and integration and convergence of functions and systems; Proliferation of nation states and groupings of peoples seeking self determination status. 2. 2. Drivers of change The second key definition concerns those forces,
so for this survey it will not be possible to rigorously provide a single definition that fits all situations so the following examples are useful to guide those seeking to imagine what could shock the systems of incremental change.
which created significant shocks to the global security, airport screening and intelligence systems and practices;
and risk managers define vulnerabilities within a given system and to then consider what type of event might de-stabilise that system.
Challenging Petersen's hypothesis, his additional thoughts on‘Cascading Discontinuity Sets'broke away from the idea of wild cards to introduce other types of interrelated events.
unplanned events that eventually overwhelm the system's ability to cope. The idea is similar to the Black swan theory described by Taleb 10 in his book‘‘The Black swan''.
Such sudden and unique incidents might constitute turning points in the evolution of a certain business social trend or system.
and Web research guides we are finding less use of the Library of Congress classification system, a system
somewhat noisy and generally socially situated indicators of change in trends and systems that constitute raw informational material for enabling anticipatory action.
The general area of health system developments and changes is also prominent. Perhaps the most provocative ones are the trends describing broad new domains of human evolution (e g. genetic manipulation
The majority of the respondents around the globe considered that more than 75%the trends will have high impact on the STEEP systems.
Almost all respondents from different Foresight affiliations stated that over 70%of the trends identified will have high impact on the STEEP systems.
Many of the most articulately described drivers were associated those with the management uncertainties of change in the environmental, governance and globalization response systems.
Almost all the survey respondents considered that the drivers will have medium to high impact on the STEEP systems with the large majority of the experienced respondents (73%)considered high impact.
and the remaining 35%will have medium impact on the STEEP systems. The figures were 75%high and 25%for medium for the Australasian respondents.
The majority of respondents (around 68%)consider that the drivers will have high impact on the STEEP systems,
Cyber crime and network vulnerabilities from failure of human systems Increased barriers to access to natural resources Growing organizational and governance incapacity Water recognised as a valuable resource
confidence levels in the ability of existing systems to adapt; Usual suspects (natural disaster, nuclear accidents, etc.
could fundamentally change the ways some familiar and long surviving societal systems. Again, to be able to embody there types of wild cards into some scenarios could be a provocative and rewarding exercise to test some of the leverage points that may impact change
creation of out-of-control species, viruses, robots Disruption of technological systems Artificial intelligence passes human capacity Shocking scientific discovery challenges all hitherto received ideas, e g.,
crime and pollution Total satellite failure interconnectivity black out More frequent natural catastrophies divert resources from development Millions of weather related refugees disrupt global system Religion
The majority of the drivers identified were identified as likely to have high impact on the STEEP systems with the rest of the drivers (approximately a quarter of them) likely to have medium impact.
nature, safety, home Personalised genomic healthcare Rapid reversal of tolerance to multicultural populations Human systems adapt to new culture of physical and biological requirements Reduced need
is responsible for European cooperation and for coordinating foresight activities as well as the research area on sustainable energy systems at the ZHAW Institute of Sustainable development.
sustainability and foresight research by applying monitoring and evaluation systems, Delphi survey, SWOT analysis and scenario development methods in various contexts over the last ten years.
cahu@zhaw. ch Peter De Smedt has a background in ecological system analyses. His professional challenge is connecting science and policy.
none of these methods are able to systematically reproduce a complete system; they all have their specific limits.
At the same time, the transport system is confronted with many challenges that reduce economic vitality and quality of life such as climate change, the emission of pollutants and noises, accidents, congestion;
In part, at least, these unintended effects and theses controversies are rooted in the complex nature of the transport system.
Also, the technology-infrastructure systems are enabled dependent on, and by, technological developments in different areas; the most important of which might be the energy sector and the development of information and communication technologies.
So, transport is a socio-technical system that is influenced by, and interwoven with, many factors inside and beyond its boundaries.
Political interventions into this field have many effects within the system, but also various impacts outside the transportation sector.
whereas a general differentiation is made between uncertainty due to variability and uncertainty due to limited knowledge of the system.
