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Crazy Futures: Why Plausibility is Maladaptive Wendy Schultz Bio: Wendy Schultz is the Director of Infinite Futures and a Senior Fellow of the Center for Postnormal Policy and Futures Studies. She also serves as Vice-President for Training of Vision Foresight Strategy LLC, is a principal of SAMI Consulting, the Emergentista for LASA Development, and a Fellow of the World Futures Studies Federation. Her primary focus in futures research is designing innovative participatory futures methods.

One person's craziness is another person's reality. - Tim Burton

What are crazy futures; and why do we need them? Let me answer this question by considering both words: ‘crazy’, as contrasted with ‘normal’ generally and then specifically with ‘plausibility’ as a term of art over-used in futures and foresight practice, especially scenario planning; and ‘futures’, that is images of non-existent, forward temporally displaced situations and contexts and their generation, especially as contributing to perceptions of ‘craziness’. In the process, I will also explore the notions of complexity and chaos, and what they imply for the usefulness of crazy futures in contrast to plausible futures. What is ‘crazy’?

* Crazy * music, dudes and dudettes! …he’s * crazy * about his dog / fishing / iPad… You want to go bungee-jumping? Are you * crazy *?

The first known use of ‘crazy’ was in 1566 (Merriam-Webster). It originally meant ‘full of cracks or flaws’ – that is, like the glaze on a pot can be ‘crazed’ with cracks. The meaning ‘of unsound mind, or behaving as so,’ emerged later, in the early 1600s. The jazz slang sense of crazy as ‘cool’ or ‘exciting’ sprang up in the late 1920s (clearly what we mean when we call ourselves ‘crazy futurists’). Nowadays it often means simply out of the ordinary, unusual – or impractical. So we need to think about two aspects of the term: first, being flawed, unsound, or broken mentally; and second, being unusual, and out of the ordinary. In the last 400 years, both physiological and psychological research have resulted in significant progress in our understanding of the full range of illnesses and syndromes that contribute to a broad range of mental perspectives and resulting behaviours that observers might label ‘crazy.’ Those illnesses cause serious pain to both sufferers and their loved ones, and this discussion in no way is meant to downplay that. But judging behaviour as ‘crazy’ is subjectively relative. When I was a child and walking down the street and the person coming towards me was talking to herself out loud, I would very likely cross the street to avoid her. Now we are all surrounded by crowds of people ‘talking to themselves’ – and no longer consider it ‘crazy’ because it is contextually appropriate in an era of mobile phone earpieces. It is neither unusual behaviour, nor out of the ordinary, given a specific technological setting. The same applies, of course, to different cultural settings: flooding a bathroom by using the shower hose outside of the stall is ‘crazy’ behaviour in the USA but perfectly rational in Japan, where the bathing room has a drain in the floor, and one is expected to be clean before entering the bath.

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So if we define ‘crazy’ by contrast with ‘normal’, then it is the unusual as contrasted against the usual. ‘Crazy’ is subjectively relative to internal expectations filtered and biased by milieu, culture, and technological setting, among other things. That is precisely its utility to futures thinking. ‘Crazy’ – and the sense of nervous apprehension it engenders in viewers – highlights and problematizes the assumptions and points of view that compose the normal. If the various futures we face are composed of surprises, of novelty – of the abnormal – then crazy is just what we need: it exposes our blind spots, the dangerous limitations of our assumptions. But a more specific new antonym to ‘crazy’ has emerged in futures practice in the last few decades. Rather than opposing crazy with ‘normal,’ it equates ‘crazy’ with ‘impossible’, and opposes it with ‘plausible’. What is ‘plausible’?

You keep using that word. I do not think it means what you think it means.

