An evolving glossary of terms useful to UPGO strategic foresight practice, education and research. The original version was authored by the late polymath futurist Dennis List of Audience Dialogue. Dennis made many contributions to our field. Among them is a variation of scenario planning, Scenario Network Mapping, as well as a methodology for foresight method development, for his PhD thesis in 2005. Before he passed away in 2007 he made his glossary available to our ASF nonprofit for our wiki, GlobalForesight.org. The glossary is now maintained by Foresight University (4U) faculty.
Have other foresight terms to suggest? Wording changes? We encourage you to email us, or add them in the comments below. Thanks!
Key Terms, in Alpha Order
3P’s foresight model / Three P’s foresight model
Probable, Possible, and Preferable (“3P’s”) futures. Widely considered to be three basic types of futures. First championed by the great 2oth century futurist Alvin Toffler, in Future Shock, 1970. Further developed by futurist Roy Amara, at Institute for the Future in 1981, futurist Graham May in The Future is Ours, 1996, and futurist John Smart, as the Evo compu devo model, in 2008. See also DCM foresight skills model, for a skills-based version. Depicted as an Evo compu devo triangle by futurist John Smart. See Futures triangle and Universal evolutionary development. The base of the 3P’s triangle is possible (evolutionary, unpredictable) foresight and probable (developmental, predictable) foresight, and the peak is preferable foresight.
80/20 rule / Pareto principle
The observation, from the nature of power law distributions in many natural systems, that 20% of the distribution, the “fat head”, has 80% of the population, wealth, performance, or other impact. It’s also the idea that 20% of the effort will get you 80% of the results. 20% of the people in any organization or society do 80% of the work. These folks are called Pareto’s vital few. Find them and support them! It’s often foolish to spend 4X more effort trying to get that last 20% of results. Stopping when you’ve gotten Pareto’s return, having spent the right 20% of effort early in a project, is called “satisficing” versus “optimizing.” Satisficing is something perfectionists and completists need to learn to do, in life and business. It may satisfy perfectionist compulsions to go after that last bit of return, but it’s usually a waste of our precious time and energy. But don’t write off the 80% as useless. Far from it. The “long tail” of strategies and ideas is a measure of the diversity of the system, and diversity is a very powerful defense strategy. There are times, as when environmental conditions change, or when that rare strange problem comes up, when your only good solution will come from the long tail. For example, the long tail of technical and nonfiction books in the bookstore may not sell very many titles versus the “fat head” of Harry Potter and the latest big name author’s work, but that knowledge is priceless. Both the fat head and the long tail have their place, and good leaders care for and use them both well. To understand some classic implications of power laws for innovation, also the Innovation 80 / 20 rule.
95/5 rule / Evolutionary vs. developmental change drivers
Developmental processes appear to comprise the small minority of genes that are active during an organism’s life cycle, yet they appear to be roughly equally as important to determining survival (adaptation) as non-developmental (evolutionary) genes and processes, which change unpredictably as organisms replicate and evolve. In some estimates, developmental genes comprise only 3-5% of an organism’s genome. These are highly conserved over time,they predict the life cycle of each organism, and they constrain the kinds of evolutionary (unpredictable, selective) change that can occur over time. The remainder of the genome appears much less conserved. As futurist John Smart proposes, this roughly 95/5 ratio between unconstrained, unpredictable, and bottom up processes, versus constrained, predictable, and top-down processes can be found in a wide variety of Complex adaptive systems in nature, society, and technology. See also Evolutionary developmental biology and Universal evolutionary development.
Accelaware / Acceleration awareness
The recognition that certain processes of change continually run faster over universal, planetary, and social history. As accelerating processes grow exponentiallly in power over time, understanding them is particularly important to long-term foresight. See also Accelerating change.
Certain processes of change continually run faster over universal, planetary, and social history. Futurist John Smart proposes that infotech and nanotech are the two most fundamental classes of such processes. See Chapter 2 and Chapter 3 for more. See also STEM compression and Exponential foresight.
The idea that there is not a single future, but a range of futures, all of which might occur at the same time in different environments or for different people, as well as a range of possible futures, which are influenced by human choice today. A pluralistic view of the future, generally accepted among futurists.