It is the sheer complexity of the system that might lead to the ex ante assumption that something unintended could happen.
‘‘structurally open''versus‘‘structurally closed''The transport system is embedded in the broader social, economic and environmental systems.
From a policy analysis perspective, the transport system, with its components and their interrelations, could be understood as an abstract conceptual model
This web-model of the transport system illustrates well that, when tackling one of the nodes,
At the more or less blurred borderlines, other systems (energy system, land-use patterns and economic system) are attached and interact.
Therefore, they build up systems with clear and sharp borderlines. In general, they allow for the further specification of knowns rather than for the detection of any unknowns (see Figure 1). Typical examples are transport models.
and to separate facts from norms Focus on effects inside the predefined system Help getting a rough understanding on effects Effects outside the system cannot be detected Open in principle to detect effects beyond system boundaries Specifications
A positive example for a careful application and integration of results of different FTA METHODS is the development of the European commissions (Commission of the European communities, 2008)‘‘Action Plan for the deployment of Intelligent Transport Systems''(ITS.
defining the role ITS will play in the future road transport system in Europe. In preparation for the action plan, an ex ante impact assessment was conducted to examine the options for action regarding ITS
''The key argument is closed that methods are rather usable in situations where the system under consideration can reliably be described
or developments where knowledge about the system and its internal structures is rather weak. The latter is falling into the categories of known unknowns
Commission of the European communities (2008), Action Plan for the Deployment of Intelligent Transport Systems in Europe.
and how disruptive events happen in systems and how responses could be better, particularly in the policy-making arena.
and to provide capabilities such as reframing to visualise systems from very different perspectives, including those considered impossible now.
1. A system cannot be explained by breaking it down into its component parts because the key element is the interaction between the parts.
The system needs to be considered as a whole. As a result of these interactions complex systems exhibit emergence (self-organised) behaviour that results from these interactions.
The location and availability of taxies in a city cannot be explained by breaking the system down into its individual parts drivers, cars, customers, fares, other taxies etc.
Rather it is an emergent property of the whole system resulting from the interaction between all the parts the taxies and customers
the road system, the traffic (itself an emergent property of a city's transport system), city taxi rules,
and even the weather (the system environment): The implication is that foresight techniques must be able to embrace emergence
Foresight techniques need to enable practitioners to develop a vision of a system's emergent properties the self-organised behaviour that could result from interactions between the parts. 2. All systems have component agents (taxies,
customers) and each agent in a system acts on its own set of rules and can be thought of as trying to get the best''outcome for itself (best fare for the driver, lowest fare or fastest ride for the customer).
''But the rules do not have to be fixed they can change according changes in the system too (for a driver a late night in a bad area may change the first rule to‘‘don't stop for anyone''.
Foresight techniques need to enable a vision of changes in the essential profile of a system. 3. The interactions between the component parts of a complex system
Systems are therefore not just very difficult to predict they are fundamentally impossible to predict.
VOL. 14 NO. 4 2012 jforesight jpage 295 Systems can also be unexpectedly very stable highly resistant to change by policy intervention-or very unstable such as where a policy intervention leads to stream of unexpected changes
''Not only does phase change happen very suddenly and over the whole system, but there are no early warning signals.
as organisational systems (people) adapt to the new environmental parameters (policies) the system can change radically, Ridgeway et al.
(called‘‘attractors''as they are states to which the system is attracted) ''which can which render policies utterly ineffective:
The starting slate is never clean extremely tiny errors in understanding where the system starts from can send any‘‘forecast''off in totally the wrong direction.
The implication is that foresight techniques need to recognise that a system has a critical history
a system cannot go back to where it was as the initial conditions have changed now. Failed policy cannot be repealed
Foresight techniques need to recognise that everything is part of a system, that there is no‘‘new''starting point,
Systems evolve, as do the agents, their rules and interactions and the system plays out in a‘‘fitness landscape''.