Inigo Montoya to Vizzini, in The Princess Bride In the early 80’s Roy Amara gave us a classic conceptualization of the set of all images of the future as roughly divisible into possible, probable, and preferred (Amara, 1981). This was useful because it was robust: possible was the set of everything – every future possible to imagine, whether or not they had already been imagined; probable was monitorable, if not measurable – researchers could observe emerging issues growing in momentum, becoming trends, evolving into greater probability; and preferable was articulable – researchers could engage stakeholders in value discussions and judgements and essentially map the value territory. In Venn diagram terms, the categories overlap, but are still useful as a conceptual base for futures research methods. Yet somehow over the intervening decades, the terms have morphed to ‘possible, plausible, probable, and preferable futures’. Ruud van der Helm carefully explores operational definitions that distinguish possible, probable, and plausible (van der Helm, 2006). He reviews both objective probability (based on the repeatability of systems) and subjective probability (based on personal or group utility functions); and also offers distinctions between absolute possibility (based on the known laws of reality) and contingent possibility (based on capabilities at given points on a time horizon). Van der Helm then contrasts both of these with plausibility, due to its intrinsically subject-related nature based on judgment and conviction. The challenge for futures practice is “to develop futures that are indeed ‘equally plausible’ but sensibly different (van der Helm, 2006, p26) in order to present convincing alternatives for exploration. Sometimes the wide and woolly set of ‘possible’ drops entirely from the field of view, and only ‘probable, plausible, and preferable’ futures remain. Ramirez and Selin suggest that as futures studies, foresight, and scenario planning evolved, probability evaluations became a key evaluative criterion for forecasters focussed on predictive capability, where plausibility became the hallmark for exploratory practitioners focussed on appreciating alternative futures (Ramirez and Selin, 2014). ‘Plausibility’ has emerged as a primary operating assumption, even a criterion for excellence,

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within English-speaking scenario practice (especially within the community of ‘scenario planners’). Here is a partial inventory of the evidence: • ‘To be effective, scenarios must be plausible, consistent and offer insights into the

future. … Plausibility: A scenario must be plausible. This means that it must fall within the limits of what might conceivably happen.’ (FORLEARN, 2005)

• From Thinking About the Future: Guidelines for Strategic Foresight, ‘plausible futures: reasonable outcomes, with a discernible pathway from the present to the future. For example, discovering extra-terrestrial life within the next decade is possible, but not plausible.’ (Bishop and Hines, 2006, p128)

• From Creating Futures: ‘scenarios are only credible and useful if they meet the following five conditions that we believe instil rigor: relevance, coherence, plausibility, importance and transparency.’ (Godet, 2001, p63)

• From Scenario Planning: ‘Scenarios are vivid descriptions of plausible futures.’ (Lindgren and Holden, 2003, p 22)

• From The Scenario Planning Handbook: ‘scenarios must meet the following criteria: they must be plausible – that is, they must fall within the limits of what might reasonably be expected to happen.’ (Ralston and Wilson, 2006, p 121)

• From Scenarios for Success: ‘A scenario is a self-consistent account of one plausible way in which uncertain future events may play out with a bearing on the future of an organization and its ability to fulfil its purpose.’ (Sharpe and van her Heijden, 2003, p 57)

• From the Neville Freeman Agency: ‘Scenario planning is a metaphor-rich narrative designed to help you consider alternative, plausible futures.’ (Freeman, 2009)

• ‘Selecting a scenario space means examining the various future states the drivers could produce. Illogical and non-plausible situations should be rejected. Selecting alternative worlds to be detailed involves limiting the number of future stories, since it would be impossible to explore every option. The key is to select plausible futures that will challenge current thinking.’ (Chermack, Lynham, Ruona, 2001, p20).

