Emerging Practices in Foresight and Their Use in STI Policy

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Emerging Practices in Foresight and Their Use in STI Policy

Cornelia Daheim* & Sven Hirsch**

AbstractForesight, a major methodological tool in the STI policy toolbox, has recently featured new directions in methodological development, becoming influenced by progress in information and communication tech-nologies and online tools. However, no overview of these directions has been available so far. Based on a literature review, an interactive workshop, and an international expert survey as well as expert interviews, the research presented here attempts to shed light onto some of the relevant issues by providing a structured overview of recent changes in order to further the debate on the future directions of methodological develop-ment in foresight. The paper outlines four clusters of emerging approaches in foresight:Integrated qualitative and quantitative approaches, IT-based and automated foresight, experiential foresight including new forms of communication and interaction such as visualization and gaming, and open and crowd-sourced approaches. The benefits and challenges of the approaches known so far are categorized and summarized, and areas of potential use for each of the clusters in STI contexts are identified.

KeywordsForesight, new methods, STI policy processes, future perspectives

The authors would like to thank all experts who have contributed via informal consultations, the survey and the interviews, especially Dr. Kerstin Cuhls and Dr. Martin Rhisiart for co-facilitating the workshop at the EU-FTA conference, and most importantly STEPI and its reviewers for supporting this research under their fellowship program and for their invaluable feedback.

* Founder and Principal, Future Impacts Consulting, Cologne, Germany, [email protected]** Foresight expert at Future Impacts Consulting and Lecturer for modeling of complex systems, ZHAW Zürich (Zürich University of

Applied Sciences), Zürich, Switzerland [email protected].

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1. INTRODUCTION

CHASING THE NEW IS DANGEROUS TO SOCIETYEVERYTHING THAT'S INTERESTING IS NEW

(Jenny Holzer, Truisms, 1984)

1.1. Background

Foresight, a methodological pillar of long-term oriented science, technology and innovation policy, is showing new directions of methodological developments. Foresight is defined as “a systematic, participatory process, collecting future intelligence and building medium-to-long-term visions, aimed at influencing present-day decisions and mobilising joint action (Havas, Schartinger, & We-ber, 2010). Recent changes in the methods employed in foresight stem from several drivers includ-ing:

• changes in demand in its use in science, technology and innovation (STI) policy (for example a demand for wider participation) and also in other decision-making arenas, such as corporate foresight or foresight for other public bodies;

• technological innovations that enables new approaches (for example improvements in infor-mation technology that enables progress in text mining and clustering for scanning in fore-sight);

• research and practical insights into weaknesses in the traditional approaches and attempts to thus further develop approaches (e.g. the push to more clearly demonstrate impacts and create deeper forms of engagement).

Different aspects of the recent methodological developments have been discussed using a variety of labels and terms, such as “Foresight 2.0,” “Open Foresight,” “5th generation foresight,” “networked foresight,” and “experiential foresight” (Daheim & Uerz, 2008; Desaunay, 2014; Hines & Gold, 2013; Porter, 2010; Prime Minister’s Office Finland, 2014; Ramos, 2012; Saritas, Burmaoglu, & Tabak, 2014; Schatzmann, Schäfer, & Eichelbaum, 2013; van der Duin, Heger, & Schlesinger, 2014). They relate, for example, to these approaches: IT-tools that support foresight; using the “intelligence of the crowd” for generating long-term-oriented research insights (crowd-sourced scenarios); the (re)integration of qualitative and quantitative approaches in foresight (qualitative-quantitative scenarios); “gamification,” visualization and design fiction or “experiential foresight” as new ways to produce insights and communicate results, for stronger engagement with a wider group of process participants and decision-making or policy implementation.

Thus, although the reflection on these changes has been the subject of a lively and more and more prominent discussion in the foresight and STI community in the last years, there are few attempts at more formal overviews and reflections of the impacts of these developments so far, apart from the discussions in several expert and working groups of the relevant networks and associations or in conferences, and some analyses on only one aspect of these developments. So far, no overview of these individual aspects of the overall methodological development has been produced and backed

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STI Policy Review_Vol. 6, No. 2

up by the input of a significant number of experts. As many of the “new” approaches have not yet been published in a formal way, and as the attempts at overview and reflection on impacts have so far focused on only one aspect (e.g., the online-based approaches or the integration of qualitative and quantitative), it remains difficult to judge the overall picture (Ciarli, Coad, & Rafols, 2013) and conduct a productive discussion about future directions without this common ground of a shared perspective of the current situation. This study thus aims to shed light onto some of the relevant issues by trying to provide a structured overview of these changes, backed by the view of experts on current developments, and thereby further the debate on future directions of methodological development in foresight. We chose STI policy as the specific field of use, as it is widespread and of key importance in the use of foresight. Especially against the backdrop of a more complex, volatile and rapidly as well as consistently changing policy environment, foresight grows in importance in STI Policy as it can serve as “a crucial part of an early warning system” (Havas et al., 2010). This is especially critical as on the one hand, new approaches are called upon to deliver better results and impacts in policymaking contexts, and “a strong need is emerging for a more realistic assessment of the strengths and the weaknesses of various types of prospective analyses” (Havas et al., 2010). This is specifically true for the use of foresight in an STI policy context (compared to regional or corporate foresight), as it is one of the fastest growing fields of foresight use and thus makes up a major share of the foresight application cases, and as it is specifically used when “a more funda-mental rethinking of policies is needed” (Havas et al., 2010; see also Popper, Keenan, Miles, & But-ter, & Sainz, 2007 and Saritas et al., 2014). Thus, it is important to be aware of new methodological directions and of their strengths and weaknesses.

Still, the question remains as to what happens once we have an indicative overview of the current developments: how can we make sense of which of those approaches to use in what situation? Therefore, we also provide first indications for the potential use of the emerging approaches in an STI policymaking context, and such first indications are included as part of the discussion of future perspectives of the emerging approaches.

However, it has to be noted that all outcomes, due to the problematic publishing situation of newer approaches, remain at the status of indicative first insights. To verify where exactly developments are going, a more thorough research will be needed and may only be possible after a considerable time lag of having these approaches entering traditional documentation within peer-reviewed jour-nals and formal project reports. But the precise aim of the reflection here is to shed some light onto recent developments while they are happening, in order to enable a more informed reflection in the community and among policymakers in terms of what we see changing now and what this might imply for future directions of foresight practice.

1.2. Structure of the Paper

In chapters 2.1 and 2.2, the paper outlines the major approaches and sources of insight used, which are informal expert consultations in the preparatory stage, a workshop with experts from the field at the European conference on forward-looking technology analyses, and an international expert

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survey and expert interviews as well as literature research. Chapter 2.3 gives further details on the emerging clusters of “new” approaches in foresight that were identified from the research,via a descriptive overview of project examples and the existing insights on strength and weaknesses. Chapter 3 reflects on potential future developments with respect to further use in specific phases of foresight processes, specifically its use in STI policy. Chapter 4 summarizes the main conclusions and indicates directions for further research.