''Imagine a landscape of mountains and valleys, where‘‘high''is good for an agent (a performance measure) an agent (taxi driver) aspires (has a strategy to) be on a high peak (making a big profit).
The entire system can be seen as a network of relationships and interactions, in which the whole is very much more than the sum of the parts.
A change in any part of the system even in a single element, produces reactions and changes in associated elements and the environment.
Therefore, the effects of any one intervention in the system cannot be predicted with complete accuracy, because the system is always responding
and adapting to changes and the actions of individuals. Mikulecky (2001) Complexity is the property of a real world system that is manifest in the inability of any one formalism being adequate to capture all its properties.
It requires that we find distinctly different ways of interacting with systems. Distinctly different in the sense that when we make successful models
the formal systems needed to describe each distinct aspect are not derivable from each other. Axelrod and Cohen (2001) A complex system is a body of causal processes and agents
whose interactions lead to outcomes that are unpredictable. So the interactions among agents often have unpredictable consequences
thus changing the frequencies of the types within the system. The taxi example can be explained easily in these terms, Table I;
B Enable a vision of a system's emergent properties. B Embrace emergence rather than planning and forecasting.
and essential profile of a system can change (where rules can be laws and policies,
B Recognise that everything is part of a system where tiny, trivial actions can have huge, irreversible impacts.
VOL. 14 NO. 4 2012 jforesight jpage 297 B Enable practitioners to visualise systems from very different perspectives,
changing the frequencies of the types within the system More successful drivers, fewer new drivers, more cleaner taxies More faster birds,
The resulting implication is that a system cannot be controlled from above ''and so policy operating in a complex system cannot achieve a specific outcome directly.
specifically policy makers must focus on the idea of interactions rather than a system's constituent parts
Simplistically, it is about understanding the system, in terms of a system's interactions rather than its component parts,
Axelrod and Cohen (2001) VOL. 14 NO. 4 2012 jforesight jpage 299 describe the idea of harnessing complexity to deliberately change the structure of the system,
which a system is perceived use of different mental models, or reframing. Again, policy makers need to watch for the‘‘emergent''properties that arise as a system organises itself following a policy intervention,
and use that policy to preserve the conditions in which the best solutions arise. With these perspectives, the link with,
and harnessing the system, can all enable policy makers to see the system from a different perspective
and to generate both optimum and (currently) non-optimum alternative potential strategies and options. In terms of policy making‘‘
rather than working with (in) interactions of the systems components itself. Similarly with techniques such as trend or driver analysis,
and rhythms rather than events (a specific example of focusing on interactions rather than constituent parts of a system), promoting effective neighbourhoods, building networks of reciprocal interaction,
and why future disruptive changes may happen in a system. It also provides insight into how foresight techniques need to be developed to perform better in complex systems to enable better decision-making and policy making.
and skills (such as reframing) to visualise systems from very different perspectives including ones that are considered not possible now,
Policy making In a complex system (which all societies are need) policy makers to recognise that systems are all about relationships and interactions between the constituent parts rather than about the details of the constituent parts.
They must recognise that everything is part of the system, and that tiny, trivial actions can have huge, irreversible impacts.
and the essential profile of a system can change, where the‘‘rules''can be laws and policies,
Policy making needs foresight techniques to enable a vision of the system's emergent properties and also of phase change situations (without early warning signals) and of the resulting changed world.
Policy making must use techniques such as Reframing to visualise systems from very different perspectives including ones not possible now,
Miller, R. and Poli, R. 2010),‘Introduction to a Special issue on anticipatory systems and the philosophical foundations of future studies'',Foresight, Vol. 12 No. 3. Mitchell, M. 2009), Complexity:
Everyday personal traffic increasingly by foot, by bike or by improved public transport systems. With goods transport rapid development of intelligent logistic chains has lowered the demand Passenger transport with electrical vehicles Transport needs grown
Dramatic improvements in energy efficiency and elastic price system the main reasons behind decreased consumption Decreased by 14 from 2008 level.
