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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.
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