• From ‘When and How to Use Scenario Planning’: ‘the scenarios should bound the range of plausible uncertainties and challenge managerial thinking.’ (Shoemaker, 1991, p549)

• ‘Scenarios are possible future states of the world that represent alternative plausible conditions under different assumptions.’ (Mahmoud et al., 2009, p798)

Let me emphasise the first two of these quotes because they clarify the matter by offering a definition and an example of plausibility. FOR-LEARN suggests that a plausible scenario ‘must fall within the limits of what might conceivably happen.’ The authors of Thinking About the Future suggest that plausible futures offer ‘reasonable outcomes, with a discernible pathway from the present to the future.’ They further clarify with an example: ‘discovering extra-terrestrial life within the next decade is possible, but not plausible.’ The difficulty with both of these lies in the subjective capability and state of knowledge of the viewer: the more knowledgeable the viewer on the topic of the scenario, or its component details, the more events and futures they are capable of

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conceiving as something that could ‘conceivably happen.’ In the example of discovering extra-terrestrial life, the scenario is possible, but perhaps of low probability. But it is in fact plausible, because discernible pathways exist not only for the evolution of extra-terrestrial life, but also for our potential discovery of it (given the various robotic surveys of other planets we have launched recently). Defining ‘plausibility’ is problematic. This limits its usefulness as a criterion for excellence in futures thinking, even assuming that it is an appropriate criterion for excellence. So let’s hit the dictionaries once again: what is the technical definition of ‘plausible,’ and what is its etymology? The Merriam-Webster Dictionary tells us that plausible means:

superficially fair, reasonable, or valuable but often specious <a plausible pretext>; superficially pleasing or persuasive <a swindler… , then a quack, then a smooth, plausible gentleman — R. W. Emerson>; appearing worthy of belief <the argument was both powerful and plausible>.

Embedded within the structure of this word is the professional vulnerability that all futures researchers face in practicing an intellectual discipline for which there are no future facts, in a world of decision-makers hungry for an evidence base: how to appear valuable when we are suspected of purveying specious results and being quacks. The Oxford English Dictionary (OED) entry is even more telling, in offering us the older, now obsolete uses of the word, all of which revolve around pleasing the public and thereby winning approval:

Acceptable, agreeable, pleasing, gratifying; winning public approval, popular. Obs.; Expressing applause or approbation; plausive, applausive. Obs. ; Deserving of applause or approval; praiseworthy, laudable, commendable. Obs.; Of an argument, an idea, a statement, etc.: seeming reasonable, probable, or truthful; convincing, believable; (formerly) spec. having a false appearance of reason or veracity; specious. Of a person: convincing or persuasive, esp. with the intention to deceive.

The OED then clarifies current uses, suggesting that plausible ideas seem reasonable or probable – while pointing out that it formerly implied that such an appearance of reason was false. Furthermore, when applied to a person, it ‘still’ implies an intention to deceive cloaked in false persuasion. Why do I dwell on these historical facts of etymological evolution at such length? My observations of how consultants use the label ‘plausible scenarios’, or ‘plausible futures’, suggest that it is actually code for ‘don’t give the clients crazy futures, or they’ll reject them, reject us, and we won’t get paid and will never work in this town again’. How often in strategic foresight projects do the end results offer truly transformational futures that challenge participants to consider the possibilities of deep structural change? How often do scenarios create ‘productive discomfort’ in how people see the world (Ramirez and Selin, 2014, p67)? Of worlds with entirely different economic or political systems? Of usefully crazy futures?

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What are ‘futures’ – and why and how do we think about them? While scenario thinking per se originated in Herman Kahn’s policy strategy concerns (Kahn, 1962), the origin of futures thinking is rooted in the image of the future, and concerns of futurist Fred Polak for the vitality of human culture and civilizations (Polak, 1961). We shouldn’t limit the ‘futures’ in ‘crazy futures’ to strategic scenarios alone. Such purpose-designed images of the future compete for mental and emotional space with a nearly endless supply of images of the future generated across human activity. Imagining long-range futures is a talent unique to our species – so what images do we create, how do we create them, and what are they for? Futures studies as an intellectual endeavour includes the inventory and content analysis of existing images of the future. Humans express imagined futures in all media, as all variety of cultural constructs, and in varying scales of personal and civilizational usefulness. Images of the future in advertisements, counselling programs, and in daydreams target personal behaviour by expressing self-fulfilling or self-defeating prophecies. In the same way, community, organizational, and political futures attempt to inspire group action through both cautionary tales (‘doom and gloom’; nightmare futures), and through aspirational tomorrows (visions). Images of the future are embedded in all political discourses and ideologies, whether they warn of imminent national collapse at the hands of the opposition (nightmare futures), call for ‘Holding the course! Steady on!’ (present-trends-extended futures), or depict a happy era to come (Conservatives: A return to the Golden Age! Liberals: An All-New

