5th International Conference on Future-Oriented Technology Analysis (FTA) - Engage today to shape tomorrow
Brussels, 27-28 November 2014
STRUCTURED ANALOGIES AS A MODE OF PREDICTION
Scott W. Cunningham and Terry R. Schumacher
1
Policy Analysis Section, Faculty of Technology, Policy and Management, Jaffalaan 5, 2628 BX Delft,
The Netherlands, [email protected]
2
Rose-Hulman Institute of Technology
Abstract
This paper supports developing creative interfaces for forward looking activities –
by re-examining a fundamental technique of social and technological forecasting.
The technique, forecasting by analogy, shows strong promise for analysing
anticipatory systems, for developing new forecasts, and for understanding how
visions of the future are perceived, imagined, and communicated. Although the
technique is widely adopted, the benefits of a structured approach to creating and
critiquing analogies has seemingly been forgotten in the future-oriented
technology analysis literature.
Keywords: Foresight, Analogy, Cognition, Societal Dialog
1 Introduction
In section 1 of this paper we define the concept of analogy, and offer a brief definition of their
role in human thought. We then acknowledge previous work on forecasting by analogy in the
future-oriented technology analysis literature. Section 2 offers a brief but structured review of the
vast literature of analogy-building from other fields. Using the review we gather insights from the
domains of science, technology and innovation, but also more social, political and legal domains
as well. In section 3 we are thereby equipped to better consider the potential role of analogies in
future-oriented technology analysis. We consider how analogies might be created by the
analyst, and the respective advantages and disadvantages of the technique compared to other
techniques. In section 4 we conclude by discussing the potential areas of foresight where
analogies might be used to maximal advantage. We begin in section 1.1 by defining the concept
of analogy.
1.1 What are Analogies?
Dictionary definitions of analogy include: a comparison between two things, typically on the
basis of their structure and for the purpose of explanation or clarification; a correspondence or
partial similarity; a thing that is comparable to something else in significant respects. Pollack
(2014) also offers some helpful insights into the definition of an analogy:
In broad terms, an analogy is simply a comparison that asserts a parallel –
explicit or implicit – between two distinct things, based on the perception of a
shared property or relation., In everyday use, analogies actually appear in many
forms. Some of these include metaphors, similes, political slogans, legal
arguments, marketing taglines, mathematical formulas, biblical parables, logos,
TV ads, euphemisms, proverbs, fables , and sports clichés (Pollack 2014)
The nature, purpose or significance of analogies in thinking has received a lot of attention from
many scientific notables. Consider the following quotes (as sourced by Hofstadter and Sander
(2013)):
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“In an analogy, a familiar domain is used in order to understand a new domain, especially to
predict new aspects of this new domain (Clement and Gentner 1991).”
“Analogy pervades all our thinking, our everyday speech and our trivial conclusions as well as
artistic ways of expression and the highest scientific achievements (Polya 1954).”
“When faced with something new, we cannot help but relate to it except by comparing it with
what is familiar and known to us (Oppenheimer 1956).”
Analogies then are ubiquitous in thinking and in public life. This leads us to further consider how
analogies work, and how they serve us in our thinking.
1.2 How Do Analogies Work?
In the world of thinking fast and slow, the use of analogies is a fast response. Fast responses
are the dominant means of thinking because thinking is expensive. Fast thinking is less
demanding of cognitive time and energy, and therefore places less cognitive load on human
faculties. Slow thinking -- while needed for consequential decisions – places a much greater
load on human cognitive processes (Kahneman 2013).