The history of what might have happened but didn’t. A great way to illustrate the power of choice in shaping the future. Also called a counterfactual. What if World War III had broken out in the 1960s? What if Napoleon had conquered the USA? What if Jesus Christ had never been born? These are Counterfactuals, and stories exploring them are alternative histories.
If you can’t predict the future exactly, what’s the use of strategic foresight / futures studies? Answer: even if you don’t know what’s going to happen, or when it’s going to happen, you can at least anticipate (generate expected probabilities) for a range of possible futures, allowing you to better prioritize, strategically evaluate, manage, and prepare for them.
Anticipatory action learning
An extension of action research into the area of futures studies – pioneered by Tony Stevenson and Paul Wildman, of Australia.
A method of revealing underlying assumptions – proposed by Mason and Mitroff in 1981, which asks people to list their own assumptions. However, in our own experiments with this method, only trivial assumptions surfaced. As they say, “the fish cannot see the water.” We’ve found this works better when two people, from different backgrounds, engage in a dialogue, and each is asked to discover the other’s implicit assumptions. We can also surfacing assumptions by caricaturing their extremes.
Autocratic Triad (aka the “Three Mons”)
Control of the individual in three kinds of autocratic ways, via politics (monarchy), commerce (monopoly), and religion (monotheism), introduced during the decline of the Roman Empire. Scholars have theorized that the special stability of this triad, and its triple autocracy, was primarily responsible for the Western Dark Ages lasting as long as they did. Prior to monotheism, at least the individual’s higher thinking wasn’t captured. Afterwards, all dimensions of the human mind and body were on a tight leash, one that took more than a millennium to unwind again, in the Enlightenment. Monopolistic mass media has arguably risen to become a fourth Mon, or system of autocratic social control, since the emergence of Radio, then Television and Film, beginning in the 1930s. That monopoly has been breaking down with the emergence of the web in the 1990s, and it will further erode with the emergence of personal sims in the 2030s. Thus mass media monopolies, while important today, do not have the historical importance or longevity of the first three mons.
The way a living system continually renews itself, in the process continually redefining the parameters of its seed (replication system), its organism (body) and its environment (see SOE partitioning). From the Greek term for “self-production.” Another way of putting this is that an organization’s identity is defined by its relationship with the outside world. For example, a business might realize that it needs to grow in a certain direction in order to remain viable. From Chilean biologists Maturana and Varela.
B-curve / life cycle curve
A generic change curve, seen in many types of biological systems, that involves an S-curve of growth followed by decline of capacity over time, and ultimate recycling and death. Looks like a “b” laid down on its long side. The impact of an individual over time, or any idea or system that eventually goes extinct or gets recycled, follows such a curve.
People born between the end of World War II and the early 1960s (when the advent of the contraceptive pill dramatically lowered the birthrate in Western countries.) Often just called Boomers.
Working backwards from a possible future state to determine how it might unfold.
Beginner’s / Bellwether / Sentinel Foresight
This concept is closely related to the occasional, well-known yet still poorly-evidenced psychological phenomenon of Beginner’s luck. The first time some individuals encounter a new process, or engage against experts in an activity, they can perform significantly better than in later rounds, sometimes even initially beating those with greater skill. I’ve seen this in chess. Likewise, the first time a individual, group, or a society encounters a new issue, process, trend, or emergent system, we often generate particularly good long-range foresight. Many examples of Beginner’s Foresight can be found in both fiction and nonfiction articles, books, and news reporting.
Very closely related (and usually indistinguishable) is the concept of Bellwether Foresight. Some prescient authors, first seeing an event or process that they mentally characterize as both “new” and “significant”, use that new knowledge as a Bellwether (also called a leading indicator, precursor, or sentinel event or insight), to see deeply into what must, could, or should happen (probable, possible, and preferable futures). Right after the bellwether event occurs, some great foresight work is produced. But for several years afterward, many authors will lose that early clarity, getting distracted for years or decades in the details of the subsequent local context, and all the complex reactions to the bellwether events, many of which are doomed ultimately to fail, if they are evolutionary, not developmental.
