and negative reputation information through a group of friends

Target Outcome The specific target outcome of this grand challenge would be to collect and publish several such "ultra-dimensional" data sets. The project would, of course, also document key issues arising in the collection of such data, identifying particular difficulties and opportunities for future work.

Expected Impact

The availability of such rich and multi-dimensional data sets would act as a spur to social simulation techniques allowing them to be truly tested and evaluated for the first time. This would focus the efforts of many computer and social scientists to satisfactorily capture and model these challenge situations. Making the data publicly available would also provide for broad scientific collaboration towards these ends.

A truly bold effort to create such data could transform the near-term prospects for the computational simulation of social phenomena by demonstrating in a compelling way the potential for simulation techniques to yield insights into complex social phenomena and what will be necessary for such techniques to form the basis of a deeper social science.

Suitability for ICT and FET It can be argued that the most important future applications of ICT systems will be in helping us understand and manage our own socio-economic systems. At the moment, only ICT-based simulation systems offer the means for gaining insight into the dense webs of feedback that drive such systems and so often lead to fundamentally surprising and unanticipated outcomes. Progress on this challenge will feed directly into the creation of an entire world of future ICT applications of direct social benefit. This makes this grand challenge very suitable for ICT and FET. The project will also, of course, encourage important advances in the ICT-based means for collecting data in social settings.

Communities The very nature of this is interdisciplinary, involving social scientists of various kinds, multi-agent systems researchers, social network analysis experts, formal social modellers and statisticians, social simulators and various stakeholders.

9. ICT for understanding human mobility in crisis situations The large-scale patterns of human movements in modern societies, especially during times of crisis, reflect the dynamics of an underlying complex social system in which "intelligent particles, " i.e. people, navigate within a common environment their own actions help to shape. Today, ICT is tightly entangled with such movement and strongly influences the patterns through the information it makes available to citizens. The rise of global communication networks greatly increases the potential for events at the micro-level (of individual people) to reach up and cause the emergence of self-organized collective states with attendant dangers for human safety, or with large social, economic or political costs. Yet ICT systems also offer a great opportunity to study this important linking of the individual to the collective, and to predict important dynamics as well as to find means to control them.

Challenge / Area Coping with crises is a key challenge for modern society. Among other issues, it requires a deep understanding of expected patterns of human movement both within large cities and without, as well as internationally. We now have a chance to greatly further such understanding with ICT technology, especially along particular avenues:

• • • •

by collecting large dynamical data bases on individual behavioural patterns; by developing new forecasting procedures; by validating complex models that reveal universal collective behaviours; by developing strategies for crisis governance based on key control parameters.

Topics Projects at the European level could allow us to meet these challenges with a number of concerted efforts: 1. GPS systems, mobile phones and the Internet produce enormous amounts of data on human mobility. These data are presently recorded by private companies and public authorities; their use raises privacy issues, and, as a consequence, the scientific, economic and political relevance of such data is not well understood. The construction of a European Laboratory for Social Complexity could coordinate data collection from such different sources and perform filtering procedures guaranteeing the anonymous use of the data themselves, while also allowing the scientific community to study it. The laboratory could coordinate a symbiotic relation between the organizations, which remain the data owners, and the scientific community. Against data sharing with the Laboratory, the organizations involved could benefit from scientific insights and develop innovative uses of communication technologies. The laboratory could focus its activities on representative European cities from different countries and provide valuable policy relevant information to these nations.

2. The availability of data on individual human movement patterns for an entire city over long times would allow the study of transient and critical states revealing both potential instabilities and corresponding control variables. Following approaches from meteorology, the likely history of developing movement patterns can be forecast using data-driven simulations and techniques for

coping with huge sets of heterogeneous and often unreliable data. These procedures should be interfaced with real-time data collection made possible with wireless communication systems.

3. The models developed should help identify universal statistical laws for collective human movements and suggest potential control parameters for a governance strategy of congestions and other critical situations. The models will also reveal the possibilities of performing in silico experiments to analyse different realistic future scenarios and to study the limits of predictability.

This research could also take advantage of bio-inspired models suggesting new adaptive or selforganizing solutions to managing efficient transport. The laboratory will be equipped with large computational facilities suitable for simulating the movements of people (and traffic, etc.) within a whole city. The simulation results will be at disposal of the scientific community for analysis.

4. The models will allow researchers, acting in conjunction with authorities, to construct "knowledge instruments" for the practical response to crises. Such responses could be based on effective minimal interventions targeting key parameters (suggested by the empirical data and the models), especially if a system is near a sensitive critical transition. This leads to a new research field for theoretical and mathematical physics -- the non-equilibrium thermodynamics for social systems. Another key will be to study the effect of new information introduced in the system through ICT, which increases individuals' knowledge and the level of interaction between them.

This may also suggest innovative means tor controlling or guiding large-scale human movements through the real-time exchange of information between people and authorities.

Target Outcome A key target outcome would be the establishment of a European Laboratory for Social Complexity, which would coordinate data collection on a massive scale from many sources and perform filtering procedures guaranteeing the safe use of the data for science. The laboratory would also pioneer the use of such data, in conjunction with models both analytical and computational, to identify potential control parameters for a governance strategy of large-scale social movements, especially in times of crisis. Effective operation of this laboratory would depend on a "super-simulator" combining massive computational resources with large-scale data. It would demand reliable interconnectedness with a variety of other simulation tools to allow multi-scale micro- and macro- modeling, support the simultaneous integration of multiple data-sources (real-time streams and historical datasets), incorporate boundary conditions measured "on the fly" in real-world systems and improve itself naturally as more data becomes available over time (e.g. determination of weather-dependent road capacities or of spreading rates of diseases). The development of powerful applications may also require verification and validation (through lab and Web experiments, for example, or serious multiplayer games) and visual data exploration tools for users to explore the rich dynamics of systems of interest.

Expected Impact Significant progress on the previous challenges will deepen our understanding of the dynamics of large-scale human movements. A laboratory at the European level coordinating the collection and use of mobility data from different sources will greatly improve our means for understanding the evolution of complex social systems, especially human flows therein. The forecasting procedures together with a real-time data acquisition will offer a realistic description of the mobility state in a urban network, which will be extremely valuable for planning crisis responses. The mobility governance strategies suggested by microscopic models could become a essential instruments to avoid crises or, at least, to reduce their social impact.

In addition, a deep ICT-based understanding of human mobility patterns will also create new

business activities in the mobility management of significant cultural, social or tourist events, or in the urban planning of large scale infrastructures or future transportation systems.

Suitability for ICT and FET The enormous amounts of data from diverse sources now being collected automatically presents an unprecedented resource for social scientists and policy makers. It's potential can only be tapped with ICT, and then, only if we can learn to gather and store such data and process it in new ways to get our useful information. This will be among the most important drivers of policy making in the future, as well as for directions for future ICT research; hence, this challenge is especially appropriate for ICT and FET.

Communities This is clearly a multidisciplinary area. Understanding the complexity of human mobility from microscopic data requires the interaction of scientists in different areas including physics, mathematics, engineering, computer science, cognitive psychology, sociology and urban planning.

10. Supporting revolutionary new modes of ICT-enabled value exchange The transfer of monetary value between parties is today, in the West, based almost entirely on binding laws and contracts. But this is not the only possibility. Informal value transfer and credit networks between people or institutions can provide credit or value transfer services based on social trust. Such networks have not yet received much scientific attention, yet they have a significant impact on people's lives globally. As ICT advances, especially in technologies reducing social distance and supporting economically-feasible micro transactions, it increasingly allows for significant improvements in the reach and quality of these networks and may soon trigger enormous changes in the mechanics of economic exchange.

This grand challenge aims to develop the means for understanding the dynamics behind such informal systems, and to assess how modern technology may help bring them into wider existence in a socially beneficial way.