2. SURVEY AND EXPERT INTERVIEWS - APPROACH AND MAJOR OUTCOMES

2.1. Methodology

For answering the question of which directions of methodological development are currently be-ing seen in the field, an international expert survey was used as the core of the research, supported by literature research and additional expert consultation. The inputs used for generating the survey (e.g. the list of approaches that was used in the survey and discussed in the expert interviews) were generated in four steps1 :

1. Literature analyses on “new” approaches2. An informal collection of expert input via the Association of Professional Futurists mailing

list 3. An interactive workshop on the topic at the European Commission JRCs FTA conference

2015, with 30 experts from the field2

4. Integrating the findings from literature search, expert inputs and the workshop into a provi-sional clustering of “new” approaches.

The survey and the expert interviews both aimed at generating, within a reasonable “first insights” paradigm, input from experts in foresight, on which approaches have grown in importance in fore-sight in the last years, and how they might develop in the future.

Approximately, 600 experts were invited personally or via the respective mailing lists of bodies that bring together knowledgeable practitioners and academics, such as the Millennium Project’s Plan-ning Committee and the Association of Professional Futurists. In the end, 104 experts answered to the survey. For the ten expert interviews, the initial set of experts was selected from the European Forward-Looking Technology Analysis Scientific Committee, identifying those members who have the necessary overview of methodology development globally (e.g., have applied at least two of the

1 The clusters identified here draw from mix of review of existing information, expert consultations and the workshop mentioned, and resulted in an overview of emerging approaches clusters that as such did not exist before. A first classification was developed by the authors via the first two steps mentioned, and then “tested” and refined with the participants oft he workshop at the FTA conference. The survey confirmed the clustering and led to only one major change, in the naming oft he “experiential foresight” cluster.

2 These were practitioners in the field mainly from Europe and with an academic background. The main results of the workshop are documented at http://lib.fo.am/future_fabulators/new_approaches_ and_needs_ in_ foresight#foresight_2030.

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identified clusters of “new” approaches and have the respective international experience) and then enlarged via a co-reference system.3 Interviews were conducted in a structured format, but allowed for an open discussion at the end to reflect on findings and conclusions that could so far be gener-ated. Thus, the research outcomes presented here are of course dependent on the insights of the experts involved, and might thus be prone to specific biases. However, as the participation was tar-geted to be and successfully realized as varied in terms of organizational and regional background, and more fully-fledged research bases via a larger panel for the survey and a systematic analyses of publications and projects globally were not possible in the time available for research, we assume that this still provides a solid basis for first insights for the objective of a structured, if not detailed overview.

2.1.1. Composition of Participants Overall, 611 invitation were emailed out in January and February 2015, with a second email re-minder after the initial email. The survey stayed open until February 10th, 2015. 104 participants completed the survey entirely. Furthermore, 625 qualitative comments were left in the survey. The eighty-one participants who gave details on their country of residence came from thirty-three coun-tries, with the majority of responses from Europe (40%), Asia (29%, with 20% of all participants from East Asia), North America (26%) and a smaller share from Australia, South America, and Af-rica.

FIGURE 1. Survey Participants’ Country of Residence

Origin of participants

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Seventy-four participants gave information on their institutional background, with the majority of responses coming from participants from the consulting/private sector foresight (28%) and the aca-demic sector (26%) and a smaller share from policy/government and NGOs.

FIGURE 2. Institutional affiliation of participants

3 The expert interviews were conducted with: Per Dannemand Andersen, Professor/Head of Division Technology and Innovation Management, DTU Management Engineering, Denmark; Stuart Candy, Assistant Professor, Strategic Foresight& Innovation, Facultyof Design at OCAD University, Canada; Dr. Kerstin Cuhls, Competence Center Foresight, Fraunhofer Institute for Systems and Innovation Research ISI, Germany; Andrew Curry, Director, The Futures Company, UK; Dr. Zhouying Jin, Director, Center for Technology Innovation and Strategy Studies, Chinese Academy of Social Sciences; Aaron Maniam, Director, Industry Division at Ministry of Trade and Industry, Singapore; Ariel Muller, Director Asia-Pacific, Head of Futures Centre, forum for the future, Singapore; Jongchae Oh, Future Researcher, Principal Engineer, Samsung SDS, Rep. Korea; Byeongwon Park, PhD/Research Fellow, Center for Strategic Foresight/Team Leader, STEPI (Science and Technology Policy Institute), Rep. Korea; Kuniko Uruashima, Ph. D., Deputy Director, Science and Technology Foresight Centre, National Institute of Science and Technology Policy (NISTEP), Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan. The authors would like to thank these experts for their time and invaluable input.

2.2. Overview of Major Outcomes

In the following, we will summarize aggregated findings from all four sources of input (literature search with informal expert consultation, workshop at the EU-FTA conference, survey, and expert interviews), focusing on the outputs of the survey and adding in additional information from the other sources where applicable.

2.2.1. Identification of Clusters of “New” Approaches or Emerging PracticesThe EU conference workshop, literature search and informal expert consultations produced a draft

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of four clusters of “new” approaches in foresight, which were then used as a basis for the expert survey:

1. Integrated qualitative-quantitative approaches,2. IT-based/“automated” foresight,3. New forms of communication and interaction: visualization, gaming, design fiction (later

called “experiential foresight,” due to the feedback in the survey and the interviews)4. Open and crowd-sourced foresight.

The participants of the survey broadly confirmed the four clusters of new approaches that were sug-gested as being recognized as gaining in importance in foresight: 82% seeing “new forms of com-munication in foresight” being used more, 80% confirming this development for open and crowd-sourced foresight, 73% for integrated quantitative and qualitative approaches, and 71% for IT-based and automated approaches (with the highest share for being used “a lot more”).4 Only in the case of the cluster “new forms of communication” the name was changed to “Experiential foresight,” as this proved to be clearer as an umbrella term for these approaches that are at least partially estab-lished (see Raford, 2012).

The survey also showed that, even if we used the term “new” approaches with the stress of the quo-tation marks already highlighting that “new” is to be regarded as a relative concept here—and that for all of these approaches, precursors of comparable and related practice clearly exist—the use of the term “new” still led to a number of misconceptions and arguments about whether approaches were really “totally new” or not.5 Thus, we decided to shift the terminology in the course of the research towards the term “emerging practices” and “emerging approaches clusters,” which seems more helpful in focusing the discussion on the center of the research: approaches that are gaining in importance and use, despite how they may have been practiced before and have foundations and precursors.6

4 Some comments (less than five in number) suggested other types of clusters, for example, separating “Open and Crowd-sourced” or differentiating further between different types of IT-based and automated foresight. However, we decided to remain with the clusters in general as they had proven overall to be helpful in demonstrating and communicating rough directions of emerging practices that have gained in importance in recent years, and were confirmed by the large majority of experts.

5 While the new approaches mentioned in the comments were included in the research through the descriptive overview of project examples where sources could be identified, there were also a number of mentioned approaches that were not included here as they can be regarded as rather established “traditional” approaches at this time (e.g., scenarios, wild cards and weak signals or roadmapping).

6 An analysis of the historic developments and roots of these approaches and their development over time would of course provide further insight, but could not be realized within the time available for research.

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FIGURE 3. Approaches with Increasing Use in the Last Decade

The survey also highlighted three clusters of drivers of the developments, based mainly on the out-come of the discussion in the EU-FTA workshop. Here, “Changes in the demand side” was regarded by 85% of answers as a driver, and “Research insights on weaknesses in traditional approaches” by 85% as such. Technological change was regarded as the clearest and strongest driver: 94% seeing it as a driver and 40% as a very strong driver, thus being the highest share by far in this category. The comments in this case also pointed very much in this direction, with many participants stressing that the strongest change in the field from their perspective comes from new possibilities as enabled by IT, big data, and smart algorithms.