There are two competing ideas about how analogies work. In one, the construction of analogies
is a slow and deliberate construction of a map, one which translates from a familiar domain to a
new and unfamiliar. In a competing vision, analogies instead reside in the fast portions of human
cognition. In the words of Hofstadter and Sander
This stands in stark contrast to the standard image of analogy-making as a
process of deliberate construction of mappings between situations. Naïve
analogies lead directly to conclusions without there being any consideration of
other options, and without any uncertainties or doubts arising (Hofstadter and
Sander 2013)
This leads to some of the strengths and weaknesses of analogy-making as a process of human
thought, and indeed of analogies as a method of future-oriented technology analysis. How is it
that we as humans can make these short-cuts in reasoning? How can we get by merely looking
at superficial resemblances between things? Again, in the words of Hofstadter and co-author:
The reason analogy is so extremely efficient is that appearances are indeed great
indicators of essences. This is why reliance on surfaces is not a poor strategy in
life. It’s just that in selecting which of a situation’s innumerable surface-level
features to rely on as clues, one has to do one’s best at separating the wheat
from the chaff. This is what the development of expertise does for us (Hofstadter
and Sander 2013)
This thinking about the nature of expertise is also a fruitful insight about how to use analogies
more effectively, and a point we will turn to later in the paper. In the meanwhile:
The idea is simple: the only way we have of making decisions, whether they are
small or large, is through analogy – that is, by making analogies with a spectrum
of previous experiences (whether personal or vicarious) that have been brought
to mind by the pressing decision (Hofstadter and Sander 2013)
In the next section we consider the history of analogies as a method for forecasting and
foresight.
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1.3 When Where Analogies First Recognized in FTA?
Forecasting by analogy is listed as a technological forecasting techniques in major texts as early
as 1972. Martino (1972) enables use of analogies by providing a list of frames of reference, and
reminding the audience of certain fallacies of reasoning. Sahal (1981), in the space of
technologies, argues that three major conceptions have been historically used. Analogies have
an earlier and more extensive history in the social sciences. Daniel Bell’s influential essay on
social prediction dates even earlier than Martino or Sahal (Bell 1964). Analogies are not
explicitly mentioned here; or perhaps, it is more correct to say that a number of distinct modes of
analogous reasoning are being considered. Despite these foundational works, newer
methodological developments have been limited.
Linstone comments there has been little new development of technology forecasting methods in
the past 20 years (Linstone 2002, Porter, Ashton et al. 2004). He thinks better techniques are
needed. Our paper attempts to make such a contribution. There have been a number of different
texts mentioned as an assessment of the level of development of analogy as a technology
forecasting tool, and the level of professional guidance offered in the future-oriented technology
analysis field for analogy use (Ayres 1969, Martino 1972, Porter, Roper et al. 1991). Our paper
attempts to move forward to a new level of development. To add to the paucity of guidance for
using analogy as a tech forecasting technique (c. f. Martino 1972), we review research that
explores the use of analogy in learning and acquisition beginning in the 1980s. Using analogy in
forecasting can be seen as a learning activity and thus shares significant similarity with this
work.
Porter and co-authors treat analogies alongside creativity in a single methodological chapter.
This organization is as if analogies and creativity are synonymous. This perhaps does a little
disservice to analogies because the even the most truly creative uses of analogies are often
subject to introspection and critique (Hofstadter and Sander 2013) . Suggested techniques for
use along analogies include checklist procedures and random words as a trigger for free
association (Porter, Roper et al. 1991). The offer general habits of thought as well for promoting
creativity, including suspension of disbelief, and lateral thinking.
2 Methodological Approach
In this section we consider the creation of analogies, looking at analogies made for two distinct
purposes. We first consider analogies which might be most effective for identifying future trends
or developments in technology. These are often the analogies in use by engineers, scientists
and innovation. Then in the next section we consider analogies which might work best when
communicating ideas to decision-makers and stakeholders.
Our purposes here are to observe the uses of analogies in a somewhat distant context, in order
to bring these lessons back to future-oriented technology analysis. By doing so we may be more
thoughtful in our own application of analogies, and we may be able to formulate new
methodological recommendations, and build new societal interfaces for constructive discussion
about emerging technologies.