References A°kerman, J. 2011),‘Transport systems meeting climate targets. A backcasting approach including international aviation'',doctoral thesis, Royal Institute of technology, Stockholm.
and systems that relate directly to the nanoscale. The ability to control matter at such small length scales got a big push by the development and improvement of a variety of microscopes (e g.
Here again, we see topics that relate to the very far and speculative future such as nano-systems that control
systems development, site development and building construction. Each of the five steps has its own geographical scope, objectives, operational methods, norms and administrative procedures.
the functional implications for the territorial system are determined, which may display territorial elements, socioeconomic flows and local stakeholders.
After determining all kinds of implications across the territorial system, the analyst should be able to perceive the gap between the proposed future vision and the present situation of the territory
This context clearly benefits the Spanish productive system because it incorporates a sustainable integrated economy into the global markets.
This goal may be achieved by analysing the in depth implications of each future scenario for functional systems, parametric indicators and spatial patterns. 4. 2 Step 2:
The existence of strong social capital permits a decentralised democratic system. This model requires a strong set of management skills in all public organisations to guide participation and coordination actions.
Major outputs of the planning process are the creation of new natural sites, the provision of a high quality public transport system and the rehabilitation of integral parts of a city.
The medium-low density communities and their traditional lifestyle and production systems have not posed any threat to its sustainability in the past.
Regarding the transport system, new road development will kept to a minimum, while the railway network will be augmented substantially and improved.
The implementation of the public transport system will not be feasible due to the excessive dispersal of land uses and the low density population.
B Promote an educational system that transmits the values of sustainability, innovation, social commitment and solidarity.
B Set up an educational system aligned with new social and environmental values. B Establish mandatory measures to diminish energy consumption
A dynamic and sometimes turbulent environment puts enormous pressure on rational planning systems, which in many cases have been designed to simulate highly stable and predictable functional systems.
Therefore, foresight methods represent an emerging approach that works with few technical constraints and shows an increased adaptability to environmental changes.
complementing the scenarios with a system of monitoring mechanisms, legal contingency planning, and preparatory measures.
and manage complex, global, socially interactive systems,..r evealing the hidden laws and processes underlying societies''(www. futurict. eu). The objective is
a modelling system with the ambitious plan of turning massive amounts of data into knowledge and technological progress.
''PAGE 340 jforesight jvol. 14 NO. 4 2012 While the‘‘Living Earth Simulator''will‘‘require the development of interactive decentralized supercomputing that scales up to global level systems
reflected in its proposal to use modelling systems (along with its data mining procedures) to better enable
In effect, the use of modelling systems corresponds to one of the most recent trends in FTA.
a computerized crime mapping system developed by NYPD in 1993 and now used by police departments nationwide.
scenario planning, backcasting, modelling systems and simulation platforms) offer a number of important advantages when applied to the legal context.
This is the case of modelling systems, such as Futurict. VOL. 14 NO. 4 2012 jforesight jpage 343 The application of modelling techniques to the legal domain represents a step further in the use of ICT, Artificial intelligence (AI) and other advanced
for instance, knowledge based systems and intelligent information retrieval. With the development of modelling techniques and instruments such as the one described above,
I believe that the employment of modelling systems in political discussion and deliberation exercises should also be used in the preparatory phases of legislative procedures.
I propose the idea of attaching modelling systems and simulation platforms to parliamentary activities of lawmaking processes as another example of a FTA technique applied to Law.
Still within the field of lawmaking, modelling systems could be combined with other FTA METHODS, such as backcasting and future verification procedures.
global modeling system which acts as a powerful tool for the exploration of the long-term future of closely interacting policy-related issues (including human development, social change and environmental sustainability).
and measurement systems optimized for the Industrial Age models of production. According to the author, foresight needs a paradigm shift in the Knowledge society,
Nanotechnology is dealing with functional systems based on the use of sub-units with specific size-dependent properties of the individual sub-units or of a system of those...
Functional systems are systems where the (technological or natural) functionality to be considered provides the criteria for defining system boundaries...