FIGURE 4. Key Drivers of “New” Approaches

was not used more in the last 5/10 years was used a little bit more in the last 5/10 years

was used regularly in the last 5/10 years was used a lot more in the last 5/10 years

was clearly used more in the last 5/10 years

I don´t know

not a critical driver for "new" approaches in foresightclearly a driver for "new" approaches in foresighta very strong driver for "new" approaches in foresight

somewhat a driver for "new" approaches in foresightstrongly a driver for "new" approaches in foresightI don´t know

Research insights on weaknesses in traditional approaches

Technological change that enabled new approaches (big data, social media, automated information gathering and scanning…)

Changes in demand (e.g., foresight “users” needing more tangible outcomes)

7.8%

10.6%

12.5%

14.8%

4.6%

8.1%

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In terms of their future development, all of the identified clusters of approaches were expected to be used more with only small differences between the different clusters: 94% expect growth for new forms of communication and open and crowd-sourced foresight, 84% for integrated qualitative and quantitative approaches, and 87% for IT-based and automated foresight.

FIGURE 5. Expectations of Development in the Next Decade

Concerning the relevance of the approaches for STI policy, all of the identified clusters of ap-proaches are regarded as important for STI to some extent, again with only small differences be-tween the different clusters: 97% say so for open and crowd-sourced foresight, 92% for new forms of communication, 89% for integrated qualitative and quantitative approaches, and 87% for IT-based and automated foresight. If we only look at the answers that see the respective cluster as clearly/strongly/or very strongly important for STI policy, the picture shifts slightly towards new forms of communication in the top position with 82%, followed by open and crowd-sourced with 80%, integrated qualitative and quantitative with 79%, and IT-based/automated foresight with 67%.

will not be used more in the next 10 years will be used a little bit more in the next 10 years

will clearly be used more in the next 10 years will be used regularly in the next 10 years

will be used a lot more in the next 10 years I don´t know

New forms of communication in foresight (Storytelling/Visualization/Gaming, ...)

Open and Crowdsourced Foresight

Integrated qualitative-quantitative approaches

IT-based/“automated” foresight

7.5%

7.6%

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is not important for STI policy is somehow important for STI Policy is clearly important for STI Policy

is strongly important for STI Policy is very strongly important for STI Policy I don´t know

New forms of communication in foresight (Storytelling/Visualization/Gaming, ...)

Open and Crowdsourced Foresight

Integrated qualitative-quantitative approaches

IT-based/“automated” foresight

Approaches especially important for increasing use in STI-policy

FIGURE 6. Relevance of Approaches for Use in STI Policy

2.3. A Descriptive Overview of Project Examples in the Clusters of Emerging Practices In the following we give further details and examples of respective projects of the clusters of emerging approaches in foresight that were identified from the research without aiming to be ex-haustive.7 The table below summarizes how the foresight project examples used in the following are attributed to the clusters, and provides further information on which aspect of the respective cluster is relevant. In attributing the examples to the clusters, we used the dominant feature of the project as the attributing category. 8

7 The examples described in the following were chosen according to the criteria of providing a wide overview of existing practices, and include insights from overviews of approaches that have been produced for different areas of emerging practice. The examples stem from the literature search and/or have been mentioned in the expert survey by at least three participants as relevant examples, and/or were recommended by the experts in the expert interviews.

8 This means that some project examples could theoretically be attributed to several clusters. However, we see the clusters as mutually exclusive because we define the attribution to a category as dependent on the dominant feature of a project (i.e. the feature without which the project would not be possible). Following the definition, the GFIS (The Millennium Project’s Global Futures Intelligence System) for example is characterized as an IT-based approach. This is the case because without its IT-based platform, the project would not be possible. Even though it is somehow also open (by including a large variety of inputs from different stakeholders), the project as such is not feasible without its IT-based platform, but it could be realized without the characteristic of full openness.

6.3%

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Project Example Approach Type Characteristics of Emerging Approaches

Integrated Qualitative-Quantitative

Experiential(includes Visualization

(Vis), Games (G), Design Fiction (Des)

Elements)

Open (O)/

Crowd-sourced (CS)

IT-based or “automated”

(includes IT-based (IT), “automated” (Aut),

web-based elements (Web)

DEFRA: Future of Waste Scenarios (same process also for use in companies)

Combined qualitative-quantitative scenarios X

Investigative research process with systemic modeling in strategy process (Hadjis)

Combined systemic modeling and qualitative research

X

Integrated Regional Modeling

Integrated numerical modeling and participative scenario analysis in sustainability research

X

Emission-Free Transport in Cities 2050

Integrating system dynamics modeling with “traditional” foresight methods (visioning) and impact assessment

X

Global Futures Intelligence System, The Millennium Project

Large scale open scanning/collaborative intelligence platform

X (Web, IT)

Shaping Tomorrow, Extractor Tool

Automated Scanning and Text Extraction Tool X (IT, AUT)

Future of Facebook Independent web-based open foresight project bridging scenario tools, expert and public views

X (O, CS)

Singapore 2065 (ongoing) Social innovation foresight project, with face-to-face workshops

X (O, CS)

BBVA Vision 2030 Open Innovation Foresight project X (O)

Future Agenda, Phase 1 and 2 (ongoing)

Workshop-based large scale foresight process X (O)

FutureScaper/Climate Change Project

Crowds-sourced engagement and analysis tool for foresight X (CS)

IFTF foresight engine, numerous examples, here SmartGrid 2025

Interactive foresight gaming platform employing a card-like interface

X (CS)

Sensemaker, Financial Uncertainty Project

Open auto-aggregation tool, using crowd-sourced narrative fragments

X (CS)

Wikistrat Open online platform for geostrategy forecasting X (CS)

TABLE 1. Project Examples and Attribution to the Clusters Identified

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Project Example Approach Type Characteristics of Emerging Approaches

Integrated Qualitative-Quantitative

Experiential(includes Visualization

(Vis), Games (G), Design Fiction (Des)

Elements)

Open (O)/

Crowd-sourced (CS)

IT-based or “automated”

(includes IT-based (IT), “automated” (Aut),

web-based elements (Web)

Future of Money Crowd-funded TV series, Visualization in online video format

X (Vis)

Fly me to the Moon aka Dinner with Friends

Visualization of potential future in online video

X (Vis)

DHL 2030 Visualization of Scenarios in online scenario videos

X (Vis)

UKCES Future of Work Visualized scenarios with vignettes and online-based quiz, social media strategy

X (Vis, G)

Museum of Future Government Services

Museum of Potential FuturesX (Vis, Des)

Prehearsals, Example Food Futures Project

Enacted/“prehearsed” scenarios with design fiction elements

X (G, Des)

The Thing from the Future Imagination game to describe objects from a range of alternative futures

X (G, Des)

Foresight Cards Card-based game with driving forces cards and materials for 3 workshops (“create awareness,”“stress test business models,”“determine key uncertainties for scenario planning”)

X (G)

M VIP Cards Card-based game for rapid future scenario development on the topic of sustainable mobility

X (G)

Playbook for Strategic Foresight and Innovation

Tools for fictional “Future User” profiles, “Futuretelling” (scenes from the future enacted as a performance), or paper mock-ups of future products

X (G, Des)