Challenge / Area An example of informal value transfer is a friend paying the bill at a restaurant, expecting that this cooperative act will be reciprocated in the future. Informal networks of exchanges of this kind, based on social norms of obligation, need not be related to money but emerge in, for example, babysitting circles, or house swaps. Traditional systems of this kind e.g. the â&#x20AC;&#x153;Hawalaâ&#x20AC;? system in the Muslim world, transfer considerable sums of money (estimated at $200 billion in total last year) across the world without needing central records or written contracts.

Similar distributed systems are now arising using the internet. Already we observe peer-to-peer systems implementing simple value transfer and credit based protocols. For example, BitTorrent, the most successful file-sharing protocol on the Internet, uses an algorithm based on the tit-for-tat strategy for promoting cooperation in repeated interactions. More recently, private communities have learned to implement points systems to reward and encourage socially beneficial behaviour.

Micro-credit services have expanded the reach of traditional informal value transfer networks beyond national and regional borders.

This challenge aims to rethink the possibilities for such services in a fundamental way, taking into account the expansion of individual reach driven by ICT advances.

While many aspects of human cooperation involve some exchange of value and are the traditional subject matter of the field of economics, this exchange often involves many social processes and mechanisms other than those usually considered by economists, including: social norms, altruism, reputation, trust, group membership, friendship, kinship, identity, status, etc. These can only be understood (currently) by modelling them at the individual level. It is imperative we build a deeper understanding of such systems as they will likely play an ever more important role thanks to the removal of barriers and to individual empowerment allowed by the growth of communication networks.

Topics Pushing this challenge forward will involve work on a number of topics linking to finance and economic systems, infrastructure, policy and regulation, social networks and exclusion. As for methods and tools, agent-based simulations will clearly be necessary for improved understanding and forecasting. The challenge is to understand, monitor, direct and support informal value transfer

systems of diverse kinds. As with any change to the economic system, there are risks of exploitation, monopolization and collapse, all phenomena that should be studied for prevision and control. Specific challenges may include: • •

Detailed study of the emergence and self-organisation of functioning trust-based networks in informal socio-economic contexts where individual behaviour produces functional social structures.

Analysis through individual models, empirical studies and experiments dynamics, of risk and extreme events within such networks.

Target Outcome We envision several specific target outcomes including: • • •

A thorough empirical documentation of the functions and dysfunctions of novel complexity models of informal value transfer and credit networks, based on studies of real world examples; An understanding of the fundamental dynamics of such networks achieved through simulation and analysis, as well as the development of new models and theory; An assessment of the supporting role in such networks of different social mechanisms such as norms, trust, kinship, social networks, group membership and reputation.

The key research questions are as follows. What combinations of social mechanisms and individual abilities allow the functioning of totally distributed but reliable credit networks? Which of the various mechanisms seem to be more effective in this regard? In what ways are such systems vulnerable and can cease to be sufficiently reliable? What are the key indicators that such systems are on the edge of failing? How does one seek to start/re-start/fix such systems?

Answering these questions would make a major contribution to complexity science both in the understanding of observed social systems and in the invention of new forms of cooperative activity.

Expected Impact The impact of a scientific recognition of this important phenomenon will be very wide. Results from this line of work might greatly extend the reach of informal credit networks, thereby mobilizing resources which until now have been locally constrained. It would also have positive social effects by extending the awareness of people about their own potential for self-determination.

Suitability for ICT and FET Informal value transfer and credit networks must be studied in the context of ICT, as developments in ICT are making it possible to harness social resources including social norms, altruistic instincts, reputation mechanisms, kinship and so on for social benefit.

Communities The communities touched on by this topic include most of social sciences, with economics as a focus; to tackle the problem, we will need competences in social complexity modelling, including evidence based modelling, models of reputation and trust, models of distributed networks, gametheoretic and other analytic approaches.

11. Understanding "irreducible complexity" in global systems Humanity today faces huge challenges, including growing instability in social welfare systems supporting education, healthcare and social security and in the critical infrastructures underlying the financial system, telecommunication networks, power supplies and transport. We face enormous dangers from the increasing depletion of natural resources and progressive erosion of global ecosystems. These problems, along with expected climate change, may drive massive demographic events and human migrations, as well as conflicts of unprecedented magnitude.

All these problems are strongly interrelated. To develop models and procedures for describing and handling them, we need to gather data on a scale far beyond what is presently available, and to develop new ways of extracting information from these data. We have, ultimately, to achieve a fundamental change in our general world view and in the methodology of the social sciences. All these problems are complex to an unprecedented degree and demand a radical re-thinking of our strategies for science and management.

Challenge / Area Western analytical thinking has always been reductionist, and the requirement of parsimony (formulated by Aristotle and later by Occam) has remained a guiding principle. Galileo not only introduced the concept of mathematical description and experiments, but also of disregarding unimportant details, focusing on the "essence" of the phenomenon. Physics realized this reductionist program to the full and its impressive success created the impression that reductionist science, and the discovery of the right core model at the root of all phenomena, is the true way of science. Yet the application of the reductionist approach outside the hard sciences is fundamentally flawed, because complex systems are irreducible. Such systems depend on an extremely large number of variables, and tiny details are often essential in determining the behaviour of the system. The description of such a system in terms of a parsimonious model is often both futile and dangerously misleading.

A key challenge is to find new ways to think about such systems, replacing expectations of predictability and reduction to simple models with more flexible ideas attuned to the setting of complex systems, ideas that will ultimately far more useful in learning to manage them.

Topics A rarely mentioned but fundamental feature of complex systems is their "irreducibility," which means that they depend on a very large number of variables and can be sensitive to tiny details; they are intrinsically high dimensional. A valuable research project would collect as many examples as possible of such behaviour from biology, ecology, brain research, economy, finance, etc. These systems pose fundamental problems for science in that the number of available data are typically insufficient for the calibration and validation of any model having sufficiently high dimension to vindicate its claim to faithfully represent them.

To increase our understanding of such fundamental issues, and to gain a view on what is both possible and not possible, we need to focus in detail on specific questions in several general areas.

Computation â&#x20AC;˘

explore computational simulations as case studies of irreducible systems. This can be done in the context of large complex systems with conflicting interactions such as spin glasses,

•

neural networks, agent-based models of economic systems or models for ecological or traffic systems. using such models, explore in a systematic way the likely consequences of irreducibility, including extreme sensitivity to detail, enormous numbers of relevant explanatory variables, and extreme sensitivity to boundary conditions, control parameters, etc. Such systems may lack any simplifying features that would come to the fore in the limit of large numbers (unlike the general trend in thermodynamics, for example.) Explore the question of whether such phenomena may emerge naturally in systems involving adaptation, learning and selfreflection.

Cognitive science and Psychology •

•

explore the perspective of cognitive science on how the mind has evolved to deal with irreducibility, by relying, for example, on quick heuristics for decision making (rather than detailed calculation).Which part of the brain performs these intuitive, heuristic assessments, and how? explore the typical psychological aspects of irreducibility. Are we frightened by it? If so, does this explain a tendency to impose oversimplified patterns upon real phenomena, seeing predictability even when it does not exist? How does this link to the irrational desire for simple explanations, as we as the allure of religious beliefs and simplifying ideologies?

Management science, policy aspects

•

explore how irreducibility influences decision making, especially in policy making.

Target Outcome At present there exists no viable approach to these problems other than building large-scale computer models and performing experiments on them. In some fields, such as climate modelling, this is being done on an industrial scale. A target outcome for this grand challenge is a deep theoretical perspective, backed by a wealth of examples, showing that a similar approach is urgently needed for the social sciences, including economics and finance.