A good example is the social foresight found in several articles in Time magazine in the days after the first military use of an atomic bomb, August 6, 1945. Authors of those early articles, with the deeply disturbing new event clearly in mind, realized we were now in an era of weapons we no longer wanted to use, that we had a high probability of an unproductive arms race ahead, and that prioritizing international cooperation on nonproliferation could avert that dystopian future. Later articles on the topic became much more tainted by Cold War rhetoric and biases, and it took decades for most of the writing on nuclear weapons to again get that early clarity. We’d clearly seen what needed to happen on first exposure, then we got diverted by our own biases and self-serving stories. Another good example is Frank Fukuyama’s call in in his prescient book on political foresight, The End of History (1992), when he argued that Western liberal democracy is the obvious endpoint, or developmental attractor, for biological humanity’s sociocultural future (though he did not use the biological qualifier, or the evo devo language). This book was a follow-on to his prescient article, The End of History? (PDF) published in The National Interest in the Summer of 1989. The dramatic collapse of the Communist government in Poland that Summer, due to sustained mass political activism by the Solidarity trade union and workers movement, and the installation of a new Solidarity-led coalition government, signaled how weak and outmoded the old communist order had become. Fukuyama used this bellwether, along with new weaknesses in the Soviet Union, to clearly see a much wider set of coming sociopolitical changes ahead.
Security expert Richard Clark offers the term sentinel personalities, to define people who are driven see what’s coming next. His book with R.P. Eddy, Warnings: Finding Cassandras to Stop Catastrophes (2017), focuses on the dystopic side of sentinel events, looking at past examples of people who accurately foresaw catastrophies, then turns to seven potential future catastrophes, presently told by seven “Cassandras”, that he considers particularly worthy. I don’t consider most of these sentinel stories to be nearly as dangerous as the personalities think they might be, but all of them do pose some risk, and we are certainly not preparing for any of them as well as we could. Works like these are very smart ways to try to improve foresight, and convert evidence-based fears in to preventative action.
A good foresight scholar recognizes that beginners, bellwether, or sentinel foresight is constantly happening all around us, and they will go to the earliest sources they can find of discussion of any topic to see if any Beginner’s/Bellwether Foresight was involved. Bellwether Foresight occasionally also crops up in client foresight exercises (Wargaming, scenarios, forecasting) the first time a strategy group is exposed to a new idea or challenge. Good documentation of such exercises can help capture those early insights, if they occur, and they can help keep the team from getting lost in the weeds in subsequent work, and having to “reinvent the wheel” slowly and painfully later.
Bellwether / Sentinel
An event or information that is recognized as a signifier of things to come. To remember the term, think of a village ringing a bell every morning, to signify to the villagers what the weather forecast is for that day. A bellwether is also a region or social group that adopts important trends earlier than most others. For example, it is often said that the Nordic democracies are a bellwether for the other Western democracies, as they institute inevitable social reforms years or decades ahead of the rest of us. California is also called bellwether state of the USA, and Silicon Valley a bellwether in digital futures, because many trends appear in these regions or groups first.
One danger of such assumptions is that bellwethers can change. Try to imagine:
(a) a cosmopolitan place, which is attracting well-educated young people.
(b) a political and social climate that doesn’t hold back change.
(c) a conduit for news to the rest of the world (because a trend can’t be a precursor unless people elsewhere become aware of it).
(d) a thriving arts scene: permitted by (b) and encouraging (a) and (c). For example, in the early 21st century, Ireland qualifies on (a) and perhaps (c), Finland on (a) and (b) but probably not (c). Other possibilities are New York (still?), Hong Kong, and Prague.
Compare to similar terms Precursor and Leading indicator.
This term is normally used to imply that the diversity of plant and animal species should be maintained, and that extinction is undesirable, because you never know when a species might be useful. The idea can be extended beyond its biological reference to human cultures and languages. Their biodiversity might be important too.
Boundary spanner / connector / networker
People who pass information from one type of social group to a different type are boundary spanners. Connectors / networkers are a similar, people who know and keep in touch with many people. Such people promote diffusion of information. Social networks and smart agents are increasingly acting as proxies for such people, vastly growing the speed and scale of diffusion.
The idea, often expressed in writings on chaos theory, that small changes in one part of a system can produce unpredictable large changes in another part – thus a butterfly flapping its wings in South America might trigger a snowfall in New York.