RILAO Remote Viewing Protocol

Collaborative world-building game to create a future world

X (G, Des)

World System Model Game

Participative learning game on futures topics based on the “world problématique” model

X (G)

PRISM Singapore Scenarios from participative process interpreted into different visualization and artistic forms for a public immersive arts experience

X (Vis, Des)

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2.3.1. Integrated Qualitative-quantitative ApproachesThis cluster of approaches was the most debatedsince the start of the research. Here, it is most clear that the inclusion in the group of approaches that have gained in importance in recent years is exact-ly about this aspect—the integration of both paradigms having gained importance—and bringing about first signs of a paradigm shift of “bridging the gap between numbers and narratives,” an ex-pression used by a specifically set-up expert group at the EU-level in the framework of COST A 22 actions.9 In the comments and expert interviews, the input from experts can be largely categorized into two reactions:

a) A minority claims this development is non-existent (12.5% in the survey said these approach-es were not used anymore), most of them with a normative twist (visible via the comment section) stressing that the development should not exist because foresight has to be qualita-tive.10

b) The majority of comments state that there have been traditions of both qualitative and quan-titative approaches in foresight for a long time, and that the new development in the last de-cade is really about bridging the two sides of the practitioner/expert community, and what we see now is the true integration of these two “worlds.”

Of course, while a major share of futures-related work labeled as foresight seems to be qualitative (see Popper et al., 2007), there have been longstanding traditions of quantification within the fore-sight or wider futures-oriented research arena, first and foremost in the forecasting tradition. While there is no formal, established agreement yet on the difference between foresight and forecasting, in practice the difference to most experts and experienced practitioners is clear, even if boundaries are even more blurry in application than in theory (Cuhls, 2003). Cuhls reflects on the following concerning the difference between foresight and forecasting: “Major differences between foresight and forecasting are that in forecasting, (1) the broad area to be forecast has to be known at the start and (2) conclusions for the present, e.g. for specific activities, may be missing” (Cuhls, 2003, p. 108). She also adds in an overview of attributes in forecasting and foresight that the former is “more quantitative than qualitative” and the latter “more qualitative than quantitative” (Cuhls, 2003). Based on this differentiation, it is clearer that it makes sense to describe the increasing integration of qualitative and quantitative approaches as a recent development when the lines of “more qualita-tive than quantitative” or “more qualitative than qualitative” in both communities seem to be mov-ing, at least according to the experts, towards a stronger integration of the other approach.

What is meant by this change becomes clearer when we look at exemplary projects. In reflections on the increasing integration of qualitative and quantitative, it has been argued that this integration can enable a more holistic view, and also address better the needs of decision-makers. One project

9 See Haegemann, Scapolo, Ricci, Marinelli, & Sokolov (2011) for an overview of the efforts and debate in the community so far. They also mention strategic design, social network analysis, social scanning, and prediction markets as promising futures fields in integrated qualitative-quantitative approaches.

10 Haegemann et al. (2011) provide a useful reflection on barriers for the increasing integration of qualitative and quantitative approaches. They also diagnose an “emerging consensus which calls for the need to integrate both dimensions.”

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referred to in this respect is “Emission-Free Transport in Cities 2050” (Ahlquvistet, Nieminen, Auvinen, Tuominen, & Oksanen, 2013; Nieminen, Ahlqvist, Tuominen, & Auvinen, 2012), which brings together system dynamics modeling with “traditional” foresight methods (visioning) and impact assessment. The authors argue that such new methods are needed in order to deal with “the increasing complexity of socio-technical environments,” requiring:

• “Methods which strengthen horizontal approaches,”• “Steering mechanisms which are adaptive and able to respond to the rapidly changing situa-

tions,”• “Approaches which support strategic thinking and interlink activities with a view of strategic

management” (Nieminen et al., 2012). Ahlquvist (2013) later concludes that the advantage of the approach is

that it is able to concretely assess the consequences of various policy actions (including the more systematic possibility to map the intended and unintended consequences of the poli-cies), define various paths to desired societal vision, and assess the usability of various pol-icy measures in the context of specific socio-technical change... The case of emission free transport indicates concretely, how an optimal mix of various policy measures may support change towards desired vision in a complex socio-technical environment, and how various possible paths towards vision can be defined. (Ahlqvist et al., 2013)

In an article on the increasing use of qualitative-quantitative scenarios in corporate foresight, an approach which was also demonstrated in the public sector for an STI project with DEFRA’s “fu-ture of waste scenarios” (DEFRA, 2011), Hirsch Burgraf and Daheim (2013) argue that this ap-proach—when integrating systemic modeling with a participative, key-factor-based qualitative scenario methodology—can deepen insight into potential disruptions and systemic interconnection, allow for insight into potential developments paths and their consequences for respective actions (thus creating a better link to strategy processes), and generally connecting better to the mindset of decision-makers, thus creating stronger impact (however also stressing that any report with numeri-cal data has a risk to be limited to the numbers perspective, in the worst case to an unintended pre-dictive perspective. The case of the DEFRA waste scenarios also illustrates how these approaches answer to very concrete needs in decision-making: here, a “traditional” (participative, consistency- and key-factor-based) scenario methodology was integrated with a model (encompassing waste volumes and treatment) that builds on and connects with the narrative and qualitative scenarios. The project was specifically created to feed into the 2010 Waste Policy Review that needed to en-compass perspectives of alternative policy developments, but also had to relate to specific impacts that can be expressed numerically, such as consequences for CO2 emissions. The project was suc-cessful in bringing together the two perspectives of previously existing insights from research and the respective experts from the qualitative and quantitative side on waste issues, in a policy field where it had not been possible to connect these perspectives in alternative scenarios to support poli-cymaking (DEFRA, 2011).

Hadjis (2008), illustrating a case of integrating modeling within a software company’s strategy pro-cess in what they call an “investigative research process” based on system dynamics, also comes

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to the conclusion that these approaches play an increasing role as they enable “a more dynamic approach” and continuous and rapid change requires more than a single analyst’s capacity or the traditional and rather static planning processes in dealing with complex changes. Furthermore, in sustainability research, an integrated approach of numerical modeling, scenario analysis, and par-ticipative approaches has even been described as becoming common (Walz, Lardelli, Behrendt, Grêt-Regamey, Lundström, Kytzia, & Bebi, 2007; see also Döll, 2004). It is striking that all these examples highlight the use of an integrated qualitative-quantitative approach as better dealing with complexity, and stress that it connects better to reality and the needs of the decision-making pro-cesses.

