SUSTAINABILITY IISUSTAINABILITY II Part II: Foresight Processes - Co-Designing desired Futures

Josef FröhlichIKA ] a [ Akademie der bildenden Künste Wien 7th April, 2014

Consequences for the orientation of complex systemsThe example Innovation management

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Complex System – a well established definition

“A complex system is one whose components interact with sufficient intricacyA complex system is one whose components interact with sufficient intricacy that they cannot be predicted by standard linear equations; so many variables are at work in the system that its overall behavior can only b d t d t f th h li ti f ll i dbe understood as an emergent consequence of the holistic sum of all myriad behaviors embedded within. Reductionism does not work with complex systems, and it is now clear that a

l d ti i t h t b li d h t d i lifpurely reductionist approach cannot be applied when studying life: In living systems the whole is more than the sum of its parts”.

Source: Levy, 1994

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Complex systems and their general features

Complex systems consist of a number of Complex systems consist of a number of -at least three – agents

Agents in complex systems adapt to their i t th h

System

Selforganizationenvironments through self-organisational processes.

Precondition for self-organization:

g

Open systems which are able to gather resources from the environment

Agents are connected by a multitude ofFeedback loops Agents are connected by a multitude of links and therefore interact non-trivially

The interactions in complex systems are non linear which means that feedback

Agent

Feedback loops

non-linear, which means that feedback loops between agents do exist.

Openness

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General features of complex systems

Feedback loops between agents in complex systems can have positive or Feedback loops between agents in complex systems can have positive or negative effects on the systemic behaviour

The time-dependent behavior of complex systems can show several states

Even small variations of the initial condition can switch the system from a statically state into a chaotic state,

which in turn can produce a new collective behavior as an emergent which in turn can produce a new, collective behavior as an emergent phenomenon

Emergence and the development of macroscopic phenomena can be d t d f l l i i i t ti d t ifi lfunderstood from local microscopic interactions and actor specific self

organizational processes

Stephen Hawkins: “Complexity will be the science of the 21st Century”

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Consequences for the orientation of complex systems

Continuous monitoring of changes in the framework condition and the Continuous monitoring of changes in the framework condition and the environment of complex systems and of (policy) interventions in complex systems is necessary Establishing an evaluation culture to support (policy )learning Establishing an evaluation culture to support (policy-)learning

Bundling of political instruments and measures / policy mix is necessary to orientate complex systems into desired corridors Adaptive political requirements / adaptive governance

New instruments for the transition management for long term transformations of complex systems are necessary Platforms and other “weak” coordination regimes are needed to govern

complex systems Shaping the future of complex systems by participatory projects e.g.Shaping the future of complex systems by participatory projects e.g.

foresight processes, mission statements, visions, target corridors

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From Forecast to ForesightWhy do we need Foresight processes?

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Why do we need Foresight processes?

Increasing demand on

prospective andprospective and strategic

methods and tools in politics

and management

Increasing change in science and society scenarios beyond short time

Need for shared orientations, visions and leitbilderIntegration of

planning horizons

Increasing interdependence and international networking ( l it ) li iti th

Limited influence of individual actors

gdifferent perspectives and disciplines

(complexity) limiting the classical planning methods

coordinated action are necessary

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Functions of Foresight – 5 C‘s

Concentration on the future exploration of scientific technological Concentration on the future - exploration of scientific-technological developments and socio-economic demand „...systematic attempt to look into the future of science, technology, economy and society“ not focused on the very one most probable future but on several scenarios“„.. not focused on the very one, most probable future, but on several scenarios

Communication – participatory learning process „... widening of the participants‘ horizons and learning in developing results through active

involvement of participants“p p

Consensus and conflict – shared understanding of future challenges, goals and priorities „.. systemic, participatory, future intelligence gathering and vision-building process“„.. systemic, participatory, future intelligence gathering and vision building process „... identify areas of strategic research and the emergence of generic technologies likely to

yield the greatest economic and social benefits“

Commitment – mobilization of actors and stakeholders „.. mobilizing joint actions“

Coordination – enabling coherent actor strategies „.. aimed at coordinating present-day decisions“

Source: Martin & Irvine 198911

Five generations of Foresight

First Generation (1970ies) First Generation (1970ies) Technology identification and forecasting