Expected Impact The impact of this challenge will be a far-reaching change in awareness, for scientists, policymakers and the public, of the fundamentally different challenges presented by complex systems when compared to systems studied in all past science. Armed with this understanding, we may be able to develop an intuition for such phenomena and also learn techniques for aiding such intuition.

Such a change may be absolutely crucial to solving a wide range of social, ecological and technological problems now looming before us, which are all complex to an unprecedented degree and demand a radical re-thinking of our strategies for science and management.

Suitability for ICT and FET This grand challenge is highly suitable for ICT and FET, as the most important future applications of ICT systems will lie in helping us confront many looming problems we now face, all of which stem from the complex dynamics of large-scale systems. Only ICT-based simulation systems currently offer us the means for gaining any kind of fundamental understanding of the new challenges these systems present, and how our thinking must change to handle them more

effectively.

Communities Achieving this grand challenge will demand collaboration between scientists in fields including physics, mathematics, statistics, psychology, computer science, economics, social science and artificial intelligence.

12. Reverse social engineering "Reverse engineering" is the process of discovering the technological principles of a device, object or system through analysis of its structure, function and operation. By analogy, applying this concept within the social sciences means seeking the socio-economic principles of a social system from its structure, function and performance. The idea of this grand challenge is to stimulate the development of a broad scientific framework to generate a reliable mathematically-based understanding of social systems and to gain deep insight into important phenomena.

Among the most important are social norms, which support cooperation, trust and loyalty, and which constitute a major component of what is called ``social capital.'' These help determine, for example, how well private initiatives, businesses and the public sector can flourish and avoid dysfunction associated with overly selfish behaviour.

Challenge / Area The traditional social sciences, including economics, already offer a number of basic principles and perspectives for understanding socio-economic behaviour in many settings. However, these sciences still lack fundamental insight into the origins of social phenomena such as the emergence or persistence of organised groups, social norms and so on, or abrupt changes in social conditions involved, for example, in critical events and economic crises. A deeper understanding of such processes can only come from detailed analysis of the structure and diversity of the human interactions within social systems.

Nowadays, it is increasingly possible through ICT systems to obtain data on all aspects of modern societies, to detect subtle statistical patterns and, in an automated way, disentangle laws or principles, akin to those governing physics, for social systems undergoing critical situations. There is a fundamental gap in the understanding of the causal role of norms in societal organization, which can be filled up by integrating individualized approaches (e.g. moral psychology, experimental ethics) with ``normative pattern recognition'' based on large-scale ICT systems and modelling. This would require the collaboration of scientists who rarely interact, in particular experts in modelling social systems (e.g. with normative multi-agent models), ethics, moral or social psychology and law. In pursuing this kind of research, modern social science has a great opportunity to provide flexible, robust and adaptable methodologies for understanding and monitoring socio-economic systems. Of particular interest would be the identification of tipping points -- situations in which discontinuous change can come very quickly -- based on the integration of mathematics and computation with massive data collection and analysis.

Topics Key topics to be addressed include: â&#x20AC;˘ â&#x20AC;˘

â&#x20AC;˘

understanding how both individual and group behaviour can be modelled in a way that captures the knowledge and methods of the social sciences and also extends these by using the new mathematical and computational methods of complexity science. understanding how multilevel databases can be built based on synthetic micro-populations and how streams of data can be collected and used to instantiate and update these databases.

Also, learning how such data intensive resources might be combined with simulations for use in policy planning, implementation and management. understanding more clearly what it means to 'predict' the behaviour of a complex social technical system in a way that is useful for policy making.

â&#x20AC;˘

on a very practical level, understanding how ICT data and analysis can help identify important shifts in social norms and beliefs as they occur. As the properties of ever more social processes become reflected in ICT data (e.g. reputation systems for individuals, products and institutions, information systems supporting elections, ICT-supported decisionmaking), these data can be used to study moral issues with what might be called "moral sensors." These would include, for example, web-based tools allowing individuals to evaluate their individual moral profiles, mobile labs allowing for in situ evaluations of peoples' views on moral issues, or reputation systems to assess the moral qualification of individuals or entire companies to perform sensitive tasks.

Target Outcome The main target of this challenge is to produce outcomes of use to policy makers. We expect that these kind of methods and tools will be of primary interest to those agencies devoted to forecasting socio-economic changes of all kinds, especially crises. While some find the term "social engineering" alarming, linking it to oppressive collectivist movements of the 20th century, this challenge recognises that all nations today engage in social engineering of one form or another through policy design, and that policies over the past few decades been based overwhelmingly on economic principles that largely neglect the influence of social norms and other important collective social processes. Bringing the best scientific tools into play in trying to understand social processes can only help in the design of more effective policies.

Expected Impact The outputs of the present project are expected to have a broad impact on the entire society. In the context of an emerging, highly quantitative social science, it will help to establish guidelines, design rules and efficient algorithms to help both individuals and policy makers navigate surprising emergent phenomena in complex social systems which have hitherto fallen outside the understanding of social science. The dedicated development of such models would have wide impact on many areas of science, including sociology, anthropology, and political sciences. In practice, it would stimulate the development of new software technologies, and new scientifically grounded methodologies to anticipate social movements.

In an immediate practical sense, desirable outcomes would also include the creation of data on moral behaviour and judgement that could be used to calibrate and test agent-based simulations, the establishment of ICT-based ``sensors'' for moral shifts and responsibility gaps in organizations and societies or tools to enhance the moral self-reflection of individuals and organizations.

Suitability for ICT and FET The challenge is suitable for ICT and FET as its success depends intimately on ICT, and also as it promises to stimulate important advances in ICT itself. In particular, quantitative social science will demand advanced data acquisition and data mining using logs of communication networks. The expected outcomes will also clearly establish ITC tools at the forefront of technologies required for effective policy making in the socio-economic sphere.

Communities This grand challenge involves a range of communities including statistical physics (large scale simulation, scaling theory and complex networks), applied mathematics (stochastic processes, statistical inference and differential equations), computer science (non-linear optimization and

clustering techniques), sociology (data acquisition and behavioural economics) and economics.

13. Working out a "Plan B" to Save our Society A fundamental challenge for social system sciences is to provide scientific bases for a "Plan B" -an alternative plan for a bottom-up organization of social and economic activities of groups and societies which can be implemented in case our current ways of organization fail. Internet and mobile communication technologies provide for revolutionary new means by which large groups of individuals can coordinate in the achievement of common goals. The essence of plan â&#x20AC;&#x153;Bâ&#x20AC;? is use science to capitalize the potential of new technologies to increase the safety and well-being of societies by enhancing their capacity for constructive self-organization.

Challenge/Area We live in a time of warning signs indicating that our current way of living may not be sustainable.

Our use of resources at current rates cannot continue unless both technology and human behaviour change radically. Global warming is likely to result in large-scale social unrest triggered by enormous migrations of people seeking water and habitable conditions. Terrorism and the growth of local conflicts are likely to produce local instabilities and threats to global security. If the current way of organizing society fails in a given domain (i.e. disintegrates or becomes inefficient), we do not have an alternative plan. As history shows, when control fails, loss of services quickly leads to chaos, conflicts and violence, and often the emergence of alternative criminal power structures.

A major challenge for social and system sciences is to develop an alternative plan for how to organize social and economic processes so as to converge on constructive action without top-down planning or control. This requires a deep understanding of the dynamics of economic, social and psychological processes, including the conditions under which unsupervised social groups will cooperate, rather than engaging in conflict, and how large groups of individuals can coordinate without the hierarchical administration to produce useful products and services. Understanding bottom up coordination alone, however, is not sufficient, as almost invariably the highest quality can be achieved by some combination of top down and bottom up processes.

The purpose of this approach is not to replace those involved in top down control (policy maker and government officials and so on), but to identify the best way to improve their capabilities by harnessing self-organizing processes in decentralized systems. Understanding how best to combine the top down and the bottom up process for recovery and sustained growth represents the main challenge for social economic and complexity sciences.