The UK innovation agency NESTA comes to a comparable conclusion in their analysis of emerging quantitative approaches, stressing their analysis suggests the most promising methods are

Those that allow the analysis to explore states of ignorance... These exercises are not ca-pable of predicting instances of outcomes, but they help explore the future in a conditional manner, acknowledging the incompleteness of knowledge… We suggest that these types of agent modeling and scenario modeling are the ones that can make a more positive contribu-tion to policy-oriented FTA—by avoiding narrow prediction and allowing plural exploration of future technologies. (Ciarliet, Coad, & Rafols, 2013, p. 29)

2.3.2. IT-based and “Automated” ForesightMany players from IT-based industries have moved and publicized strongly in the last years the potentials of increasing computing power, cloud-based technologies, and semantic analysis for making sense of the future. Famous examples are the Microsoft Prediction Engine and Lab, the cooperation between IBM and Twitter for Watson’s predictive capacities, or the “predictive model-ing” services by Kaggle. While none of these examples claims to be or can be regarded as foresight, taken together they show the speed of the development of the underlying drivers. One might also wonder whether players from outside the traditional foresight community are actually taking over this realm of IT-based foresight. But examples from the foresight field exist as well.11 The Millen-nium Project, a global NGO and think tank on future issues, has switched its own research and com-munication base to a system called “Global Futures Intelligence System” and opened it up to other contributors and users from outside the Millennium Project as such. It stresses that this is “not just new software, vast information, and global experts; it is also a system to produce synergies among these three elements for greater intelligence than their separate values. It is rather a global intel-ligence utility from which governments, UN agencies, businesses, NGOs, universities, media, and consultants can draw different values. The GFIS staff is more interested in synergistic intelligence than competitive intelligence, and how the world can work for all, not just for a single nation, ideol-ogy, or issue. It can provide decision makers, advisors, and educators with insights that reflect the consensus and/or range of views on the important issues of our time. The engagement of the user

11 See specifically the Special Issue of Technological Forecasting and Social Change on Foresight support systems: The future of ICT for foresight, from August 2014.

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with our information, participants, and software is intended to help humanity become more proac-tive” (Millennium Project, 2015). Structured along the project’s long-tracked fifteen global chal-lenges, GFIS enables shared information tracking and scanning, but also communication between contributors, and defines “collective intelligence” as an emergent property from synergies among: 1) data, info, knowledge, intelligence, and wisdom; 2) software and hardware; and 3) experts and others with insight that continually learns from feedback to produce timely knowledge for better decisions than these elements acting alone (Millennium Project, 2015). As it is made clear from its description, its idea and long-term goal is to utilize the technology behind the tool, software, and platform to provide more transparent insightinto global debates on futures issues for a larger group of users as well as to create more proactivity towards the future.

Shaping Tomorrow, a web-based service providing access to information on trends and future de-velopments, has also recently demonstrated a new approach in utilizing IT further for its scanning. It works with an “extractor software,” a tool created to help in the collection and structuring of in-formation on the future, or as

a software service which works invisibly in the background and helps the user in two ways: it extracts metadata like publication date, author, source, country, region, keywords auto-matically from the input URL and adds it to the insight... It gives suggestions to the user about which parts of the texts are relevant for the future. (Kehl, 2013)

The tool thus helps to more quickly gather information and enter it into a structured database, claiming it halves the time effort and “increases the quality and consistency of human tagging” (Kehl, 2013). It is clear (and stressed by the team from Shaping Tomorrow) that the tool does not fully automate the scanning process, but aims to make it less time-intensive by assisting in it. This focus on the benefit of time and effort being reduced in certain tasks is also visible in other forms of IT-based approaches that are described in the next section of crowd-based approaches, as they also focus on bringing in input from a large number of contributors.

2.3.3. Open and Crowd-sourced ForesightAlready in 2008, there were claims of foresight becoming more open in the sense of including a wider view of participants, of extending beyond the traditional groups of experts who are included in creating perspectives of the future (Daheim & Uerz, 2008). Several projects in recent years clear-ly illustrate this shift, a well-known one being “The Future of Facebook,” an independent project that brought together expert views and public insight from a wide range of contributors through an online-based process. It defines open foresight as a process for analyzing complex issues in an open and collaborative way, and to raise the bar on public discourse and forward-focused critical think-ing. It draws on well-established methodologies from the Futures Studies field, principles from design thinking, and visual communication tools to create a framework for building forecasts and scenarios (Future of Facebook, 2011). The project resulted in a series of six videos that explore the impact of social technologies, worked under a creative commons license, and brought about a wide discussion through numerous channels such as Facebook, Twitter, Youtube, and Quora.

The on-going project “Singapore 2065” also uses technology to enable an open foresight process.

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The project by the Thought Collective, a group of social enterprisesin collaboration with the Minis-try of Culture, Community and Youth, is “an inaugural 3P platform for the exchange of ideas on the envisioning of Singapore's communities and spaces for the future” that crowd-sources visions for shared spaces—having for example produced visions for a living museum and office-worker sanc-tuaries in the city center—through online-based and face-to-face communication and workshops (Forum for the Future, 2015; Thought Collective, 2015).

Further examples of projects that have attributed themselves to the open foresight or open innova-tion and foresight category include the BBVA Vision 2025 (BBVA 2012) project or the completed first and on-going second round of “Future Agenda”. The latter, aiming to open up the dialogue in its current round more towards younger generations and increasing its social network use, currently has what is probably the widest reach in terms of globally realized interactions within a consistent continuous interaction-based dialogue format, planning 100 workshops with 2000 organizations in 2015, and having engaged with over 50,000 people from more than 145 countries in the first round including online interactions (Future Agenda, 2015).

With respect to crowd-sourced approaches, this is one of the few areas that have seen formal analy-sis. Raford has analyzed how foresight support systems or online approaches that work with a large set of input impact on specific attributes of a scenario-planning process, using data from five em-pirical case studies (Raford, 2015). The case of a “traditional,” non-crowd-sourced scenario process on the Future of a Northern Spanish Region is contrasted with:

1) a project on the impact of climate change on the UK government, realized with the tool Fu-turescaper;

2) a project on the impact of financial uncertainty on government public services with the Sen-seMaker platform;

3) a project on “Smart Grid 2025” using the Institute for the Future’s foresight engine (this an interactive gaming platform employing a card-like interface, which has been used for numer-ous projects, the latest being an ongoing game on black swans);

4) the online platform Wikistrat, focusing on geo-strategy forecasting (a service by a for-profit consultancy);

5) the Future of Facebook Open Foresight Project (see description in the section above).

Raford analyses the impacts of the online-based approaches on key aspects of the scenario process, such as number, type, and geographic scope of participants involved, number of variables and opin-ions collected, the time spent on data collection and analysis, and the amount of user debate and re-flection. Among other findings, he concludes that a significant increase in participation (in terms of absolute number of participants involved, their geographical distribution, and their disciplines and areas of expertise) can be shown. However, the nature of participation was “in most instances fairly limited” and focused on the early stages of the scenario process. He also found that in terms of the methods for clustering and ranking data, two cases with approaches such as auto-aggregation for easier clustering demonstrated “new mechanisms for analysis and exploration that helped to more effectively leverage the existing time available” (Raford, 2015). Also, costs for the online-based ap

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proaches can be assumed to be clearly less costly than traditional approaches. But the most marked difference wasin the depth and type of socialization, which took place mainly in limited online-based forms. He stresses specifically that “the different kind and level of social intensity produced by the online cases… suggests that they are not, at present, capable of achieving the stated emotion-al and social goals sought after in the best scenario workshops” (Raford, 2015). In his conclusion on future perspectives of these approaches, he suggests that “a hybrid form of online and face-to-face engagement could be developed that would leverage the benefits of both virtual and in-person collaboration more effectively” (Raford, 2015).

2.3.4. Experiential Foresight: Emerging Communication, Engagement and Interaction Formats Including Visualization, Gaming and Design FictionThe cluster of those approaches embraced here under the label “Experiential foresight” seems to be the one where most examples of such projects are known and documented. We will focus in the following on examples that stem from different backgrounds and motivations to demonstrate the breadth of these approaches. The cluster here embraces approaches that either work with “new” formats of visualization and communication (e.g., videos or quizzes) that have not been tradition-ally used a lot in foresight with its report dominance, that employ design-fiction based approaches by for example creating or co-creating future artifacts, or that use gaming approaches.