Second Generation (1980ies)( ) Anticipation of new technologies and markets

Third Generation (1990ies)C bi i l k h l i k d i l d l Combining outlooks on technologies, markets and societal developments

Scenario-thinking for collective strategies Mobilization of actors and stakeholders

Fourth Generation (2000s) Develop adaptive strategies to cope with different future scenarios Combining collective processes with intra-organizational strategic foresightCombining collective processes with intra organizational strategic foresight

The Next Generation Focus on how to deal with Grand Challenges Horizon scanning and identification of weak signals

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Key characteristics of foresight at AIT Innovation Systems

Development and application of a broad spectrum of support tools for Development and application of a broad spectrum of support tools for foresight – AIT Foresight Infrastructure Foresight Monitoring Database Bibliometric and scientometric tools Bibliometric and scientometric tools Online-Delphi processes, data mining, Horizon Scanning Modeling and interactive simulation

W k h b d h ( ti i t t di i li Workshop-based approaches (e.g. participatory, trans-disciplinaryworkshops for scenario building, World Café, IT-supported interaction)

A broad range of scenario development and analysis techniques (e.g. l t i i i i b k ti d i )exploratory scenarios, visioning, back casting, road mapping)

Long-standing experience – more than 60 projects for national and international customers and funding bodies

Tight embedding in international foresight networks European Foresight Monitoring Network EFMN and European Foresight Platform

EFP (EU-DG RTD) Cooperation with UNIDO, CASTED and other international organizations

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AIT-Innovation Systems: selected recent foresight projects

Future of science & innovationINFU & RIF 2030

Foresight for research programmes:FET Open

Sustainable energy for the future:eTrans 2050

Crosslinking foresight knowledge with foresight actors: EFP

U b EUrban Europe:Strategic Research & Innovation Agenda for the JPI

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New patterns in innovation management

Analysis and discussion of the emergence and diffusion of new innovation Analysis and discussion of the emergence and diffusion of new innovation patterns and their significance for European policy

A project in the 7th EU-Framework Program in cooperation between

INFU – research steps Collecting emerging signals of change – signal scanning Clustering and amplification of signals – contrasted visions Macro contextualization – megatrends and the socio-economic framework Consitent / different / plausible scenarios – integration and differentiation

1509.04.2014

INFU signal scanning

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INFU Clustering & Amplification of Signals

Clustering Amplification

Transfers to other sectors, to other user groups...

Clustering Amplification

e.g. from fashion to furniture industry; elderly people instead of kids or vice versa...

Generalisation as the mainstream practice... e.g. what if active users involvement i i ti ldin innovation processes would become the default…

Radicalisation of the principle...Radicalisation of the principle... e.g. what if user involvement in innovation process developed into an innovation actively developed by the demanddemand...

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Emerging innovation methods and paths

1_Open Source Society... 2_Virtual-Only Innovation... 3_Negotio-Vation... 4_Innovation on request... 5_Public Experimentation...What if experimentation would be at the core of innovation?

What if many innovations would be enjoyed only virtually?

What if innovation becomes publicly negotiated?

What if companies generate innovations from user

communities?

What if open source development becomes an all compassing

innovation pattern?

What if the emphasis on innovation spreads to all

workplaces?

What if people innovate together in proper places?

What if innovation is directed at population living in poverty?

What if people produce products themselves in fabrication

laboratories ?

What if innovation fatigue takes over and No-Innovation is en-

vogue?

6_No-innovation... 7_Innocamps... 8_90% Innovation... 9_CIY Create It Yourself... 10_Innovation Imperative...

What if companies would What if companies use digital What if we scan the internet for What if companies externalise

11_Innovation Marketplace... 12_Innovation Campus... 13_Darwin’s Innovation... 14_Web-Extracted Innovation... 15_Innovation meets Education

What if innovation skills would be on the education agenda of

kindergarden?

pcollaborate in joint innovation

places?

p gsystems to randomly create and test

innovation?ideas and automatically pick the

best ones?

pinnovation to an open innovation

marketplace?

Education...

What if the principle of “Waste equals Food”/”cradle to cradle” would be widely

adopted?

What if stores were to become laboratories where companies and customers co-develop

innovations?

What if cities became stronger actors in the field of

innovation?

What if the bulk of innovation wereto come from today’s emerging

markets?