The use of analogies is widespread in public discourse and academia. For instance, a recent
issue of Foreign Affairs draws analogies between the current situation in Crimea and the
outbreak of World War II (Mankoff 2014). Zakaria (Zakharia 2008, Zakharia 2008) describes the
British empire as an analogy to understand the future of the U.S. economy. Hanson (2000)
anticipates massive increases in productivity in a post-industrial society through the use of
structured analogies to other major societal transitions. An influential strand of literature
concerning technological transitions draws analogies between previous technological transitions
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and modern ones (Geels 2002). Such analogy building is undoubtedly useful . Green and
Armstrong (2007) show that structured analogies greatly enhance expert abilities to assess
complex social situations.
2.1 Analogies in Science, Technology and Innovation
Analogies are widely used in science, engineering and innovation. This use is vividly
documented by Hofstadter and Sander (2013). In Hofstadter and Sander’s view analogies are
fundamental to all of human thought, and involve often unconscious comparison of things given
their most salient features. Despite this, many experts are able to make wildly creative analogies
since they are able to look beyond surface phenomena to better compare the fundamental
essences of things.
In the book by Hofstadter and Sander (Hofstadter and Sander 2013) are examples of the
constructive use of analogies in innovation. There is a similar list, partially overlapping in other
sources as well (Pollack 2014). The list of inventions and innovations which were heavily
inspired include the computer mouse, the graphical user interface, and the analogy of a
computer desktop as envisaged by Apple and by Microsoft. Other authors describe this shadowy
space of would-be inventions and ideas, seemingly reached by analogy as “the adjacent
possible” (Johnson 2011).
Also discussed by observers of science the examples of the use of analogies leading to new
understanding in science, including new understanding of waves (of sound and light), the nature
of the solar system, and understanding the structure of the atom. Even the most creative insights
of Einstein are themselves a masterful feat of analogy-building. In fact, for some authors, the
very activity of modern physics involves participating in a joint-activity of analogy building:
Over the past hundred years or so, making bold analogical extensions in physics
as become so standard, so par for the course, that today, the game of doing
theoretical physics is largely one of knowing when to jump on the analogy
bandwagon, and especially of being able to guess which of many competing
analogy bandwagons is the most promising (and this subtle selection is made by
making analogies to previous bandwagons, of course!) (Hofstadter and Sander
2013, p. 213)
We now turn to the use of analogies in the public sphere. Here we find many of the same
features of analogy-building, but also some new ones as well. In social life, analogy-building is
an important means of persuasion, but also of misdirecting others.
2.2 Analogies in Social, Political and Legal Life
Analogies are also an essential part of social, political and legal life. Pollack (Pollack 2014) also
writes about the social and political consequence of analogies. As he notes analogies are part of
a process of social dialog or contestation:
This may be one reason that effective analogies, which are essentially
compressed and spring-loaded stories, often enable people to seize the high
ground in an argument. In offering a coherent narrative, they allow their creators
to deftly sidestep the quicksand of competing “facts” and more closely approach
the intellectual and emotional core of their argument (Pollack 2014)
For some authors, this social dialog moves beyond mere dialog or persuasion to outright
contestation. As Cohen (2005) notes “we are living in the age of the false, and often shameless,
analogy.” Lakoff (2004) harnesses the power of analogies to push forward his own specific
political agenda. But he is not alone in this (de Bruijn 2011). As Lakoff notes, if you don’t
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harness the power of an analogy for yourself, then your opponent will. Your opponent’s choice of
language “picks out a frame—and it won’t be the frame you want (Lakoff 2004).”
Other authors have given thought to analogy as a frequently used, yet frequently overlooked
part of strategic decision-makers. Although analogy-building is an effective mode of thinking, it
behoves the decision-maker to be more explicit in their use and consideration of analogies
(Gavetti and Rivkin 2005).
Law is also “almost entirely dependent upon analogies..” In one account of an American law
school most of the training involved a wilful examination of the similarities and differences
between cases, and between statues. All of law school is “really about arguing whether the
similarities or the differences are more important (Cohen 2005).” Another curious feature of legal
reasoning is the chaining of analogies which occurs by precedent. Originally an analogy may be
of dubious merit, but by repeated use it gains currency, and gains common practice. Even more,
the precedent is used to reach even further out into newly emerging areas of need in law,
governance or institutions.