The specific-size dependence of these properties becomes evident when they a) no longer follow classical physical laws
because this would imply exclusion rules independent from a scientific evaluation of the fundamental working principles of a functional system described by the three criteria.
or systems and integrated into reliable and marketable products. The segment of dnanotechnologyt that is closest to a widespread application is the field of dnanomaterialst.
or distinctions and often using varying terminology the following basic elements (1) definition of task and system (2) analysis of technology, their applications and framework (3) impact assessment (4) evaluation and development
and institutes (representing basic research on nanotechnology related phenomena, material researchers and developers, systems engineering, toxicology of nanoscopic structures,
Since 2003 he is a member of the scientific staff and since February 2004 deputy head of the Institute for Technology assessment and System Analysis (ITAS) at the Research centre Karlsruhe.
the FTA Conference Scientific Committee took the stance that FTAHAS a potentially useful role to play in exploring future developments of complex societal systems and in defining effective policy actions, by way of:
complex and adaptive nature of the systems we are dealing with today, as well as to the chaotic phases through which these systems may pass,
when moving to the molecular era, thus limiting the possibilities of forecasting. He continued that
if we want to bring the systems approach closer to the real world, the organisational and the individual perspectives would become essential,
a crisis of consciousness, of behaviours, of cultures and of systems (Hames 2011a. In response to these crises, he saw a need for new forms of dialogue at different levels,
and the difficulties they face in the complexity of interconnected innovatiio systems. They argue that RTOS face a systemic-temporal paradox:
anticipatory systems; innovation; creattiv evolution Introduction Predictions about future almost always fail. In this paper, the epistemic and ontological causes for this failure are described and their implications for foresight, innovation policy,
theory of autopoietti and anticipatory systems, and cultural historical theories of cognitive development and social learning.
we describe and expand Robert Rosen's analysis of the nature of modelling and the relationships between natural and formal systems.
Already relatively simple systems have interactions, nonlinear dynamics, and sensitivity that lead to chaos, strange attractors,
Innovation and social learning in the context of the local downstream systems of meaning then become key drivers for the evolution of technology.
and systems of categorisation (Schon 1963; Fleck 1979; Dosi 1982; Perez 1985; Garud and Rappa 1994;
and systems of meaning that are located in communities of users and social practice. The true nature of the beast is revealed only when someone domesticates it.
In mobile technology, global system for mobile communication (GSM) short messaging is created in a similar fashion.
Constant 1987) and with specialised systems of knowledge and meaning (Polanyi 1998; Knorr Cetina 1999.
it is useful to recall Robert Rosen's work on anticipatory systems. According to Rosen (1985), anticipatory systems are systems that contain predictive models,
allowing future to have an impact on the present: To take a transparent example: if I am walking in the woods,
7) An anticipatory system, therefore, needs to include a model that generates predictions. In some cases, the model can be hardwired'in the biological system.
For humans, anticipation is hardwired less, and we can continuously adjust our expectations and predictive models.
Scientific models create linkages between natural and formal systems. In Rosen's terminology, natural systems include stones, stars, solar systems, organisms, automobiles, factories, cities,
and any other entities in theworld where a set of observable qualities can be related. Natural systems are the substance matter of sciences and
what technologies seek to fabricate and control. Natural systems are at least partially constructions of the human mind
but natural selection and the linkage between action and cognition weed out models that are incompatible with the world.
Natural systems change their states based on interactions between the system elements. These interactions in natural systems are
what we usually call causality. Simple observation of a natural system, however, can never tell us anything about the relationships between the observables.
Relationships between qualities are never observable as such. We can observe correlations, but there is no natural way to extrapolate from correlations to causal relations.
we need to relate the natural system with another, formal, system, where predictions become possible.
The crucial point for Rosen is that time works differently in natural and formal systems.
In natural systems, time separates events into two classes: those that are simultaneous with each other
and those that are ordered as predecessor and successors. The predecessor success relation generates causality. In a formal system, in contrast, causality is expressed in structural
or logical relations that remain true independent of time, and time becomes a parameter that can be used to label system states.
In practice, this means that if the formal model is good enough a representation of the natural system,
we can use the formal system to find out the state of the natural system in some future point of time.