Topics Laying out a scientific basis for the effective combination of top-down and bottom up processes requires significant advancement of our understanding of how social systems function, advancement of technology (e.g. large, distributed, intelligent networks of multi-modal sensors, new generation of databases) and also a better understanding of how social systems and emerging technology work together in self-organization of constructive social processes. We need not only to understand how in general social systems can function optimally based on bottom up coordination, but also how these processes interact with top-down control. This knowledge needs to be used to construct new models in almost every area of social science.

We need to extend our inquiry to detailed models of effective functioning based on selforganization, in a long list of areas including the financial, market exchange and tax systems, the information system underlying public medias, the innovation system supporting science and technology, the education, healthcare and social support systems, government and legal systems and the creative system producing art and entertainment. In all of these areas, new and emerging

communication technologies create revolutionary new possibilities for self-organization and bottom-up coordination of social groups and societies. This represents a potential never before available to humanity.

But it is also true that effective solution of most problems must involve both technological and social aspects. To reduce energy consumption, for example, will require both more efficient energy devices as well as changes in human behaviour, and these aspects are interdependent. Smart energy sensors can lead to energy savings only of humans use the information they provide. In total, the design of effective plans requires a holistic understanding of how technology, individual behaviour and social groups interact in a given domain. To design effective policy and intervention strategies one needs a reliable working model of this system. Developing computer simulations of the interplay of technological, human and social factors presents a challenge for modern science.

Target outcome This project should develop models, theories and general understanding of how ICT-enabled and ICT-transformed social systems work, as well as understanding the dynamics of economic, social and psychological processes. This understanding will lead to scientifically informed principles and a plan for using new technologies in the service of creating emergent social processes of high quality.

Expected impact The challenge will have strong impact on computer science especially in creating and supporting techno-social networks and natural computer interfaces. If successful, this project will significantly increase security and the well being of our societies by employing the achievements of modern science and technology in the service of the most pressing needs of humanity.

Suitability for ICT and FET Rapid development of ICT offers capacities never before available to humanity. The essence of plan â&#x20AC;&#x153;Bâ&#x20AC;? is to capitalize on this new potential to increase the safety and well-being of societies by enhancing their capacity for constructive self-organization. Perhaps the most transforming aspect of modern ICT is its capacity to provide new ways of organizing social and economic processes. Selforganization of social and economic processes made possible by new ICT tools can rival the most effective ways of traditional organization. Establishing conditions under which new technologies can lead to emergence of constructive social processes of high quality, and understanding the dynamics of these processes is a major challenge for the exact, social and economic sciences. IT, formal and social sciences must work together to harness the power of ICT for the security and sustained growth of humanity.

Communities This is a highly interdisciplinary research initiative addressing many communities and calling for a new integration of many scientific fields. This initiative calls for the unprecedented integration of the exact and social sciences, especially computer science, physics and economics. The project may also go beyond pure science and involve art and visual communication (e.g. understanding interfaces for effective group collaboration or communication of scientific discoveries to general public), as well as the stakeholders of the processes of interest including national and regional governments, administration, industry, businesses, financial institutions, NGOs, educational institutions, health services, media, and many others.

14. Methods for navigating complex societal problems Our societies are ever more frequently afflicted with problems that exceed the boundaries of any one scientific field. Examples include issues facing the public health and agricultural industries (BSE; Foot- and Mouth disease; Fowl Plague), the transportation sector (pollution, traffic congestion), or healthcare (HIV/Aids, SARS). To face such problems, pioneers in the social sciences are now pleading for a better scientific methodology based on the concept of complexity, which has proven extremely valuable already in physics, biology and ecology. This new methodology rests largely on insight from evolutionary biology on system adaptability, from statistical physics on universal behaviours in large, multi-component systems, and from computational modelling, which is one of the most powerful tools for exploring complex system behaviour.

But these new tools and theories are not enough. Science is still fragmented: different disciplines use different languages, interdisciplinary groups are scattered over different domains, and scientists are organized according to conflicting paradigms. Complex societal problems are most of the time seldom completely static, but change during their development and involve many actors each with different views of the problem, with different interests and with different â&#x20AC;&#x2DC;solutionsâ&#x20AC;&#x2122; in mind. This challenge seeks to build fundamentally on the recent development of a methodology for working with complex societal problems which combines knowledge, methodology and technology from different sciences.

Challenge / Area The field of Methodology of Handling Societal Complexity has developed methods and tools for better understanding, integrating and handling these kinds of problems in a highly practical way, bringing all expertise to bear, and avoiding natural distrust between differing parties which can often make decision making very difficult. The research challenge is to build on this recent development by finding better ways to combine human brains and advanced technology to support the solution-finding process for complex societal problems.

Topics The Compram methodology (recommended by the Organization for Economic Co-operation in 2006) is special set of techniques and methods developed to bring differing parties and experts together toward a consensus and legitimate solution strategy to complex social problems. It starts by analysing the main issues, and similar examples from the past, with a multi-disciplinary team of experts guided by a facilitator. In analysing a financial crisis, for example, these experts would include people from economics, systems theory, psychology and sociology, and also from societal domains such as banking, finance and government. Guided by the facilitator these experts explore the problem in brainstorming sessions, analyse documents, collect and interpret facts, validate or reject viewpoints, and so on. Then, supervised by the facilitator and experts on simulation, the participants together build a conceptual simulation model to capture how key phenomena influence one another in a web of complex feedbacks.

After such development, the group then invites a wider group of relevant stakeholders and responsible actors to review the model and improve it. This simulation is then embedded in a roleplaying game in which human players make decisions in the context of information provided by the ongoing simulation about how the system in question is evolving. In this way, they come to appreciate key chains of causes and effect, as well as the difficulty of finding simple linear relationships. This gaming-simulation design is then tested and improved by playing it a number of times with teams composed of different players. The final result is a powerful tool instrument to

analysing, handling and finding potential solutions for complex social problems.

The Compram methodology is specialized to combine knowledge from different fields, stimulating thinking beyond the usual boundaries and handling emotions in the problem handling process. It aims to acknowledge and balance power differences among the different interest groups, while guiding the problem analysis process to give practical direction to policy makers. This kind of approach requires an ambitious and multidisciplinary research focus to develop its full potential as a practical tool.

Target Outcome The specific outcome of this research will demonstrate a better way to analyse and find sustainable to solutions to complex societal problems. Handling societal problems in a multi actor way gives a better chance for real-world implementation of proposed solutions.

Expected Impact The expected impact of the research is a demonstration of the value of this approach so it will be more attractive to both researchers and policy makers. This will provide the basis for more sustainable interventions to be found for real world problems.

Suitability for ICT and FET This challenge is highly suitable for ICT and FET because the ongoing development of ICT-enabled methods both for the exploration of complex system dynamics, through simulations, and for enabling more effective multidisciplinary interaction will be crucial to finding solutions to many of our societies' most complex problems.

Communities There are a number of communities involved in this challenge, including the International Society on Methodology for Handling Complex Societal Problems, the Euro Operational Research Group on Handling Complex Societal Problems from the European Operational Research Society and the Dutch Federation of Methodology in the Social Sciences. Moreover, by organizing sessions on the topic in different conferences during decades, also members of the Research Committee Sociocybernetics and the Research Committee on Logic and Methodology in Sociology of the International Association of Sociology (ISA) are also involved. Key disciplines include the social sciences, mathematics, physics, operational research and computer sciences.

15. Capturing and Freeing the Academic Meta-Literature With the advent of cheap computing power and the internet the distribution costs for academic papers has become insignificant. However, the search cost -- the difficulty in finding the papers one should read -- has grown. The present, journal-centred, system is not coping well with the explosion of the academic literature and the increasingly varied reading needs of researchers.