What have we learned from this comparison of analogy use in science and society, and what
does it teach us about the appropriate and beneficial use of analogies in future-oriented
technology analysis? Both applications of analogy use the familiar to explain something less
familiar. In both cases some analogies are inherently more useful than others; the coherence of
the analogy may have a lot to do with its use. Yet a political argument is designed to resonate
emotionally and prompt immediate and unjudging acquiescence. The use of analogies for futureoriented technology analysis should therefore take the best available knowledge from both
scientific, as well as public discourse, in order to better build a constructive bridge with the
public.
3 Results, discussion and implications
In this section we harvest the findings of the review in order to formulate recommendations for
the futures analyst. The section begins by asking why should we use analogies? Then we turn to
the question of how do we create useful analogies, or where do we find societally meaningful
analogies? And then finally, we think critically about the benefits and drawbacks of analogy, as
revealed by a plentiful application literature.
We summarize our position by offering our first analogy: weather forecasting as an analogy for
forecasting and for future-oriented technology analysis. Weather forecasts today are frequently
inaccurate, but they are much better than 30 years ago. Including satellite data and computer
models has extended our ability to see the future weather. Improving foresight techniques could
likewise offer the value of improved prediction.
3.1 Why Use Analogies?
A future-oriented technology analyst might therefore also be able to anticipate the process of
discovery or invention if their selection of analogies were also fortuitous. That is, if the analogy
was constructed on the appropriate essence of science and technology, made apparent through
domain knowledge or expertise. This also might be furthered through the use of expert opinion
techniques in forecasting (Porter, Roper et al. 1991).
Most would agree that accurate foresight would be very valuable. Sadly, the track record of
those who attempted to peer into the future is littered with failures. In one example, Linstone
(2002) offers a list of 14 significant, unforeseen events in the forecast for a single company.
Some see the answer to forecast inaccuracy is to forgo forecasting and instead be flexible, put
much greater emphasis on designing adaptive strategies and policies (Kwakkel, Haasnoot et al.
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2014). This approach is willing to forgo any efficiency gains possible in adopting longer term
strategies in exchange for the flexibility of a shorter term policy, as found, for example, in a real
options approach. Ultimately, “managers who pay attention to their own analogical thinking will
make better strategic decisions and fewer mistakes (Gavetti and Rivkin 2005).”
3.2 How Can the Analyst Create Analogies?
Several general purpose techniques of future-oriented technology analysis might be useful for
analysts seeking useful analogies for the purposes of forecasting and analysis. We may
subdivide the process of applying and using analogies into three procedures:
1. the search and selection of source domain or domains,
2. the comparison of the source domain to the target, and
3. the evaluation of fit between source domain and the target domain.
If we agree with Hofstadter and Sander (2013) then most analogies are made instantaneously
and with little deliberation. Why then a three step method for the analyst? We argue that it is the
analysts responsibility to engage in slow thinking and deliberation to gain the best out of
analogous reasoning, and so as not to mislead potential users of the analogy (a point which we
return to below). In the following paragraphs we consider how existing future-oriented
technology analysis techniques can be used to good advantage when creating analogies.
Different techniques are suggested for each of the three steps as noted above.
Creativity might be best at the first of the three processes – searching for and selecting
appropriate domains from which to construct an analogy. Porter and co-authors treat analogies
and creativity as if they are synonymous; here we consider creativity as a means to the ends of
creating productive analogies. Suggested techniques include checklist procedures and random
words as a trigger for free association (Porter, Roper et al. 1991). The offer general habits of
thought as well for promoting creativity, including suspension of disbelief, and lateral thinking.