People seem impelled to assign causes to anything that happens: this seems to be some kind of deep psychological need. But if they assign the wrong causes, this belief can be difficult to change, and sometimes leads to bloodshed – for example, when one social group blames another for causing problems. Think of the Israelis and the Palestinians, the Catholics and Protestants in Northern Ireland, the Hutus and the Tutsis in Rwanda, and the Catholic/ Orthodox/ Muslim struggle in the former Yugoslavia. Causal attribution is a powerful force – so can it be reshaped? (See also fundamental attribution error and ultimate attribution error.)
Causal layered analysis (CLA)
A futures analysis approach developed by futurist Sohail Inayatullah: that the forces driving history can be subdivided into a number of layers, operating at different layers of social consciousness. He distinguishes four levels: most superficially, the “litany” (as expressed by populist media). Secondly, social causes (with a more quantitative emphasis, as found in more academic literature). Thirdly, “worldview” and the cultural structures that support them. Fourthly, and least accessible, the layer of myth and metaphor: archetypes, the collective unconscious, with an emotional rather than intellectual emphasis. To understand forces shaping the future, we must consider all four of these levels. For more, see Sohail’s website www.metafuture.org
A scenario which describes a chain of events (probable or not) leading to some future. For example the futurist Herman Kahn in his book On Escalation: Metaphors and Scenarios, 1986 outlines chains of events that would lead to World War III. Backcasting is the construction of a chain scenario in reverse (from the future rather than from the present). Compare snapshot scenario for the more common alternative type of scenario.
A curve that charts the change in number, capacity, or performance change in the growth, development, or decay of some system over time. There are several generic types (generic change curves) and a broad range of possible individual types. See S-curve, B-curve, and J-curve for some generic types. See also linear change, exponential curve and superexponential curve definitions.
Misleadingly labelled: this is the concept that patterns which appear to be chaotic can be quite predictable, because a small change in one measure can lead to a major change in another. So if you understand the mechanisms, the apparent chaos disappears. Water changing to steam when it boils is almost an example of such “chaos”. See Butterfly effect. The book Chaos by James Gleick is a clear introduction to chaos theory.
A group of people, born during the same period. For example, the baby boomers are a cohort, born c.1945-1960. The term “generation” is sometimes used in a similar way, but a cohort can be much less than a generation. For example, people born in a single year are a cohort, but not a generation.
Conjecture / speculation
A thought about the future that falls short of a prediction. A low probability is implied: a conjecture is something that seems unlikely to happen.
Constructive technology assessment (CTA)
Anticipating the effects of a new technology by having meetings with a wide range of stakeholders, who foresee problems with the new technology and find improvements to it. CTA is not a specific research method, but an approach to sustainable technology development; a wide range of consensus methods can be used.
A future as seen from the past: the mainstay of much science fiction. What if World War III had broken out in the 1960s? What if Napoleon had conquered the USA? What if Jesus Christ had never been born? These are counterfactuals.
An economic theory of Joseph Schumpeter, which argued that less adapted firms and institutions must regularly fail, or be replaced, in order for healthy rates of innovation to occur. More generally, it is the idea that when there are limited resources available, and no easy frontiers to run to, we may need regular cleaning out of the old and less adapted systems and ideas in order allow room for the new to flourish.
Critical futures studies
A recent approach to studying the future, centred around identifying and questioning assumptions that people hold, sometimes unconsciously. This term is championed by Richard Slaughter, as well as Sohail Inayatullah, the developer of Causal layered analysis. Critical futures is related to (but different from) Integral futures studies.
A type of uncertainty that makes a major (i.e. critical) difference to the future of the entity being studied. Often related to a discontinuity. Used in dimensional analysis. Morphological analysis is in some ways similar.
To do cross-impact analysis, first list the main forces that can affect the future of the system being studied. Then compare every force on the list with every other, and ask “if these two forces happen together, will the effect on the system be about the same as if each happened separately, or more, or less?” The practical problem with cross-impact analysis is that if you think of 50 forces (a typical number, in many situations), that’s 1225 comparisons to be made (50 x 49 / 2). For 100 forces, the number of comparisons jumps to 4950. With such large numbers, it’s hard to find time to consider each pair in enough detail.