16_Relocated Innovation... 17_Waste-based Innovation... 18_Laboratory Stores... 19_City driven Innovation...

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Future of innovation & Governance of innovation: Innovation Futures - INFU

Foresight project to analyse and discuss the emergence gand diffusion of new innovation patterns and their significance for European policy

Key dimensions of change:- Mediation and Coordination, - Participation,

M ti ti- Motivation, - Automatisation, - Infrastructures, - Creativity

http://www.innovation-futures.orgCreativity,

- Spatial shifts, - Systemic sustainability innovation

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RIF – Research and Innovation Futures

Funded by DG Research and Innovation (2011 2013) Funded by DG Research and Innovation (2011-2013) in order to „explore and analyze new and emerging ways of doing research

in the context of STI in universities research organizationsin the context of STI in universities, research organizations, companies and civil society“

Approach systematize knowledge on emerging patterns trends and drivers systematize knowledge on emerging patterns, trends and drivers outlook on future developments by way of scenarios identify and assess key issues against the background ERA establish a dialogue on strategic options for different establish a dialogue on strategic options for different

stakeholders.

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Scenario development: from explorative to transformative scenarios

→ each scenario storyline explores tensions & dilemmas and explains why & how a transformation process might take place 21

Five transformative scenarios 2030

Open Research PlatformsSelf-governance in a decentralized research landscape

(i)landscape

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Open Research Platforms: The dilemma 2020

Ongoing fragmentation of R&I (e.g., of funders, ROs)Conflicting actor strategies

Rising need for coordination (e.g. R&I efficiency, demand

Conflicting actor strategies (e.g., open vs. close R&I)

( g yfor societal solutions)

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Organisation principlesORPs are evolutionary self

Open Research Platforms: The research landscape 2030

- ORPs are evolutionary, self-organised platforms for open research attracting ROs & funders - governments embed activities, provide infrastructure & support certain ORPsinfrastructure & support certain ORPs

Research programming- ORPs create their own agendas evolutionary

f di i it ORP- funding agencies monitor ORPsOutput & quality- open & distributed research with supporting infrastructures in the backgroundinfrastructures in the background- quality regulated by researcher community - automated reputation management & fraud detection mechanisms, protection against

b tt k b th tifi ticyber attacks by authentification

Ownership & exploitation- open-source licensing (if any), some ORPs restricted for security reasonsrestricted for security reasons- industry competes to be first in exploitation

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Five transformative scenarios 2030

Knowledge Value ChainsKnowledge Value Chains Research for innovation in a specialized and simple structured research l d

(ii)landscape

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Knowledge Value Chains: The dilemma 2020

New Public Management reinforced; funding of fewer, but larger projectsAccelerating global innovation

A boost in efforts for fund raising & evaluation and stiff competition for limited funds put economic pressure Accelerating global innovation

races on ROs27

Organisation principles

Knowledge Value Chains: The research landscape 2030

- value creation in KVCs with (1) integrators on top, (2) specialized service providers, (3) suppliers of fragments - organized by business management principlesorganized by business management principles- national & regional governments support their organisations in KVCs Programming- governments & industry fund, closed circleprogram research for innovation- national & regional governments fund & program high risk basic researchhigh-risk basic research- industry basic research beyond KVCsOutput & quality- specific roles of organisation types in research- quality is defined, rated & assured by business management principlesOwnership & exploitation

industry/RIOs define ownership & exploitation/- industry/RIOs define ownership & exploitation/marketing of research products to customers

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Transformative scenarios 2030

Open Research Platforms Knowledge Parliaments Grand Challenges for RealOpen Research PlatformsSelf-governance in a decentralized research landscape

Knowledge ParliamentsThe free negotiation of knowledge claims

Grand Challenges for Real Collective experimentation in socio-technical labs

Knowledge Value Chains Research for innovation in a specialized and stratified

Researchers’ choiceAutonomous researchers go for self-fulfillment and a specialized and stratified

research landscapegwellbeing

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FET-Open: Boosting the exploratory power of open research

Project to support the activities of the European Commission to strengthen Openstrengthen Open Collaborative Research and to establish it as a new mode of funding and doing research indoing research in Europe.- Combination of survey, case studies and scenarios developmentscenarios development- Direct input topreparations for Horizon2020: embedding Open R h i i iResearch into existing European research funding and building a strong institutional base