Morphological analysis might be best suited for the second procedure of building analogies –
comparison of source and target domains. Morphological analysis is described in the forecasting
context by Ayres (1969). Porter and co-authors also describe techniques of fractionation and of
morphological analysis, which they again group with general creativity techniques (Porter, Roper
et al. 1991). Fractionation involves breaking problems down into their parts, while morphological
analyses entail finding whole part relationships. Challenging current structural relationships
through the deliberate reversion of inversion of relationships can also be used productivity.
Morphological analysis is described by Zwicky (1969); Altshuller also describes the role of
general principles and systematic techniques for fostering engineering creativity (Altshuller
1977). His work is also notable for reverse engineering processes of technological
recombination given patents (Altshuller 1999).
The third procedure of building analogies – the evaluation of fit, requires a more complex
examination. Indeed there are an established set of techniques for addressing the social
constructivist and group decision-making characteristics of foresight activity. Porter et al. (Porter,
Roper et al. 1991) for instance writes about group decision making procedures; Linstone
(Linstone 1981) discusses the importance of adapting multiple perspectives.
Alternatively, if we are not creating our own analogies as analysts, then we may be seeking
them out in the real world. Given the omnipresence of analogies in public dialog and political
rhetoric, the press is also vivid source of potential analogies which can be mined using content
analysis or other techniques (Krippendorff 2013). The discovery of such analogies “in the wild”
might be important precursors of changes in social or political thinking.
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Regardless of the specific techniques used for developing analogies, it is fruitless to hold out for
the perfect analogy. Any analogy will entail building a network of features, some of which will be
similar, and others dissimilar. As the previous review of use of analogies reveals, it is far better
to select and adopt multiple analogies, using each when and where they are appropriate, rather
than adopting a single analogy for all purposes.
3.3 What are the Benefits and Drawbacks of Analogies?
In keeping with Linstone (2002) we argue the use of analogy allows moving beyond the limits of
narrow extrapolation and thus can offer improved potential for forecasting when facing “the
chaos phase.” In our view analogy offers the greatest potential to overcome any “inherent limits
of predictability” because it is furthest removed from the constraints of extrapolative methods.
Many contexts provide other examples of show the valued added by adopting a new, contrasting
perspective, as can be provided by reference to an analogy. The structure of benzene was
unknown and the ratio of carbon to hydrogen seemed incorrect. The German chemist Kekulé put
forth the ring structure of benzene after a dream in which he had the image of a snake bitting its
own tail. Here using the analogy of a ring suggested a reframing of the data and led to the
discover of the correct chemical structure. This established the chemical field of aromatics. At
the core of Kuhn’s Structure of Scientific Revolutions is the pattern of research moving forward
gradually, with much activity producing modest gain, when then at some point a different framing
of the situation, a paradigm shift (e.g., relativity; E=MC2) refocuses the data yielding new
interpretations and substantial forward progress.
In order to reach and compel the public analogies must be highly familiar as well as emotionally
laden: “because while they often operate unnoticed, analogies aren’t accidents, they’re
arguments – arguments that, like icebergs, conceal most of their mass and power beneath the
surface. In many arguments, whoever has the best analogy wins (Pollack 2014).” And yet,
despite this many compelling analogies actively mislead and provide a poor basis for future
action.
As an example of this stream of research that began in the 1980s explored the use of analogy in
teaching (Gick and Holyoak 1980, Spiro, Feltovich et al. 1988, Holyoak and Thagard 1989). We
believe this work has not previously been referenced in the foresight literature. Spiro studied
medical students and observed mistakes they made in applying analogies that had been used in
teaching. Their concerns include “the use of analogies in learning is far from straightforward and
surprisingly often results in deeply held erroneous knowledge.”
As an example of potentially creating erroneous knowledge the vascular system of the human
body can be described by an analogy to home plumbing, a connected system of pipes through
which liquid flows. These two systems are different in that pressure in plumbing is nearly
constant, while pressure in the vascular system rises and falls with each heartbeat. They
observe that despite medical students full awareness of the systolic and diastolic pulse, they
regularly misdiagnose pathologies by applying the plumbing analogy.