Brighter Tomorrow!). At the largest scale, Polak’s call for aspirational, transformative images of the future was meant to catalyse civilization-level vitality. But categorizing any specific image of the future as a nightmare or a vision is entirely subjective. Furthermore, it is a subjective judgment that can generate tragedies.

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Conflicts arise when people fear a nightmare future is the hidden goal of others around them. And any extreme of difference is labelled ‘crazy,’ whether it is extremely good, extremely bad, or extremely different. We could probably conceptualize a craziness scale for futures, anchored at sanity/normality/plausibility on the one end, and ‘completely bug@%$@ crazy’ at the other extreme. It might be operationalized as the percentage of any given population that perceives a specific image of the future as offensively, scarily transgressive and transformative beyond all bounds of reason and decency. If nobody feels the future is beyond all bounds, it’s normal and plausible as normal can be. If 50% of the people feel it’s beyond all bounds of reason and decency, and the other 50% do not, then it’s only moderately crazy. And so on. It is not just the image itself that is judged. ‘Crazy futures’ often earn that label, despite being prosaic and mundane in content, if they have transgressed in process. The current decision-making environment for many economic, political, and social issues is instrumentalist, evidence-based and biased towards Western empiricism. Sadly, a field that engages in research despite lacking an ability to observe its subject directly (until such time as tachyon-powered time machines or traversable wormholes enable field research in the futures) often lacks credibility as well. In a previous essay, I summarised this ‘cultural contradiction’ (Schultz, 2006) between the criteria for excellence in empirical, evidence-based research, and for excellence in futures research (specifically horizon scanning), as follows:

Empirical/ Evidence-based Research

Futures Research, especially emerging issues scanning & analysis

• Credible;

• Documented;

• Authoritative;

• Statistically significant;

• Coherent: the data

agree; • Consensus-based:

the experts agree;

• Theoretically grounded; and

• Mono-disciplinary.

• Any emerging issue unusual enough to be useful

will probably lack apparent credibility; • it will be difficult to document, as only one or two

cases of the change may yet exist; • it will emerge from marginalized populations, and

be noticed initially by fringe sources, hardly the sort of authoritative sources that civil servants feel confident in citing;

• as emerging issues are by definition only one or two cases, they are also by definition statistically insignificant;

• the data will vary widely, converging over time only if the emerging issue matures into a trend;

• not only will consensus be lacking, but experts will often violently attack reports of emerging issues of change, as they represent challenges to current paradigms and structures of expertise, power, and entitlement;

• emerging issues of change often challenge previous theoretical structures and necessitate the construction of new theories;

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Empirical/ Evidence-based Research

Futures Research, especially emerging issues scanning & analysis

• and the most interesting new change emerges where disciplines converge and clash. As the impacts ripple out across all the systems of reality, emerging changes and their impacts require a multi-disciplinary analytic perspective.