The first group of emerging practices that became more widespread refers to the aspect of visualiza-tion. While storytelling in the written, narrative form has of course always been a well-established approach in foresight, these approaches go further and work with images or live-visualization in workshops or video. As for publicized futures-oriented studies, one might argue that this is by now a nearly standard approach (see the example of DHL; DHL, 2012), but it seems this now also be-comes a stronger tendency in research-based, public sector-funded foresight (for example, the use of images, cartons and movies in the Korean national foresight exercises Korea 2030; Park, 2005, or in the UK Commission for Employment and Skills “future of work” scenarios that used visual vignettes and a visualized online scenario quiz; UKCES, 2014). The use of video as an output for-mat to communicate scenarios has also been used by crowd-sourced foresight projects: Heather Schlegel’s Future of Money TV series was funded on Kickstarter, and her video “Fly me to the Moon a. k. a. Dinner with Friends” is a vivid example of new narrative forms used in online media now (Schlegel, 2011; 2013). In the video, a scenario that would in a traditional foresight project have been written up as a narrative story is enacted as a scene from around 2020, when cash is a frowned-upon anachronism. A group of friends share a dinner and then pay digitally, using a variety of new transaction forms enabling them to smoothly share the costs of a bottle of Merlot as well as tipping the waiter that enables him to realize his dream of space travel. The video, by “showing” instead of telling us what the future could look like, brings this scenario story to life. Another ex-ample of video use in a more “homemade,” clearly less costly format comes from a project from the open and crowd-sourced category, the “Future of Facebook” project videos that summarize online generated video input (Future of Facebook, 2011). While there is usually no formal documentation for these examples in terms of experiences with their impact, it became clear through expert inter-views that the benefits experienced were about increasing attention of a wider group in the public,

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and brought a different kind of reaction. Many interviewees mentioned that videos particularly lead to a more engaged, more enthusiastic reaction to futures content conveyed in this way, and that the motivation for using these tools stemmed from the aim to be less abstract, to “make the future real and tangible,” a motivation that also applies to design-fiction related foresight (Selin, 2014; Rijken-Klomp, Baerten, & Rossi, 2014).

The influence of gamification on foresight has also been discussed recently, referring to the increas-ing use of playful or gamified approaches in all kinds of workshops and professional settings (Wat-kins & Neef, 2013). While the term “gamification” describes “the use of game design elements in non-game contexts,” it is also related “to similar concepts such as serious games, serious gaming, playful interaction, and game-based technologies” (Deterding, Khaled, Nacke, & Dixon, 2011). In foresight, there are by now numerous gamified or playful futures workshop approaches, one being “The Thing from the Future” (from the Situation Lab by professors Stuart Candy and Jeff Watson), which is an imagination game that challenges players to collaboratively and competitively describe objects from a range of alternative futures (Situation Lab, 2014a). Also by the Situation Lab is the Rilao Remote Viewing Protocol (RRVP), a collaborative world-building game that was initially produced for and realized at the 2014 Science of Fiction conference in Los Angeles, and had over 300 participants create a whole future world—Rilao—within a day, working with a world-building system, time-travellers that introduce the future world, prompts, a card deck, and a set of rules to scaffold participants through a storytelling and creative process. A website collected the output of this process in real-time, enabling participants to watch live as the fictional world of Rilao emerged from their collective imagination (Situation Lab, 2014b)

The “World System Model” (Hodgson, 2015), initially a “mental model” of the “world probléma-tique,” has also been developed by the International Futures Forum into a participative learning game. The game can be played in a version of a couple of hours to a full day. It involves a number of topics and contexts such as the future of cities or public health policy, one example in 2014 the topic of Resilient Toronto with a team of academics and concerned citizens from the public services (Hodgson, 2015).

Other examples of card-game-based approaches include the “Foresight Cards” by IVTO, a re-search and education institute in the Netherlands, consisting of “125 external driving forces cards supported by high quality photos (25 per STEEP category)” and materials for running three work-shops (“create awareness,” “stress testing business models” and “determine key uncertainties for scenario planning”; IVTO, 2012). There is also the award-winning sustainability-oriented game “MVIP Cards” by Advanced Mobility Research and Graduate Industrial Design Programs from the Art Center College of Design in Pasadena, which supports “rapid future scenario development on the topic of sustainable mobility so that groups and individuals can quickly enter a dialog and brainstorm about possible outcomes, solutions and strategies” (MVIP, 2015). Along these lines of toolboxes that incorporate playful elements there is also the Playbook for Strategic Foresight and Innovation (Carleton, Cockayne, & Tahvanainen, 2013). Designed as a resource for the self-learner in organizations, it encompasses numerous tools and case studies, among them game-based

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approaches such as creating fictional “Future User” profiles and “Futuretelling” (scenes from the future enacted as a performance) or paper mock-ups of future products.

It is obvious from these examples that there is strong interaction between current trends in design, such as speculative design or critical design, and foresight, that strives to create what has been called “a profoundly engaging experience that goes beyond technical reports and PowerPoint pre-sentations towards a new level of engagement,” and it is debated whether a whole new “school” of futures work is developing on this basis (Raford, 2012; Rijkens-Klomp, 2014). All have in common that they stress the creation of a future fictional world going beyond a text-based scenario descrip-tion, but using fictional prototypes of future products or other artifacts. In this realm, a group called “Future Fabulators” from Belgium has developed a full approach called “prehearsals”, making it possible to “rehearse” a possible future. They emphasize

the merit of directly experiencing the present moment. While scenarios are valuable thought experiments about possible futures, it’s very hard to know what they will be like until we experience them in real life. Exploring these questions at FoAM we wondered how we could ‘rehearse’ a possible future before it came to pass. How we could experience living in differ-ent scenarios and observe our reactions to them (Gaffney & Kuzmanovic, 2015).

They have tested the approach in different contexts and conceptualized it into a “Prehearsal Pocket Guide.” An example of their work put to practice is the Food Futures project, which they call “a scenario building experiment and edible pre-enactment,” where futures techniques are used “to look at how the relationship between food, health and the environment might evolve in the future” (FoAM 2015). The first installment was realized as a tasting dinner at the Edinburgh Science fes-tival in April 2014, and the second installment as a reception at the opening of the Future Fictions exhibition at Z33 in Hasselt, Belgium. Four scenarios were translated into a series of respective dishes, and the respective events also worked with elements of storytelling and visualization.

In a related manner, IPS PRISM from 2012 in Singapore is an example of a project that started from a series of workshops with 140 leaders of different sectors to create alternative scenarios on the question: “How will we govern ourselves in 2022?” and then used the outcomes to engage with a wider public. The scenarios were interpreted into different visualization and artistic forms to offer the public a “peek into the future” through an immersive arts experience at the National Library Building, and the material was also available online. Members of the public were invited to view the Prism Scenarios in this manner and then asked to share their own stories about how they saw-governance unfolding over the next tenyears (Prism, 2015). The process was thus opened up and worked explicitly with what is being called immersive, experiential approaches; the process and its results are documented on their webpage including videos (Prism, 2015).