In summary, analogies offer a mix of positive and negative features. Analogies best enable
thinking at the “chaos phase of new technologies.” And analogies are especially valuable in
enabling decision-makers to adopt a new and contrasting perspective. Analogies often speak to
the public. If they are particularly fortuitous and build on the genuine essences of things, using
real domain knowledge, they may actually presage scientific discovery and invention. However
analogies also hide information, and may cause erroneous knowledge to become embedded
and deeply held. Given this mix of benefits and drawbacks, the concluding section of the paper
considers where analogies may be best employed in future-oriented technology analysis.
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4 Conclusions: Employing Analogies
In this final and concluding section we explore an approach which favors the need for
forecasting and foresight. We accept that detailed, highly-accurate prediction will often remain
beyond our reach. At the same time we believe technique improvements are possible that can
add substantial value for decision makers. But analogies can be misleading or even fraudulent.
How can we assess useful analogies, and discard the misleading or irrelevant ones? How can
we assess the value than an analogy offers?
4.1 Types of Analogies in Future-Oriented Technology Analysis
Because the potential realm of analogy making is so broad, it is helpful to be more definitive
about analogies when developing new analogies for future-oriented technology analysis
purposes. In the future-oriented technology analysis domain the analogical comparison is
typically drawn from a historical instance to some new target for which descriptions of a future
state is desired.
An immense range of possible types of analogy exist as shown in Figure 1. Analogies may be
stories, fables or vignettes. They may also be case studies. Taking the analogy still further along
the continuum, simple patterns of social or technological behaviour may be analogy. And then
finally a full-fledged model or model archetype may serve as an analogy. At this point the
continuum of analogies more closely approximates existing modelling and simulation techniques
in the future-oriented technology analysis literature.
Figure 1. Analogies, their Verification and Structure
In figure 1 there are two axes – one of structure and constraint, and one of verification. The
structure and constraint axis describes the comparative sophistication of the analogy. Some
analogies are quite basic, while others have many essential components which work together to
determine a final results.
The second axis is of verification,. We adopt the notation from simulation literature where
verification is internal assessment of a model, does it accurately transform inputs to outputs, are
the equations correct? Validation is external assessment, does the model represent the
intended real-world system from which the model is abstracted? Verification is a necessary but
insufficient condition of valid output; a perfectly verified model may be invalid. To the extent
verification of a source analogy is indeterminate, the potential for valid analogy conclusions is
compromised.
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We can also fruitfully consider the boundaries of the analogy technique with other futureoriented technology analysis techniques as well. Another productive dialectic would be to
consider using analogies in tandem with expert opinion, to produce potentially highly salient
analogies which nonetheless exist in a sort of private language. Alternatively, one could build
analogies in tandem with a group. Such analogies if winnowed by an effective group decisionmaking procedure may come “spring loaded” to make a big impression on subsequent listeners.
Also consider the comparison of analogies to the other technology forecasting techniques as
shown in figure 2. Most forecasts adopt an extrapolative approach, data such as time series are
extended into the future by some model (e.g., line, curve) making it inherently impossible to
deviate from any signal in the data. Analogy is near the other end of the spectrum.
In applying analogy, there is a reference to some source domain; this is not an extrapolation of
data in the current target domain, but rather a ‘distant search’ (e.g., the growth in demand for
hybrid autos [target domain] will follow a pattern like the growth in demand for televisions [source
domain], an S-curve). Analogy’s ability to drawn broadly from many domains of possible models
to apply in the target domain - rather than the extremely narrow ‘near’ search adopting
extrapolative models - suggests it truly contributes to ‘foresight’.
Figure 2. Ordinal ranking of technology forecasting techniques along a spectrum. These
techniques have core differences, but in implementation may not be mutually exclusive (e.g.,
Delphi participants may use both extrapolative and analogy thinking approaches in answering
questions.)