Challenge/Area This grand challenge is to create a distributed, scalable and maintainable system that enables each user to more easily find the academic papers they need to further their research. This must utilise the maximum available information about the papers, including: their content, their core meta-data, the citation structure, reviews about papers, discussions about topics related to papers, researchers' reading habits and collections of other entities (simulation models, presentations, data sets, newspaper articles, websites, people etc.). Whilst there has been some progress addressing each of these individually, e.g. setting up a standard for capturing meta-data, or using the citation structure for recommending papers, these are fragmentary and often incompatible with each other. The grand challenge is to achieve such compatibility in a way that can "add on" to existing systems without requiring people to re-organise existing systems (e.g. online journals).

At the moment there is a lot of potentially useful meta-data that is wasted. For example all the detail of judgements made by reviewers in journals and conferences, or the reading patterns of users of journals. If ways to capture or make available this data (dealing with privacy or commercial concerns) this would have a positive impact in itself.

Topics There are a number of systems, tools, techniques and approaches that could contribute to completing the above challenge. These could be sub-projects, but subject to the need that every tool and approach must be maximally compatible with other components, and requiring the minimum of new standards. Approaches that make new information available to future tools are preferable to those which require a particular tool. Sub-projects of the grand challenge include: •

•

•

•

Meta-data capture: finding novel, distributed and effective ways of capturing meta-data from users with the minimum of effort on their behalf (preferably as part of actions from which they derive personal benefit). Explicit meta-data, e.g. an informative review of a publication is more useful than implicit meta-data (such as citation statistics).

Meta-data storage and provision: finding ways to make available both free-to-public and commercial meta-data in a distributed manner, so that the use of many different kinds of meta-data can be mixed when used, but whose provenance and status can be easily established.

Meta-data analysis: finding algorithms to exploit meta-data to aid a potential user in their search for information, and in a manner that remains under the control of the user so he or she can combine different techniques as they wish. This aspect could be left to the market to provide except that this would not result in a coherent system, but incompatible and nonopen systems.

Meta-data motivation: find ways to motivate the production of meta-data. This is highly fundamental, as many systems fail because people simply cannot be bothered to spend the extra time entering data. Although monetary motivation is one possibility, many systems work with other kinds of reward. In Wikipedia and similar systems there seems to be that individuals feel "ownership" over a topic and hence care for what they own. Other

mechanisms include group/elite membership, reputation mechanisms, reciprocity and punishment.

Target Outcome The target outcome would be a collection of techniques, tools and resources that mesh together to provide the maximum effective access for researchers to the information and papers they need to read. Such a system must:

• • • •

be complementary to and work with the present system but also work well with public paper archives, and other emergent technologies enable each user to find those papers which they need to read (in the widest sense, including finding papers they did not think they needed to read)make the maximum possible use of available meta-information about published academic knowledge to enable the easiest possible capture of quality meta-information about published academic knowledge have the effect of increasing the useful meta-data that is available.

Expected Impact Such a system would have a radical impact upon how science. Broadly consistent systems that facilitate the creation, provision and use of meta-data would have the effect of removing the barriers concerning the creation of a "market" or "ecology" of meta-data and thus start a process that could develop increasing layers of sophistication - serving a variety of different user "niches".

Suitability for ICT and FET This is firmly within the domain of ICT and FET communities. However what works in practice when real users interact with the systems is what matters. It does not matter how well designed a system is or how sophisticated a data-standard is if people don't use them. Rather than an analysis and specification approach, a more pragmatic and experimental approach is required that will test and evaluate systems with users and also collect data and understand how people are actually using meta-data. This would involve the integration of the social and psychological sciences (for example those who study the social processes of science) with computer science.

Communities There are a number of academic associations and fields that could contribute to such a challenge, including computer science, psychology, social science, philosophy of science, economic and political science. However there are also those that provide some of the existing systems, including: commercial publishers, Google books and annotations, pre-print archives, institutional web sites, academic citation management tools, social and professional networking sites, tagging and recommendation sites.

A political decision is whether and in what way to involve those who might have a vested interest in preventing such a challenge. It may be that publishers wish to protect the status and role of academic journals, and frustrate any more distributed and alternative method of paper judgement

and subsequent reputation gain.

16. Enabling the emergence of ethical ICT ICT products often lead to unexpected behaviours, or side effects, from their users. There is a need to develop a methodology combining social simulation and field-experimentation in order to understand such effects before or as they emerge and find ways to counter them.

Challenge/Area Quite often the introduction of new ICT systems leads people to unexpected uses (beneficial or not) which are ultimately observed only after the fact. These uses can cause a great deal of social harm, as well as psychological damage (phenomena such as 'web addiction,' for example), never intended by the original designers. The further development and social acceptance of ICT as a whole may depend on developing a better ability to foresee such unintended consequences before they happen, and finding efficient ways to avoid them or provide counter actions.

This grand challenge is to use the concept of 'living labs' -- laboratories populated by real people behaving as they might in the real world -- coupled together with social simulation and novel ICT solutions in order to avoid misuse of a system.

Topics A number of specific topics must be addressed in pursuing this challenge. These include: • •

•

finding ways to elaborate mathematical models that can employ user data to detect the emergence of important side-effects in use behaviour; finding ways to design an effective set of evolving experiments that will enable the evaluation of existing ICT systems for their liability to causing unintended behaviours;developing a viable and robust methodology that will enable an efficient coupling between living labs, social simulation models and ICT development into an integrated scheme for both testing ICT systems and understanding the unexpected human interactions with technology more generally; developing a realistic and useful roadmap outlining future directions for an evolving ethics for ICT.

Target Outcome The challenge envisions several specific target outcomes: • • •

Elaborating a methodology for the development of ethical ICT Developing social simulation models of the impact of normative socio-technical solutions on both individuals and larger groups Developing a methodology for the design and implementation of adaptive experiments concerning the use of ICT

Expected Impact The main objective of this challenge is to ensure that developed ICTs won't be damaging to either individual human users, to groups, or to society at large. It will impact technology by showing the way to developing methodologies that include the intended user (or other similarly behaving people) from the outset.

Suitability for ICT and FET This is a vision-driven topic that is highly relevant for ICT and FET. A field is at once close to mainstream ICT as it deals with issues of security, but employs a very novel experimental approach that respects the nuances of human psychology and the necessity of involving people in the development and testing of new ICTs. It's impact could be very high for ICT by providing a much more powerful means for engineering beneficial ICT behaviour in actual use and avoiding damaging and counter-intuitive problems.

Communities This is a multidisciplinary research area involving sociology, philosophy, law, computer science, experimental psychology among others.

17. Creating an Innovation Accelerator The Internet is transforming the possibilities for collaboration between people around the globe, with potentially profound implications for science. The power of massive web-based collaboration to solve complex problems has already been demonstrated -- for example, in mathematics. We envision an Innovation Accelerator (IA) as a tool to support such large-scale creative collaborations -- a distributed, Internet-based platform offering ubiquitous access, intuitive user interfaces and advanced Web 2.0 features.

This tool could be used by scientists in Europe and globally, and also tailored by specific communities for their own needs. It will also help business people and politicians find the best experts for a project, and to support the flexible coordination of complex, large-scale projects. The benefits for both science and business will be the ability to discover innovations sooner and to invest more effectively in emerging trends and technologies.

Challenge/Area We envision the Innovation Accelerator to be free or very affordable for academic institutions and businesses from across Europe. Its software will be open-source to ensure that it works reliably and can be widely shared. To be successful, the Innovation Accelerator will require a host of component technologies to support the efficient coordination of individuals or groups. The challenge is to use modern technology to greatly accelerate collaboration and innovation among diverse scientists as well as people in business and policy makers.