Bishop, Hines, and Collins have produced inventories of formal futures methods for generating images of the future – both scenarios (extrapolations) and visions (value-based preferred future articulations) – and described almost two dozen rigorously structured processes (Bishop, Hines, and Collins, 2007). These range from logical and quantitative methods using statistical trend extrapolation, computer-aided cross-impact matrices, and systems dynamics modelling, through facilitated group process dialogue, to meditative, ‘guided visualization’ techniques. Evidence-based decision support cultures prefer their futures heavily salted with data and quantitative extrapolation. They are likely to shy away from guided visualization workshops. So decision-makers, observers – and practitioners – also judge some means of generating futures as ‘crazy’. Generally, the more intuitive methods are greeted with the most scepticism and distrust. Scenario planners and scenario builders are not alone in devising images of the future. Artists, advertisers, novelists, screenwriters, animators, sculptors, analysts, and leaders all generate stories, images, and artefacts expressing different future outcomes and environments. So do prophets, astrologers, tea-leaf readers, shamans, and particularly skilled remote viewers. By extension, if rigorous but intuitive tools such as guided visualization earn scepticism, artistic inspiration may as well – and astrologers, shamans, and remote viewers earn outright derision. Why shouldn’t they? Why shouldn’t we just discard images of the future generated by ‘crazy’ methods such as astrological computations and shamanic trances and remote viewing? To answer that we must return to the conceptual foundations and core assumptions of futures studies as a field of research, which include three basic axioms: 1. There is not one single future, but multiple alternative futures; 2. People’s beliefs about the future, and their images of the future, affect their decisions and actions, which in turn create the futures as an emergent property of aggregated interconnected actions; 3. Because any given lived future at any given moment is an emergent property of a complex system that frequently exhibits chaotic behaviour, it is not possible to ‘predict’ human futures. It follows from these axioms that it is not important which image of the future is correct, or best supported by empirically credible data, or most plausible. The most important future is the future the greatest number of people believe the most: it is the future on which they are basing their decisions and actions. If people read astrological forecasts or tea leaves or goat entrails, and then act on those images of the future, then

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those images of the future are important for us as futures researchers to consider. The craziest methods can generate compelling futures, and crazy or not, compelling futures are the futures that should concern us the most. Given that societies and cultures contain multiple sources of novel ideas and crazy futures, critical analysis of existing images of the future should be a cornerstone of comprehensive futures research. When researchers move beyond content analysis of existing images of the future to creating purpose-built images of the future for exploratory, critical, or strategic purposes, then it may be useful to generate crazy futures by design to mimic their emergence across societies and cultures. Why are crazy futures the most useful?

We all agree that your theory is crazy, but is it crazy enough? Niels Bohr

Consideration of the basic axioms of futures studies points directly to why crazy futures are useful: we are embedded in – and are ourselves – complex systems flirting daily with chaos. In describing the ‘edge of chaos’ (Langton, 1990), Chris Langton’s egg diagram maps the transition boundaries between periodic, chaotic, and complex states. This diagram categorizes four types of systems. There are fixed systems, existing in a state of maximum thermodynamic equilibrium, meaning maximum entropy (or death). There are periodic systems, which are ordered but not adaptive. There are chaotic systems, characterized by sensitive dependence on initial conditions, and non-linear determinism. Finally, there are complex systems that are self-organizing, self-directing, self-repairing, and adaptive. The self-directing and adaptive characteristics of complex systems result in evolutionary change over time, producing in turn novel emergent properties. They generate surprises. If sentient, they undoubtedly surprise themselves. Emergent properties are ‘out of the ordinary’, if by ordinary we mean the previous patterns of ordered system behaviour. So any complex adaptive system (and all human systems – whether single individuals or collections as organizations, or communities, or nation-states – are complex adaptive/evolving systems) will at one point or another generate ‘crazy states’.

It becomes even more likely that these systems will exhibit ‘crazy’, that is, ‘out of the ordinary’ behaviour if they are stressed by larger energy or information flows. One

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response to stress in a complex system is a transition into chaotic behaviour. This phase change also creates the potential for novel and unusual behaviour outside the ordinary.

Cynefin Framework, David J. Snowden, Cognitive Edge

Langton’s diagram summarizes system characteristics as observed externalities. In contrast, Snowden’s Cynefin Framework offers the internal view, as the observing consciousness attempts to make sense of dynamic systems and events in transition. “Cynefin … contrasts how things are, with how we know them, with how we perceive them” (Snowden, 2013). Cynefin organizes both the systems, and the knowledge about those systems, in order to suggest ‘best fit’ paths for actors navigating the dynamics of those systems and events. One of the best fit paths suggests a deliberate brief dip into chaos precisely to generate radical innovation, or potential ‘crazy futures.’ So in the end, a focus on ‘crazy futures’ may be the most adaptive strategy we can encourage people to adopt, and a focus on ‘plausibility’ the most maladaptive. Is your future crazy enough to help you, your organization, your community evolve? Better that we rehearse the full range of surprises that may await us across our futures, than be ill-prepared and unable to adapt. Emergence and evolution are preferable to equilibrium. How can we best communicate craziness?