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FET-Open: Open Research

What is Open Research? What is it not?What is Open Research?

it focuses on new ideas which are foundational and may have a

What is it not?

it is not mainstream research,foundational and may have a transformative character, it is purpose-driven, resp. aims at

technology development

it is not about small changes of existing models or approaches, it does not rely on track record alone,

technology development, it is bottom-up (defined by

researchers),

it is not pure basic science, it does not follow a policy agenda or

pre-defined topics, it is risky (possibility to fail), it is collaborative and involves

several researchers,

pre defined topics, it is not discipline-oriented research.

it is interdisciplinary.

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Sustainable energy for the future: eTrans 2050

Deriving „possible futures” for the Austrianfutures for the Austrian Energy - System from socio-economic perspectives

Identification of core- Identification of core fields for a system transformation oriented to a sustainable Energy-SystemSystem- Recommended actions for politics and other groups in our society

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The Joint Programing Initiative: Urban Europe

Megatrends for urban areas Megatrends for urban areas demographic development economic development and climate change

The heterogeneity of European cities was reflected in quantitative analyses -challenges for urban areas depend on the local historical, political, g p , p ,demographical, social, ecological etc. circumstances

Five research and Innovation areas were developed Urban Adaptability and DynamicsUrban Adaptability and Dynamics Social Inclusion and Urban Democracy Economic Vitality and Knowledge Based Society Sustainable Infrastructure and Networks Urban Environment and Ecosystem Services.

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Crosslinking foresight knowledge with foresight actors:European Foresight Platform – EFP / IFA

Knowledge platform for the foresightthe foresight community and decision-makers:E d Beyond Europe

http://www.foresight-platform.eu/

European and international networking

Beyond Europe

Two projects to establish shared knowledge platforms for the foresight community and decision-makers: Monitoring of foresight activitiesMonitoring of foresight activities Foresight briefs on selected projects and their impacts Thematic workshops on selected topics related to ERA European and inter-national networkingEuropean and inter national networking

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Selected publications (2010-2012)

Weber K M Cassingena Harper J Könnölä T and Carabias Baceló V (2012) Coping with a Weber, K.M., Cassingena Harper, J. Könnölä, T. and Carabias Baceló, V. (2012) Coping with a fast-changing world: Towards new systems of future-oriented technology analysis. Science and Public Policy, 2012, 39, 2, 153-165

Amanatidou, E., Butter, M., Carabias Baceló, V., Könnölä, T, Leis, M., Saritas, O, Schaper Rinkel P and van Rij V (2012) On concepts and methods in horizon scanning:Schaper‐Rinkel, P. and van Rij, V. (2012) On concepts and methods in horizon scanning: Lessons from initiating policy dialogues on emerging issues. Science and Public Policy, 2012, 39, 2, 208-221

Schartinger, D., Wilhelmer, D., Holste, D. and Kubeczko, K. (2012) Assessing immediate l i i t f l f i ht F i ht S i l I F i ht i t flearning impacts of large foresight processes. Foresight. Special Issue: Foresight impacts from around the world, 14, 1, 41-55

Schaper-Rinkel, P. (2011) Die Generierung von Zukunft: Von Utopien zu Idealwelten, Weltmodellen, Szenarien und Foresight, in : Frietsch, E, Herkommer, C (Hrsg.): Ideale. Entwürfeeiner “besseren Welt” in der Wissenschaft, Kunst und Kultur des 20. Jahrhunderts, Berlin: Kadmos

Abadie, F., Friedewald, M. and Weber, K.M. (2010) Adaptive Foresight in the Creative Content Industries: Anticipating Value Chain Transformations and Need for Policy Action. Science and Public Policy, 2010, 37, 1, 19-30y, , , ,

Havas, A., Schartinger, D. and Weber, K.M. (2010) The impact of foresight on innovation policy-making: Recent experiences and future perspectives. Research Evaluation, 2010, 19, 2, 91-104

Eriksson E.A., Weber K.M. (2008): Adaptive Foresight. Navigating the complex landscape of policy strategies Technological Forecasting and Social Change Vol 75 pp 462 482policy strategies, Technological Forecasting and Social Change, Vol. 75, pp. 462-482

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