Topics Making this work will require a wide range of important advances in basic IT and in developing high-level and intelligent IT applications. These would include the following: A resource manager able to automate the optimization of resources such as money, space, staff, etc.

Among other tasks, it would match job openings and the best experts on a European scale through massive data mining and social networking.

A social networking module providing for the creation of project websites and discussion groups.

A many-to-many communication system managing complex messaging. For example, users will be able to activate specific mailing groups with a few clicks, updating email rules, and so on.

A virtual conference module for the organisation of webinars or Second-Life-like environments for virtual group meetings. It will automate mechanisms for moderating interactions during meetings and for organising electronic documents, images, videos or maps and making such resources immediately accessible to all.

A incentive-based crowd sourcing system would help address the most important scientific challenges. These would be elaborated at ``Hilbert workshops,â&#x20AC;&#x2122;â&#x20AC;&#x2122; at which scientists identify open problems. These would be published online, with prizes (monetary, or perhaps even academic positions) for the best solutions to stimulate goal-driven, multi-disciplinary research.

A public dashboard allowing people to advertise their current area of study. This would serve to stimulate collaborations and to reduce multiplicity in attacking scientific challenges.

A decentralized co-creation manager allowing researchers to take part easily in large-scale projects.

Commonly produced documents would be stored within a versioning system, which would track and highlight all changes and resolve conflicts between different branches.

An annotation system organising important notes for the future, and allowing the easy import of graphics, statistics, web links, videos, scientific references and other relevant information.

An information discovery system with a rich user interface allowing the simultaneous query of multiple databases and archives.

A knowledge manager linking together and updating all pieces of known relevant information. All references and citations, figures and underlying empirical data of a scientific paper would be immediately accessible.

A powerful reputation system with mechanisms to store, exchange, modify, convert and share reputation points within decentralized communities. Individuals would accrue reputations from the evaluation of citations and a rating system, with raters being rated as well. Reputation would be measured on multiple scales, distinguishing people with many good ideas from disciplinary specialists or those who can write good reviews or fruitfully criticize othersâ&#x20AC;&#x2122; work.

An integrated micro-credit system supporting schemes to reward scientists for their personal contributions. Credits could be earned by certain activities (e.g. rating, reviewing, commenting, etc.), and they would be lost for lack of participation, spamming, etc.

A virtual education module supporting interactive scientific presentations from home without set-up or need for travel. Presentations would be recorded and could be played at any time, allowing one to download related materials, make notes or comments, or ask questions.

Target Outcome The target outcome is to establish and make widely available a powerful IT resource that will greatly accelerate collaboration between scientists from diverse areas, as well as business people, policy makers and others. It will provide the infrastructure on which today's increasingly collaborative research can reach its full future potential.

Expected Impact The successful creation and distribution of an Innovation Accelerator would have a significant impact across all scientific areas by accelerating and making more effective a range of fundamental activities. It would improve the analysis of scientific productivity, help researchers identify new innovations and trends early on, provide co-creation tools for large-scale projects and recommender and reputation platforms to help self-organise research networking. Most importantly, it would establish new institutional designs to stimulate and spread innovations.

Suitability for ICT and FET This is a vision-driven topic that is highly relevant for ICT and FET. Success would place ICT infrastructure at the centre of science and business innovation and social organization, and help spur ICT development on high level applications designed to aid collaboration in science and elsewhere.

Communities

Computer science, social science, mathematics, psychology, reputation systems.

18. The Self-Organising Web The Internet appears to have unlimited potential to support new business, science and other human activities of all sorts. Yet its growth has also brought urgent issues into focus, especially the loss of individual privacy and the inability of users to really control the data they create and use. Photos shared with a few friends end up being made public; financial data in an email may remain indefinitely on computers that are out of an individual's control. There is an urgent need to develop technologies to let people regain control over data concerning them.

The concept of a self-organizing Internet is aimed at overcoming the above mentioned and other problems. It centres in the idea of putting data in a format that leads naturally to its protection.

Challenge/Area The new ``Helbietti'' file format encrypts electronically signed contents and has a number of unencrypted specifiers identifying the file, the kind of content (factual information, advertisement, opinion, etc.), lifetime, and so on. Encrypted specifiers visible only to authorized users show the originator of the data, the owner, date and time of generation, locations of authorized copies and the persons or groups authorized to read, modify or execute the file. Other data would be accessible only to the owner of the file, such as identifiers of the file(s) it has been derived from and digital rights management settings (e.g. maximum number of copies that can be made from the original file). Depending on the sensitivity of the data (public, restricted, confidential, secret, etc.), such information would be fragmented and distributed over several files stored in different locations and password-protected, potentially requiring several passwords from independent authorized persons to access them.

These ideas set the foundation for greater security and control over data, but will require a great many other issues to be resolved to reach practical and widespread use.

Topics Letting data expire after a finite lifetime This concept would provide control over "lost files" or those persisting on the Internet. The idea is to allow files to be decrypted only within a specified time period. Additionally, the file could be opened in this time window only by individuals or groups listed as authorized. Further restrictions on file access could be achieved by requiring that either the original file or one of the authorized copies is still accessible somewhere in the Internet. If the owner of the file would delete the original file and any authorized copies, no copies of the file may be opened any longer.

Ratings and reputation for the quality of ``the commons'' Many common goods such as reliable information systems are difficult to create and easy to exploit and/or destroy, which discourages large collaborative efforts. Therefore, an important additional element in the self-organising Web would be reputation. People should be able to rate, tag and comment on any data they have accessed. The rating mechanism must prevent manipulation of the ratings. Content that users upload to the Internet would also be rated by other users who have access to them, earning the provider of the content a certain reputation. This would offer a tool to separate high-quality from low-quality content. In order to avoid opinion dictatorship by the majority and ensure socio-diversity, it will be necessary to allow for community-specific and multi-criteria ratings.

Sanctioning mechanisms

A reputation should be hard to earn, but easy to lose. To ensure this, the self-organizing Internet could include sanctioning mechanisms to facilitate high quality. The manipulation of ratings or reputation values by "sybil" attacks (self-ratings via multiple pseudonyms) should also be sanctioned, as should false declarations (e.g. labelling advertisements or opinions as information).

People should have freedom to express their opinions, but they also need to have a chance to distinguish opinions from facts.

Microcredits and micropayments The future Internet should also have the possibility to collect microcredits for small contributions to the public good. Such microcredits would allow one to reward people, for example, for contributions to public encylopedias or also for rating contributions. Within such a microcredit network, it might be possible to distinguish different kinds of currencies for different kinds of contributions. It would also be possible to give money a history and, therefore, distinguish ``dirty money'' (such as ``blood diamonds'') from ethical investments.

Intellectual property rights The issue of copyright protection fits nicely into the above concept as well. A music or video file, for example, would be encoded and require a certain password to open it; hence, access to the file could be restricted to a single user or group of users.

Privacy-protecting social networks It may be possible to protect individual privacy by letting people see only part of a social network.

Individuals and communities could determine what can be seen to outsiders of the community and to whom. Certain kinds of information would not be visible to outsiders. In essence, surfing in social networks would be like travelling between communities, and this would feel like visiting other countries. While certain things would be visible, other private aspects would remain hidden to strangers.

Target Outcome The outcome of important advances along these and other lines would be an Internet giving individuals much more control over the information they create and share with one another.

Expected Impact Establishing such standards and principles within the Internet could have an enormous impact by solving some of the security issues currently hindering areas such as social networking, and create multiple avenues through which communities could organise themselves safely and ensure their own privacy.

Suitability for ICT and FET This challenge is highly suitable for ICT and FET as it addresses fundamental issues that currently threaten the scope for the further growth and evolution of the Internet and the rich communities and businesses it supports.

Communities Computer science, psychology, security, social science.