I want to believe. Fox Mulder’s wall poster, ‘The X-Files’

So how are we to communicate compelling craziness? In 1970 Mori identified ‘the uncanny valley’ in observing how people responded to humanoid robots (Mori, 1970).

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Digital animators have also noticed a similar response to animated human characters. The uncanny valley hypothesis suggests that when human ‘replicas’ – either robotic or animated– look and act almost, but not perfectly, human, people response with revulsion. Granted, James Cameron seems to have overcome the effect in generating the Navi characters over the motion capture performance of his actors.

The relevance to useful crazy futures is that something similar exists in conveying radically transgressive, transformative images of possible futures: up until a point, increasing craziness increases how exciting, provocative, and challenging they are. Beyond that point, increasing craziness pushes the futures into the uncanny valley of the unthinkable, on the other side of which is the transgression of perfect conceptual chaos. Whatever their degree of craziness, useful futures are compelling – people respond to them, adopt them, and use them to inform action. How do we decrease the uncanny valley of the unthinkable? How do we avoid Cassandra syndrome? The endeavour of deploying crazy futures asks us to balance on a knife edge of usability: too normal, and no mind-shift results; too crazy, and brain-freeze occurs. Likewise, futures too divorced from our own experience may feel very crazy, but not be very compelling; too near to our own experience, and the futures will be too subjective to be useful – compelling, but insufficiently out of the ordinary. A possible antidote can be found in audience participation. Cutting edge methods in scenario building include projects like Jane McGonigal’s SuperStruct, and Evoke, and the growing body of work using the Institute for the Future’s ‘Foresight Engine’. These projects all rely on massively crowd-sourced, participatory futures formation via on-line game environments. They evolve from each individual’s own participation, which is very compelling – but they evolve. The futures generated are emergent properties of the participants’ interactions with each other, and the useful strangeness arises from those interactions. In The Art of Immersion, Frank Rose offers

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a range of case studies underlining how powerfully engaging the unfinished story can be (Rose, 2012). This is the Web 2.0 corollary of McLuhan’s ‘media hot and cool’: the most compelling media are the ‘cool’ media, conveying ideas in low definition and inviting us to participate in completing the details. So whatever crazy futures we imagine, we should imagine them with holes, with interstitial spaces that invite other people to adapt them and adopt them: a crazy future must be compelling to be useful. Coda Alice laughed. ‘There's no use trying,’ she said. ‘One can't believe impossible things.’

‘I dare say you haven't had much practice,’ said the queen. ‘When I was your age, I always did it for half an hour a day. Why, sometimes I've believed as many as six

impossible things before breakfast.’ Lewis Carroll / Charles Dodgson, Alice in Wonderland

In order to thrive in whatever futures we pass through, it helps to rehearse what our values, assumptions, decisions and actions - our very sense of self - might be in those futures. Authentic rehearsal inevitably requires that at some level we choose to believe not only what is plausible, and not just what is probable or possible, but that we stretch our values, assumptions, and sense of self to believe and rehearse for the impossible as well. So call me crazy.

You have to go on and be crazy. Craziness is like heaven. Jimi Hendrix

Note This article is an update of an essay originally written for the Mutual Learning Workshop on Crazy Futures, 27 June – 1 July 2011. This activity of The Bucharest Dialogues was sponsored by UEFISCSU, the Romanian Executive Agency for Higher Education and Research Funding, and their support is gratefully acknowledged. References Amara, Roy, The futures field: Searching for definitions and boundaries, The Futurist 15:1 (1981), 25-29. Peter Bishop, Andy Hines, and Terry Collins, The current state of scenario development: an overview of techniques, Foresight 9:1 (2007) 5-25 Thomas J. Chermack, Susan A. Lynham, Wendy E. A. Ruona, A Review of Scenario Planning Literature, Futures Research Quarterly (Summer 2001) 7-31 FORLEARN 2005-7, Scenario building, accessed 21 November 2014, http://forlearn.jrc.ec.europa.eu/guide/3_scoping/meth_scenario.htm#Outputs.