4.2 Valuable Use of Analogies
The value of analogy in foresight can be realized in at least three situations -- novel situations,
turning points, and familiar contexts. We consider each of these cases in turn, with short
examples of how analogies helped in each.In novel situations, there will be no established data
record upon which to base extrapolation. Here analogy may offer something. It may not offer
much, but the saying is, “A drowning man grasps the smallest of twigs” and even small insights
may suggest improvements to decisions. The recent Ebola outbreak (example 1, below) is one
example of a novel situation.
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Example 1: The Ebola Outbreak
The Ebola outbreak in 2014 is novel in the sense that all previous Ebola outbreaks
were stopped before reaching the current size. At the time of this conference, slightly
more than 10,000 cases of Ebola have been recorded in the ten months of the current
outbreak. What will be the future path of this epidemic? Some form of S-curve is the
common analogy used to forecast epidemic \growth. There is much empirical support for
adopting this analogy to forecast epidemic trajectories. The early phase is modelled as
exponential growth, and there is some upper bound which is approached asymptotically
in the late phase. In quantifying use of this analogy, the estimate of the upper bound is a
crucial unknown, What source can we use for estimating that bound? What level of
investment should be made in fighting this outbreak now?
We know that widespread epidemics are possible: the Spanish Influenza near the
end of WWI killed tens of millions. If that seems an appropriate analogy for an upper
bound estimate (attributes of transmission mechanism, treatment options, and capacity of
healthcare facilities would influence that judgment), then today we are a long way from
the point where Ebola spread will diminish. That is, we still in the exponential growth
phase and we can calculate that there could be an additional 10,000 cases added per
month in the near future, a number which has been mentioned by the U.S. National
Institutes of Health. Recent decisions by the Obama administration to substantially
increase the amount of resources devoted to fighting Ebola were likely influenced by such
projections. Note first, that the accuracy of this analogy remains unknown, but it is
influencing decisions of tens of millions of dollars. And second this type of situation where doing nothing may lead to fulfilment of a forecast of much greater deaths, and
taking action may hopefully lead to making the forecast inaccurate by arresting disease
spread is commonly encountered in policy making. Therefore our claim that small
improvements in foresight can have great value. Note also the political complications
implied by this – actions which avoid the high death count will allow criticisms of
preventative actions as wasteful when the forecasted deaths do not in fact occur.
Turning points (or transitions) are the situations in which analogy can offer its greatest value.
Here extrapolation of the past (assuming “all things equal”) by definition leads to error, and the
speculative element of analogy (Figure 2) allows this approach to suggest a different frame and
influence decisions. The turning point character of analogy use is discussed in example 2.
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Example 2. Oil prices 1980s.
Oil prices rose about 4x (from about $3/barrel to more than $12/ barrel) in in
1973-74 in the first concerted OPEC action. They rose again in 1979 following the fall of
the Shan in Iran to about $30 per barrel. Forecasts in the mid-1980s expected that oil
prices would continue to rise in the next decade. Extrapolations of the 1970s data
supported continually rising prices.
Marchetti (1980) observed dramatic swings in energy prices that occurred in
waves of approximately 50 years duration. He forecast that, consistent with the longterm historical pattern, oil prices would decline and remain low for the next 20 years, a
forecast that turned out to be accurate. This example strongly demonstrates our claim of
the potential value of analogy. It was a forecast that was in stark contrast to the majority
of forecasts, which were based on extrapolation of trend data from the previous 15
years. Marchetti derived his forecast using an analogy to a long-term, but vague pattern.
A forecast that oil prices would be flat or declining would change investments in power
plants that totalled hundreds of billions of dollars.
Analogies can even help in familiar contexts where there nonetheless remains large
uncertainties relative to potential improvements in foresight. Familiar contexts often contain
uncertainty and using past experience as analogy can provide value. Shepperd et al. (1996)
addressed the problem of forecasting the cost of software projects. They developed a software
tool (ANGEL, short for the “analogy software tool”) which allowed users to forecast project cost
using analogy to previous projects. They conclude that this outperformed expert judgment. Still
another example is forecasting the Great Recession (example 3, below).
Example 3: The Great Recession beginning in 2008.