19. Developing Crisis Observatories Many important changes in human systems as well as in most natural systems take place in rare crises or catastrophes. We envision a range of Crisis Observatories as advanced laboratories devoted to the gathering and processing of enormous volumes of data on both natural systems such as the Earth and its ecosystem, as well as on human technological and socio-economic systems, and to provide early warnings of impending events affecting financial and economic stability, social conflict, cyber risks, critical infrastructures and so on.

Challenge/Area Humanity faces enormous challenges ranging from financial and economic instability to environmental destruction and climate change, all linked directly to our inability to manageâ&#x20AC;&#x201D;and often even to understand the nature ofâ&#x20AC;&#x201D;our collective activities and their consequences. The key task is to bring modern ICT to bear through the data it can gather and process to build practical observatories focussed on foreseeing rapid, dynamic changes in human or natural systems, and helping authorities to cope with them.

Topics Financial and economic Crisis Observatory As the economic crisis has clearly revealed, we need a better picture of the stability of the financial system. For example, banks merely having ``healthy'' balance sheets in no way implies overall system stability. It is necessary to have better models not only for each single component of the economy (such as the financial market, the housing market, or investment and consumption behaviour on the microeconomic level), but to integrate all of these together. A financial and economic crisis observatory would identify early warning signs of financial trouble through massive real-time data mining in combination with large-scale computational economic models.

Crisis Observatory for conflicts Europe has recently faced conflicts in former Yugoslavia and in Afghanistan and Iraq. Several countries in Europe are troubled by independence movements, while some face social unrest following the economic crisis. These issues point to the importance of building up a crisis observatory to map and predict conflicts in time and space. It should also evaluate factors provoking conflict, such as social, economic or political exclusion or the scarcity of resources.

Crisis Observatory for crime and corruption A crisis observatory for crime and corruption would try to identify hot spots of crime and corruption by using, for example, methods from network theory. It would also help track and fight terrorism, drug dealing and fraud. Moreover, while collective social behaviour can be powerful and positive, e.g. in creating public goods and shared values, it can also assume pathological features such as riots, extremism or terrorism. It may therefore make sense to track extremist opinions within public Internet forums, where attempts to mobilize support for illegal activities are made. This tracking will not identify individuals, but find hot spots linked to potentially violent activity.

Social Crisis Observatory The Social Crisis Observatory will focus on identifying factors that may eventually create dissatisfaction and conflict, such as social, economic or political exclusion of people of a certain gender, age, health, education, income, religion, culture, language, or preference. This information will allow one to determine the need for political action before social tension builds up to such a degree that it finally causes violent eruptions. It could also be useful to measure factors sometimes

summarized under the phrase ``social capital',' including cooperation, trust, loyalty and compliance.

Crisis Observatory for health risks and disease spreading It is not only diseases such as the flu, SARS or HIV that spread by social interactions, also obesity, smoking, or the tendency to commit suicide can be transmitted socially. It is important to map and understand the risk factors for such transmission, and also to develop real-time monitoring and prediction of the spreading of emergent diseases or other influences. Recent network-based measurement methods indicate the possibility of two-week forecasts, which would be a major breakthrough allowing more efficient vaccination strategies.

Transport and logistics Observatory The majority of humanity now lives in urban settings, where traffic congestion and property price bubbles reflect endemic coordination problems. Congestion problems generate losses of productive time, waste energy and pollute the environment. The Transport and Logistics Observatory will aim to support the smoother and more environmentally-friendly operation of traffic flows and supply systems of many kinds. It should be able to provide powerful guidance for the short-term planning of large-scale evacuation scenarios, as well as the interconnections between traffic and land use, which strongly influence real estate prices and industrial and urban development.

Crisis Observatory for environmental changes Environmental changes are increasingly important. Often imperceptible changes in soil, water, ecosystems, forests and biodiversity have large consequences on food and water availability, flood and storm disasters, forest fires etc., which may affect huge numbers of people. These circumstances require a much deeper understanding of the linkages between environmental change and social dynamics, as well as of the risks and conflicts that could affect societal and political stability. Gaining such an understanding would be the goal of this crisis observatory.

Target Outcome The development of laboratories running massive data mining and computing systems to detect possible crises, such as bubbles or crashes in financial or housing markets, gain advance warning of critical shortages in, say, oil, water, or food, develop ways to identify potential wars and social unrest, emerging epidemics, environmental instabilities and so on. Success will require the development of massive computing systems able to combine real-time streams of information with historical datasets, and allow models to evolve as more data becomes available. It will also require a wide range of visual data exploration tools for users to explore the rich dynamics and possible future scenarios of systems of interest.

Expected Impact These observatories would be invaluable to the policy makers of European governments, as well as to private businesses. Today many policy decisions provoked by looming crises come very late and work with an inadequate understanding of very complex problems. While our understanding of crises will never be perfect, it can be made much better if the right information is focused within centres where scientific expertise can be brought to bear in an immediate practical way.

Suitability for ICT and FET Crisis Observatories of the kind envisioned cannot be created without the intensive use of ICT technology. What is required is the close integration of data gathering and analysis, computational simulation, and visualisation of complex system dynamics. This will require significant further advances at the forefront of ICT and makes this challenge very well suited to ICT/FET.

Communities Physics, economics, social science, complexity science, mathematics, dynamical systems theory, ecology, epidemiology and public health.

20. A Multi-National Adaptor With increasing human mobility, it becomes ever more important to support the understanding and peaceful interaction between peoples from different cultures and having different languages, values and social norms. Simple misunderstandings at the political or economic levels still create or exacerbate many national and international conflicts. Therefore, the final challenge tackled by this Flagship aims to develop a novel ICT device to facilitate the mutual understanding and easy, beneficial interaction of individuals with different ethnic, religious and cultural backgrounds.

Challenge/Area In a multi-cultural world, people should be able to communicate with each other without obstacles.

This is rarely the case today as barriers of language, culture, nationality, ethnicity or social norms divide individuals and make communication and cooperation difficult. Global socio-economic development, and the solution of global problems, will requires tools and techniques to ease the negotiation and conclusion of international contracts and effective communication across different cultures.

The challenge is to create an ICT device drawing on the latest technology that would automatically translate languages and dialects into other languages in real-time. It should also guide users to potential meanings and interpretations, alert them to possible misunderstandings, and instruct them on tacit cultural assumptions underlying the statements and behaviours of interaction partners. In this way, unwritten rules of different cultures and value systems, expressed both in language and in non-verbal means of communication, would be made more transparent, which is an important precondition of mutual understanding and successful interaction.

Topics Realising this device will require solving a number of very challenging technical problems, and packaging device capabilities in such a way that it will be extremely easy for individuals to use without much concious effort. They should be able to do so even as they carry out other ordinary tasks (walking, driving and so on.)

Specific topics to be covered include: • • • • •

Near-perfect real time translation of both written and spoken language Automated reading and interpretation of non-verbal communications as expressed in gestures and body language Creation and access of large databases capturing social norms and other cultural regularities Understanding psychological norms across human cultures that underlie instinctual reactions to cultural differences, and learning how to manage these Developing technology to network multiple devices together to handle rapid interactions between many people or use in meetings and conferences.

Target Outcome Success in this challenge would greatly facilitate more adequate interactions between people of different cultures and increase the likelihood of positive emotional, social, and economic exchanges between people. Such a system would be of enormous value for international negotiations in business, science and politics.

Expected Impact If effective and easy to use, the availability of such devices on a large scale would have an enormous impact on international business. It would strongly aid interactions between governments and also between groups of differing culture and ethnicity within nation states and even on local levels. Additionally, this profound advance in technology would likely spawn entire new industries in related technologies supporting human interactions.