What is probably the largest and most impressive example so far in this field of immersive ap-proaches has been the “Museum of Future Government Services” by the UAE Prime Minister’s Office, launched at the Government Summit in Dubai in 2014, and realized again in 2015, aiming to “create images of the future explicitly designed to shift policy conversations and accelerate inno-vation” (Raford, 2014). In his review of the 2014 version, Raford (2014) summarizes that the Mu-

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seum provided “an immersive, interactive experience that explored the future of key government services. It did so by creating ‘diegetic prototypes’…. of working future services that participants could interact with and experience for themselves,” He mentions there was a strong impact on the national discourse and that several policy initiatives were launched as a direct result, and concludes that “taken as a whole, these design-based approaches suggest an alternative way of embodying future narratives that could become more popular, and perhaps, more influential, in policy framing” (Raford, 2014). While in the overall reflection on the use of experiential approaches so far—stress-ing that the more direct, personal, and powerful engagement dominates—there has also been note of “risk of producing visually rich, but analytically impoverished, outputs,” which, however, could be foregone by combinations with deeper research and analyses approaches (Raford, 2012).

3. FUTURE PERSPECTIVES OF THE EMERGING APPROACHES

3.1. Benefits and Problems of the Approaches

As the survey has shown, experts expect an increasing use of all four clusters of approaches in the next decade. Speculation on how exactly this will play out probably is a futile endeavor. How, where, and to what extent these approaches will be used are what practice will show, and whether this expected increase in their use will in fact turn out to be the case will surely depend on more demonstrative cases that make clear the benefits, integration with the established methodologies, and also the willingness of the community to work with approaches that are not in their established toolbox yet and might move some practitioners outside of their comfort zone. As we aim at provid-ing an overview of these new approaches for enabling a more informed and structured discussion, let us revisit what the described examples, reflections, and problems of the approaches show in a condensed form and in terms of their benefits. However, it has to be noted that only in the case of the comparison of cases by Raford can we draw from a systematic scholarly analysis of projects, while all other cases are more informally documented insights.

When drawing together the main points in terms of benefits and problems, they can be clustered into impacts on the insights generated as such (i.e., insights into the issues analyzed) and the meth-od of improvement, the impact of the project overall (meaning impacts achieved or actions generat-ed) and the connection to decision-making, aspects of cost and time, and the effect on participation. As for the problems mentioned, this encompasses for integrated qualitative-quantitative approaches the risk of output being reduced to numbers and the qualitative insights being overlooked or being pushed into the background, and the challenge of avoiding being narrowed to a predictive perspec-tive. However, for these approaches there is also already a reflection on how these problems can be dealt with and which approaches overcome the challenges named (see Ciarli et al., 2013; Hirsch et al., 2013). For the IT-based/“automated” approaches, the risk of perceived “overpromise” was mentioned in the workshop and the interviews, relating to the perception that insights can by now be “simply generated” while in fact output, as with all methodologies, can only be as good as input (referring to filters and algorithms used), and stressing that no case has yet been shown that does not

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still rely on the insights and sense-making skills of the researcher or analyst working with the data output. As for the open and crowd-sourced examples, problems encompass less deep, less continu-ous interaction (and resulting insights), lacking what Raford stresses as the merit of deep interaction and socialization of (good) traditional scenario workshops. However, this issue is already being dealt with by developing hybrid forms that combine benefits of traditional and crowd-sourced ap-proaches.

On the benefits side, we would like to highlight what is striking across the clusters: a wider, broader participation can be noted as a positive effect in the case of collective intelligence for the IT-based and automated cluster, and, of course, especially for the open and crowd-sourced approaches, speci-fied by Raford’s analyses of online foresight platforms as a significant increase in terms of absolute numbers, geographical distribution, and disciplines and areas of expertise. In terms of insights and method improvement, for integrated qualitative-quantitative approaches this encompasses being able to better deal with complexity or improved insights on systemic interactions and disruptions, which is also regarded as a benefit of IT-based foresight (for the collective intelligence example). Furthermore, there are a number of references to aspects of time needed and reactivity: they high-light the approaches as being more dynamic, more being able to react rapidly to changes, and stress timely knowledge production and real-time interaction or a more effective time use using aggrega-tion and automation tools (for IT-based and open and crowd-sourced approaches). Also, increased cost-effectiveness is mentioned for both IT-based and openand crowd-sourced approaches, and an improved impact and connection to decision-making for integrated qualitative-quantitative, IT-based (in the case of collective intelligence), and experiential approaches. Enabling a connection between experts’ views and contributions from a wider public is also mentioned for the two clusters “open and crowd-sourced” and “experiential” approaches.

TABLE 2. Benefits and Problems of the Emerging Approaches Clusters

Emerging Approaches

Cluster

Benefits named, referring to

Problems namedInsights Generated / Method improvement

Impact and Connection to Decision-Making

Cost and Time Participation

Combined qualitative-quantitative

- Deals better with complexity - Deepens insights on potential disruptions and systemic interconnection - Allows for insights on potential developments paths and their consequences for respective actions- “Adaptive“/more dynamic approach that can respond more rapidly to changes (in contrast to traditional static planning)

- Interlinks with a view of strategic management- Connects better to the mindsets of decisions- makers, thus creating stronger impacts- Can illustrate alternative paths and consequences of actions

- can respond more rapidly to changes in the environment

No information - Risk of outputs being reduced to numbers, qualitative insights “overlooked”- Has to clearly avoid avoiding narrow prediction and allowing plural exploration of future technologies

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Emerging Approaches

Cluster

Benefits named, referring to

Problems namedInsights Generated / Method improvement

Impact and Connection to Decision-Making

Cost and Time Participation

IT-based / “Automated”

- Collective intelligence: synergy between contributors, higher level insights, improved insights on systemic interactions and disruptions- Automated information extraction: Analyst is “freed” from tedious tasks - Automated information extraction: increases the quality and consistency of human tagging

- Collective intelligence: to connect research and policy perspective, bring them together

- More cost-effective- More time-effective- Collective intelligence to produce “just-in- time” knowledge and more real-time exchange between researchers and other users

- Global Futures Intelligence: wider (e-) participation

- “Overpromise“: No tool can yet replace the analyst – analytical work still needed- Only as good as the filters, algorithms etc. that are used to structure the data

Experiential - Games/Prehearsals: More “personal” insights, deeper engagement, merit of direct experience- Design Fiction: Interaction with potential future worlds/artifacts is possible and immediately triggered, creates stronger interaction and insights in reaction to those worlds

- Visualization: More attention and a more engaged, more enthusiastic reaction/ deeper engagement- Museum case: strong impact on the national discourse and policy initiatives launched as direct result

No information - For visualization, in terms of reach: increasing attention of a wider group in the public- Enables direct interaction and experience of “future worlds”- Enabling a connection between experts’ views and contributions from a wider public

- Risk of producing visually rich and engaging, but analytically impoverished results

Open and Crowd-sourced

- For scenario cases (Raford analyses): two cases with approaches such as auto- aggregation for easier clustering demonstrated useful new mechanisms for analysis and exploration- Open: Enables connection between/ connects expert views and insights from wider public- Open: “raises the bar” on public discourse and forward-focused critical thinking

No information - For scenario cases (Raford analyses): Less costly- For scenario cases (Raford analyses): for two cases more effectively leverage of the existing time available

- Open: Wide, broad (e-) participation- For scenario cases: significant increase in participation (in terms of absolute of numbers of participants involved, geographical distribution, disciplines and areas of expertise)- Enabling a connection between experts’ views and contributions from a wider public

- Can mean less deep, less continuous interaction- For scenario cases (Raford analyses): the nature of participation was “in most instances fairly limited” and focused on the early stages of the scenario process, lacking the deep interaction /socialization and respective insights of traditional scenario workshops. But promise seen in hybrid approaches.