The magnitude and duration of the Great Recession has been greater than any
recession since the Depression of the 1930s as indicated in Figure 3. We consider the
Great Recession a turning point because economic downturns for the past 70 years have
all been recessions of short, shallow impact relative to a depression such as the 1930s.
We believe the Great Recession is qualitatively different, and represents an event of such
magnitude, that reference to the other recessions (Figure 3) is deeply misleading.
However more recent recessions have been by far the dominant source for
forecasts on how long the Great Recession will last. The US congress debate on the size
of economic stimulus the government should fund concluded that only “shovel ready”
projects (those that were already planned and ready to start) could be funded, any greater
investment would be wasteful because -- using the analogy of post WWII recessions to
estimate the length of the Great Recession -- the Great Recession would end before any
other projects could be made ready.
Another explanation that we accept is that Republicans wanted the recession to
be more, rather than less painful, with the expectation that Obama would be blamed for
any negative voter sentiment. We point out that these explanations are not mutually
exclusive, and that even if the congress used the “small stimulus-shovel ready” argument
only as a facade to support their low stimulus decision, it remains the use of an analogy in
decision-making.
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5th International Conference on Future-Oriented Technology Analysis (FTA) - Engage today to shape tomorrow
Brussels, 27-28 November 2014
Example 3: The Great Recession (continued)
Figure 3 shows that a forecast of Recession length made early in 2009, using
recessions since WWII as analogies, might conclude unemployment would return to
normal levels within 15 to 30 months (at the FTA conference in 2014, we are now nearing
72 months and counting).
Figure 3. US unemployment change data shows the Great Recession (red line) has had
substantially longer and deeper impact than other post-WWII recessions. X-axis is
months from recession start.
4.3 Employing Analogies in Future-Oriented Technology Analysis
This paper has revisited an old technique of forecasting and foresight. Although the technique
has slumbered in the future-oriented technology analysis literature, research has been quite
active elsewhere. Among the sources examined, we reviewed literature from computing,
cognitive science, psychology and pedagogy. Other sources have included politics, law and
rhetoric. The role of analogies in creative thinking, and especially in science, technology and
innovation has been receiving increasing amounts of attention at late.
In addition to this review, we thought critically about how analogies may be created using
established future-oriented technology analysis techniques, as well as the similarities and
differences between analogies and these alternative techniques. The review of analogies
reveals that analogies employ a powerful mechanism of thought which is both productive, and
also dangerous. Nonetheless, certain critical periods of time almost mandate the use of
analogies since there is so little base to otherwise reason about the future. We hope therefore
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5th International Conference on Future-Oriented Technology Analysis (FTA) - Engage today to shape tomorrow
Brussels, 27-28 November 2014
that this paper has helped revive interest in a valuable if lagging technique, and also provided
some new and novel insights about how this technique can be best deployed in a future-oriented
technology analysis engagement.
Several agenda items for future research are immediately suggested by the review and findings
of this paper. First, it would be useful to actually apply analogical reasoning to a new technology
at the early transition stage. Existing work such as Geels (2002) may actually be doing just that;
in which case it would be useful to diagnose and critique the work from an established basis of
methodology. Second, such a case demonstration could help future researchers also seeking to
use analogies in their own work.
The research highlights the benefits of using multiple analogies. It would be useful therefore to
examine multiple competing analogies for a single case, mapping out which features of the
domain are best covered by which analogies. A synthetic future might therefore be constructed
which combines the best features of various analogies. This future may also enable decisionmakers and stakeholders to think more vividly, and more flexibly, about their own futures.
As a final note for future research activities, more work in using analogies with groups of
participants or stakeholders is much needed. Empirical evidence of how real people are thinking
about the future, and the strengths and weaknesses of their own native analogies would
undoubtedly be an insightful piece of work. Such work might be highly relevant for efforts to
enhance public engagement in science and technology. This work might also contribute to the
emerging literatures on participatory policy making, and participatory design.
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Brussels, 27-28 November 2014
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