Suitability for ICT and FET While current ICT can handle many tasks that require fast processing of data, it still stumbles when aiming to aid the interactions of human beings. This challenge is very well suited for ICT/FET as it addresses directly one of the most important tasks for future ICT -- adjusting it to the emotional, psychological and social reality of the human world.

Communities Psychology, computer science, linguistics, management, anthropology.

Annex I: Terms of Reference

VISIONEER is funded within the scheme of Future Emerging Technologies (FET) Proactive, which is part of the Information and Communication Technology (ICT) Programme of the European Commission. FET acts as a pathfinder for the ICTs of the future supporting foundational long-term research and technological innovation and by fostering the emergence of new European research communities in ICT. FET addresses evolutionary and revolutionary approaches through multidisciplinary cooperation. It explores novel future technology options, identifies new drivers for research, and brings new science into ICTs to expand their scientific foundations.

To support this task, two main activities have been carried through: launching a web site which allows scholars to easily submit their proposals and sharing them with the rest of the community from which they could get feedback; organizing a workshop in order to prepare drafts of white papers of the project.

The afore-mentioned lines of action are detailed in the following annexes.

Annex II: VISIONEER Web Site The web-site http://www.visioneer.ethz.ch and its mirror //www.knowledgeaccelerator.eu have been created, set up and launched on Nov 18th with a broad promotional campaign, which reached more than 2000 people, among them mainly scientific scholars, but also some journalists and science foundations.

In parallel, a specific request for contributions has been sent to about 250 professors, who were identified as leaders of the fields relevant to VISIONEER.

By September 30th, the website's community had 138 registered active users from all over the world.

26 of them have submitted 43 contributions, 25 of them for work package WP4.

List of Contributors to WP4: Andras, Lorincz (HU) Arenas, Alex (E) Bazzani, Armando (I) Carbone, Anna (I) Draief, Moez (GB, F, TN)

Edmonds, Bruce (GB) Fioretti, Guido (I) Flache, Andreas (NL, D) Geroliminis, Nikolas (CH, GR) Gershenson, Carlos (MEX) Holyst, Janusz (PL) Kondor, Imre (HU) Mikhailov, Alexander (D, RUS, J) Nowak, Andrzej (PL, USA) Paolucci, Mario (I) Picascia, Stefano (I) Sato, Aki-Hiro (J) Scalas, Enrico (I) van Dijkum, Cor (NL)

Annex III: Visioneer Workshop Jan 13th -15th A 3-days workshop was held at the ETH Zurichâ&#x20AC;&#x2122;s Chair of Sociology, in particular of Modeling and Simulation, from 13 to 15. A selected international multidisciplinary group of scientists was invited to discuss about the topics of the VISIONEER project. Among the scientists were also representatives from the US and Japan.

The primary goal of the workshop was to identify the present shortcomings in the scientific fields addressing socio-economic systems and to the future grand scientific challenges, particularly challenges that can be addressed by complexity science and ICT. A second objective of the workshop was to prepare first sketches of the white papers, which are to be delivered as outcomes of work packages WP1 to WP3.

The following people have been participating in the workshop: Balietti Stefano (CH, I)

Battiston Stefano (CH, I) Caldarelli Guido (I) Carbone Anna (I) Ciampaglia Giovanni Luca (CH, I) Flache Andreas (NL, D) Helbing Dirk (CH, D) Kondor Imre (HU) Lozano Sergi (CH, E) Maillart Thomas (CH, F) Mazloumian Amin (CH, IR) Mihaljev Tamara (CH, D, SRB) Mikhailov Alexander (D, RUS, J) Murphy Ryan (CH, USA, SGP) Perez Roca Carlos (CH, E) Reimann Stefan (CH, D) Sato Aki-Hiro (J) Schneider Christian (CH, D) Swistak Piotr (USA, PL) Tedeschi Gabriele (I) Wu Jiang (CH, CN)

Annex IV: Current Shortcomings in Socio-Economic Research Outcome of the VISIONEER Workshop, 13-15 January Z端rich

1.0

THEORETICAL PROBLEMS AND OBJECTIVES Develop generalizations of theories currently

SPECIFIC Rational agent models, equilibria concepts, representative agent to

TYPES OF SOLUTIONS NEEDED Analytical and computational

EXAMPLES

CHALLENGES

Bounded rationality.

Multi-equilibria.

Heterogeneous agents

1, 11

1.1

1.2 1.3

contradicted by evidence Merge existing theories into more comprehensive theoretical frameworks Create theories of change/innovation Explain the natural emergence and evolution of factors that are typically fixed and accepted as "given"

1.4

Move away from typical simplifications

2.0

Move away from the standard notion of a unique prediction to researching possible worlds/scenarios Evaluate robustness of predictions

2.1

3.0

Move away from a method driven research

4.0

Create tools and interfaces making complex systems modelling widely available to researchers and students Identify facts, events and variables that are critical to various social sciences Create new indices, measures and methods to collect data

5.0

5.1

heterogeneous agents Micro and macro economics, theories of individual behaviour and institutions in political science and individual behaviour and social structure in sociology How new institutions and new behaviours emerge Learning, adaptation, preference formation, emergence and change of norms, values and cultures, emergence and change of new functions of a system where function is modelled as a dynamic, contextdependent, evolving property From static to dynamic models, from rational actor to alternative models.

Analytical and computational

1, 5, 14

Mostly computational Analytical and computational

5, 7, 10

Analytical and computational

4, 5, 6, 11, 12

From Nash equilibria to evolutionarily stable strategies, bounded rationality models, agent based modelling

Computational

How robust are analytical predictions of existing theories?

What happens when we introduce noise and feedback?

Some analytical solutions may be possible but mostly computation is needed

Simple statistical models like regression models.

Currently used functional forms that lend themselves to analytical solutions Create classroom interfaces.

Create systems and interfaces of relevance to all social sciences, policy and decision makers.

Computational

Computer science, systems design.

1, 8, 9, 11, 13, 14

General equilibrium in economics, rational agent models in economics, political science and sociology.

Noise induced transition.

Artificial societies, models of complex systems

1, 3, 9, 11

Netlogo, Igraph.

14,15

Expert opinion

Use ICTâ&#x20AC;&#x201D;private and public repositories.

Use ICT infrastructure for generating new data and controlling for factors we cannot manipulate in reality.

Analytical and computational

1

6, 8, 9, 12

1, 2, 6, 8, 9, 12, 14 Use existing data basis that were not used for research (ebay, financial markets data, google data, social networks data)

4, 5, 8, 9

Use existing monitoring ICT systems.

A

PRACTICAL PROBLEMS (THREATS TO SOCIAL, ECONOMIC AND POLITICAL INSTABILITIES) Sudden Breakdowns

B

Conflict

C

Sustainability

D

Institution Design

E

Social Capital

F

Emerging Forms of Social Organization and Control

INSTANCES

CHALLENGES

Financial crises Epidemics Revolutions Migration Hunger Wars Terrorism Balance of power Intercultural conflict Global warming Scarce resources Ecology Demography Mechanisms to improve progress in science (multidisciplinary exchange, convergence, mutual understanding, fashions, common language) How to organize separate institutions into a federation (countries, regions, etc.)

Size of organizations and their stability Social mobility Multiculturalism and discrimination â&#x20AC;&#x153;Rightâ&#x20AC;? amount of central control Forms of optimal political organization (degrees of democracy, bottom up governance) Regulation of economic markets Trust Cooperation Compliance Solidarity Imbalance between individual and collective rights Cyber threats Internet communities Instantaneous political mobilization Privacy threats: the ability of states and large corporations to control vast amounts of private information

1, 2, 5, 9,11

5, 6, 10

Addressed by the Global System Dynamics and Policy (GSDP) community 1, 4, 5, 10, 13

4, 5, 6, 10, 14

5, 7, 9, 10, 13,14, 16