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Oliver Freeman, Scenario Planning: Case Study 4, accessed 21 November 2014, http://www.futureshouse.com/downloads/vision.pdf. Michel Godet, Creating futures: scenario planning as a strategic management tool (London: Economica, 2001) Andy Hines and Peter Bishop, Thinking about the Future, Guidelines for Strategic Foresight, (Washington: Social Technologies, 2006) Herman Kahn, Thinking about the Unthinkable (New York: Avon Books, 1962). Christopher G. Langton, Computation at the edge of chaos: phase transitions and emergent computation, Physica D 42 (1990) 12-37. Egg diagram accessed 21 November 2014, https://theory.org/complexity/cdpt/html/node5.html Mats Lindgren and Hans Bandhold, Scenario Planning: the link between future and strategy (New York: Palgrave Macmillan, 2003) Mohammed Mahmoud, Yuqiong Liu, Holly Hartmann, Steven Stewart, Thorsten Wagener, Darius Semens, Robert Stewart, Hoshin Gupta, Damian Dominquez, Francina Dominguez, David Hulse, Rebecca Letcher, Brenda Rashleigh, Court Smith, Roger Street, Jenifer Ticehurst, Mark Twery, Hedwig van Delden, Ruth Waldick, Denis White, Larry Winter, A formal framework for scenario development in support of environmental decision-making, Environmental Modelling & Software 24 (2009) 798-808. Merriam-Webster, Crazy, accessed 21 November 2014, http://www.merriam-webster.com/dictionary/crazy. Merriam-Webster, Plausibility, accessed 21 November 2014, http://www.merriam-webster.com/dictionary/plausible. Masahiro Mori, The uncanny valley, IEEE Spectrum, accessed 21 November 2014, http://spectrum.ieee.org/automaton/robotics/humanoids/the-uncanny-valley. Oxford English Dictionary, Plausibility, accessed 21 November 2014, http://www.oed.com/view/Entry/145466. Fred L. Polak, The image of the future: enlightening the past, orientating the present, forecasting the future (New York: Oceana Publications, 1961) Bill Ralston and Ian Wilson, The Scenario Planning Handbook: Developing Strategies in Uncertain Times (London: Thomson/South-Western, 2006) Rafael Ramirez, Cynthia Selin, Plausibility and probability in scenario planning, Foresight 16:1 (2014) 54-74

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Frank Rose, The Art of Immersion: How the digital generation is remaking Hollywood, Madison Avenue, and the way we tell stories (New York: W. W. Norton & Company, 2012) Paul J. H. Schoemaker, When and how to use scenario planning: a heuristic approach with illustration, Journal of Forecasting 10:6 (1991) 549-564 Wendy L. Schultz, The cultural contradictions of managing change: using horizon scanning in an evidence-based policy context, Foresight 8:4 (2006) 11. Bill Sharpe and Kees van der Heijden, Scenarios for Success: Turning insights into action (Chichester: John Wiley & Sons Ltd, 2003) David J. Snowden, Mary E. Boone, A leader’s framework for decision-making, Harvard Business Review, November (2007), accessed 21 November 2014, https://hbr.org/2007/11/a-leaders-framework-for-decision-making. Snowden, Great is the power of steady misrepresentation, December 11, 2013, accessed 21 November 2014, http://cognitive-edge.com/blog/entry/6149/great-is-the-power-of-steady-misrepresentation/. Ruud van der Helm, Towards a clarification of probability, possibility, and plausibility: how semantics could help futures practice to improve, Foresight 8:3 (2006) 17-27