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3.2. The Potential Use of Emerging Approaches in STI Policy Contexts

The overview of clusters of emerging approaches generated so far and the indications of their po-tential also leads to the question as to where and how these might be used more widely in the future of general foresight and in STI policy use specifically (as an example of a field where foresight has been established strongly as a tool). In the following, we draw from two models of distinguishing phases in foresight in general and STI policy projects specifically: the model from the Association of Professional Futurists and a model that was originally developed by Aguirre-Bastos and Weber for developing economies for STI foresight processes. Due to its clear and transferable nature, this model serves our purpose well for clarifying simply first indications of the potential use of the emerging approaches in different phases in STI foresight projects (Aguirre-Bastos & Weber, 2014; APF, 2015). In this STI foresight process model, Phase 1 “positioning” is concerned with STI sys-tem and policy diagnosis and current trends, while Phase 2 “strategic/future intelligence” deals with a system’s exploratory scenarios. Phase 3 concentrates on “key focal issues” around key technolo-gies and social and other challenges or sectors, while Phase 4 “visions and roadmapping” develops a vision for the future in the sense of a success scenario. Finally, Phase 5 creates a set of future-oriented agreements with stakeholders and leads to policy implementation (see Aguirre-Bastos & Weber, 2014, for further details; the full model also includes the parallel policy-level phases).

TABLE 3. Potential Use of Emerging Approaches in STI Foresight Process Phases12

12 While we focus only on the application in STI, we have noted similar general foresight project phases in the table below to demonstrate how the same conclusions could be drawn on this level.

Emerging Approaches Cluster

Potential Use in Foresight Project Phases

STI Policy Foresight Process Phases

1) Positioning2) Strategic /

FutureIntelligence

3) Key Focal Issues

4) Visions andRoadmapping

5) Future-oriented

Agreements

General Foresight Process Phases

1) Framing 2) Scanning 3) Describing 4) Visioning 5) Planning

Integrated qualitative-quantitative

X X X

IT-based/“automated”

X X X

Experiential X X X X

Open and crowd-sourced

X X X X

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As a first indication of where potential use of the emerging approaches could be promising in STI foresight processes, based on the insights on benefits from the projects overview in the previous chapter, one can draw several conclusions:

• An integrated qualitative-quantitative approach could contribute particularly in phases 2, 3 and 4 in improving system understanding in terms of potential disruptions and interactions of factors from a systemic view, and in an improved understanding of potential policy measures’ impact on the system.

• IT-based and “automated” foresight is promising especially for the first three phases with their strong information gathering and analysis elements, as well as their increased effectiveness and improved insights in scanning.

• Experiential foresight approaches may play less of a role in the first phase of positioning where the system’s status quo is analyzed, but could bring in substantial benefits in all participative elements in the later phases, especially for bringing together experts’ views and wider public participation as well as for the integration of policymakers into the process. Another poten-tial use can also be imagined for the last phase of reaching agreements with stakeholders on future-oriented action, where these agreements are enabled through immersive and co-created future visions.

• Open and crowd-sourced approaches potentially play a strong role in phases 1 to 4 in increas-ing the degree of participation and input in all stages that are concerned with understanding the system, current trends, and creating future visions. This is less so for the last stage of creating future-oriented agreements with stakeholders. As this last step relies strongly on personal face-to-face interaction, an application here is at most possible in a hybrid format (for example, pre-paring agreements by collecting wider views in crowd-based formats but then finalizing them in smaller face to face interactions).

4. CONCLUSION

We started from the observation that there is considerable uncertainty about current directions in foresight methodology development, which is further exacerbated by the usual time lag between changes in practice and scholarly publication, documentation, and reflection. Thus, the research presented here aims to provide a structured overview of the changes visible in the field, backed by the view of experts on current developments, and thereby further the debate on the future direction of methodological development in foresight.

On the basis of the research input outlined, we can conclude that there is a strongly shared view amongthe experts in terms of the identified four clusters of emerging practices: Integrated qualita-tive-quantitative approaches, IT-based and “automated” foresight, open and crowd-sourced fore-sight, and experiential foresight (emerging communication, engagement and interaction formats including visualization, gaming, and design fiction).

Thus, while the paper provides in no way a full overview, we demonstrate a first tableau of clusters

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with the respective project examples. First insights in benefits and problems related to the respec-tive approaches can also be summarized. Some issues are as follows:

• For integrated qualitative-quantitative approaches there is a risk of output being reduced to numbers and qualitative insights being overlooked or being pushed into the background, and the challenge is to avoid being narrowed into a predictive perspective.

• For the IT-based and “automated” approaches: the risk of perceived “overpromise” relating to the perception that insights can by now be “simply generated.”

• For open and crowd-sourced approaches: less deep, less continuous interaction (and resultin-ginsights), lacking the deep interaction and socialization of traditional scenario workshops.

• For experiential foresight: A risk of a lack of deep insight and analysis.

However, in most cases suggestions for how these challenges can be dealt with exist as well. On the benefits side, some recurring themes were striking:

• A wider, broader participation can be noted for the IT-based and automated, and for the open and crowd-sourced approaches.

• In terms of insight and method improvement, for integrated qualitative-quantitative approach-es this includes being better able to deal with complexity and improved insight into systemic interactions and disruptions, which is also regarded as a benefit of IT-based approaches.

• There are a number of references to aspects of time needed and reactivity: they highlight the approaches as being more dynamic, more being able to react rapidly to changes, stress timely knowledge production and real-time interaction, and more effective time-use. Also, higher cost-effectiveness is mentioned for two approaches.

• Improved impact and connection to decision-making is identified for three approaches, and en-abling connection between experts’ views and contributions from a wider public is mentioned for two clusters.

Furthermore, some first conclusions can be drawn for the further use of the identified emerging practices in different phases of the STI foresight processes:

• Integrated qualitative-quantitative could contribute particularly in phases 2, 3 and 4• IT-based and “automated” foresight holds promise especially for the first three phases • Experiential foresight approaches could bring in substantial benefits at least in all participative elements in the later phases 2 to 5

• Open and crowd-sourced approaches potentially play a strong role in phases 1 to 4

In terms of further analysis, there are many clear directions for promising research. It would be worthwhile to investigate whether there is a difference in the use of existing and emerging ap-proaches for different contexts, in other words for different types of project questions and aims, or between different regions, nations, or organizations with different cultures. For each of the clusters, or even for groups within them (such as the many gamified approaches within the experiential fore-sight cluster), a systematic analysis of comparable cases would also be an important field for further enquiry. A reflection on underlying theory and connections to insights from other fields such as design and psychology, in other words for what has been called the “experience factor in foresight” would also be worthwhile (Rijkens-Klomp et al., 2014). However, while we still lack these solid

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research insights and probably will for some time in the future, the dynamics of the developments in all four clusters of emerging approaches, the degree of agreement between the experts consulted concerning their current and future relevance, and the first insights on their wide range of benefits all form a strong indication that the foresight and STI community should be striving to integrate them into their practice more today.

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Emerging Practices in Foresight and Their Use in STI Policy

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