This will allow us to test the implications of alternative imputed relationships between the observables.
We can observe a natural system create hypotheses about the unobservable causal relationships, fast forward the formal model to a future point of time,
and check whether our natural system actually ends up in that state or not. This, indeed, is the only way we move from simple correlations to theoretical models.
we have to encode the states of the natural system into corresponding states of the formal system.
or predict the impact of causality in the natural system by using the rules of inference in the formal system.
the way we construct a natural system depends partly on our capacity to successfully model it.
In practice, we have to experiment with alternative systems of encoding to find one that pragmatically fits the task at hand.
Indeed, speaking informally,‘a state embodies that information about a natural system which must be encoded in order for some kind of prediction about the system to be made'(Rosen 1985,75).
If the nature is a lock, we try different keys until one opens the Lock in general,
for example, the construction of those artificial natural systems that we usually call technology. Rosen clarified the modelling relation in considerable theoretical and conceptual RIGOUR.
however, leaves somewhat open the question howwe come up with the natural systems in the first place. Rosen combines here a partly Bergsonian explanation,
we purposefully locate natural systems and formal systems together. This is because natural systems are also cognitive constructions, partially based on existing anticipatory models and partially on the available repertoire of cognitive categories.
The actual interactions of the world transpire on the left-hand side of the figure, behind a‘phenomenological veil'.
'On the right-hand side, time is a parameter that can be used to label system states
We construct natural systems and their associated predictive models by abstracting the lived reality. As Bergson (1988) pointed out
This means that both natural systems and their predictive models are necessarily to a large extent retrospective.
It arises because a natural system can be constructed using inappropriate categorisation systems because the natural system may be mapped into inaccurate predictive models using codings that leak information,
and because the observables can be measured with error. Ontological Downloaded by University of Bucharest at 04:52 03 december 2014 Foresight in an unpredictable world 745 Figure 2. Modelling in the context of the phenomenological veil. unpredictability,
introducing novelty that irreversibly changes natural systems and makes their predictive models obsolete. Implications for foresight and future-oriented analysis What are the practical implications of the above conceptual analysis for foresight and futureorieente analysis?
Innovation changes the way the natural system itself needs to be constructed. Ontological expansion means that we do need not a better model;
facts exist only for natural systems that have associated measurement instruments and established encodings and decodings between the natural system and its formal model.
It is therefore very difficult to formally model systems when innovation matters. Policies that are legitimised by facts,
foresight efforts therefore could more appropriately be located around the problem of articulating natural systems, instead of formulating predictive models.
an educational system geared towards producing skilled labour, and public financing systems that are based on all the above assumptions.
In other words, assuming that the industrial society remains as it used to be, extrapolations from demographic data lead to an unsustainable state.
and other articles in the same special issue of foresight on anticipatory systems. Notes on contributor Ilkka Tuomi is Chief Scientist at Meaning Processing Ltd.
The social construction of technological systems: New directions in the sociology and history of technology.
Services and facilities to be provided in the GSM system. GSM Doc 28/85 rev. 2. Constant, E w. 1987.
Community, system, or organization? In The social construction of technological systems: New directions in the sociology and history of technology, ed. W. E. Bijker, T. P. Hughes,
and T. J. Pinch, 223 42. Cambridge, MA: The MIT Press. Dosi, G. 1982. Technical paradigms and technological trajectories a suggested interpretation of the determinants and directions of technological change.
The dynamics of transitions in socio-technical systems: A multilevel analysis of the transition pathway from horse-drawn carriages to automobiles (1860 1930.
Robert Rosen's anticipatory systems. Foresight 12, no. 3: 18 29. Luhmann, N. 1990. Essays on self-reference.
Self-organization in nonequilibrium systems: From dissipative structures to order through fluctuations. Newyork: Johnwiley & Sons. Nishida, K. 1987.
Anticipatory systems: Philosophical, mathematical and methodological foundations. Oxford: Pergamon Press. Downloaded by University of Bucharest at 04:52 03 december 2014 Foresight in an unpredictable world 751 Rossel, P. 2009.
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