Cultural pessimism bias
Until recently we lived in a very dangerous world. So our minds must be at least somewhat environmentally selected to imagine threats and dystopias as our first reaction to novelty or change. Only reluctantly and slowly do we look for evidence of the converse, opportunity and progress. We need to notice that due primarily to accelerating science and technological advance, most of us no longer live in that kind of world. We must strive to better understand and aid the accelerating and evo devo processes that led us to this increasingly positive place, so that we can make it even better for everyone. For some of us, that will require getting out of environments (countries, companies, relationships) that are presently too pessimistic to allow us to flourish. Sometimes creative destruction (allowing the less adapted to fail, as long as the personal consequences are not too destructive) is the best way forward.
A form of social activism, hacking, graffiti production, and/or civil disobedience that seeks to disrupt or subvert dominant media culture and its mainstream cultural institutions, and seeking to foster independent thinking and ultimately, progressive change. Common jamming targets are rampant consumerism, institutional prejudice, manipulative corporate advertising, and other power structures. See Adbusters, founded 1989, for the leading magazine of the movement.
Some experts, such as the economist Kondratieff, believe in a theory of “long waves” – i.e. that economic cycles repeat themselves every 55 to 60 years. Though a lot of (retrospective) evidence has been amassed to support this theory, and some highly respected experts support it, I’m skeptical. Why 55 years, and not 45? Is it a “clogs to clogs in three generations” effect? If so, why isn’t the cycle length increasing in parallel with the growing generation span? To me, such data, without an explanation, is suspect. There are at least three different issues mixed together here:
(1) Do repeated economic cycles exist – or are the fluctuations of the world economy effectively random variation?
(2) If waves exist, do they have about an equal amplitude? (If not, how can you distinguish a main wave from a sub-wave – bearing in mind the principles of Fourier analysis?)
(3) Even if waves clearly exist, of about the same amplitude, is the periodicity roughly constant?
Discovering-Creating-Managing (DCM) foresight skills model
Discovering (or Predicting), Creating (or Envisioning), and Managing (or Guiding) the future. An adaptation of the 3P’s / Three P’s Foresight Model, using skills/actions. Discovering/ Predicting is about probable futures, what you expect to happen based on your knowledge of the world. Creating/ Envisioning is about bringing forth or imagining possible futures, which may or may not last or work out (like a new product in the marketplace). Managing/ Guiding is about preferable (and normative, or values-driven) futures. For more see Graham May, The Future is Ours, 1996 and John Smart, Evo Devo Universe?, 2008.
Making a numerical forecast more accurate by decomposing the figure into a set of separate trends. For example, Fred Collopy and Scott Armstrong (in 1996) decomposed an apparently random graph of annual highway deaths in the UK into two factors: traffic volume (which was irregularly rising), and death rate (steadily falling).
A way of estimating future measures by asking a group of experts to make estimates, recirculating the estimates back to the group, and repeating the process till the numbers converge. Often used for estimating when an event might occur – e.g. “In what year will the majority of households in OECD countries have broadband internet access?” Developed in the 1950s by Harold Linstone and Murray Turoff, and widely used, specially in Japan.
The philosophy of destiny: that the course of history is predetermined, and there’s nothing that anybody can do to change that. This leads to fatalism.
The view of history as a narrative, or sequence of events, with the implication that you are looking for causes in the chain. The counterpart of Synchronic.
The way in which an innovation begins with a small group of people, then gradually spreads to a wider population. The rate of diffusion often (roughly) follows an S-curve. See the work of Frank Bass, and Everett Rogers’ book Diffusion of Innovations, 5th Ed. (2003)
A common method of producing scenarios. This involves seeking the critical uncertainties – i.e. the two or three main dimensions on which the future under consideration is most uncertain, and creating scenarios around the extremes of those dimensions. Clear examples can be found in the free online book Window on the Future: A Scenario Planning Primer, Dale Hunscher, (2001).
A sudden historical change, making it difficult to compare what came before and after. The sudden extinction of the dinosaurs is an example. However, because people focus on the recent past, a discontinuity may not be noticed till well after it happens. Thus whether the dinosaurs became extinct in a month or a thousand years is not relevant to us now, and what we currently see as discontinuities may be seen by later generations as minor changes in a broad trend. Similar to a wildcard event. See also surprise and innovation (discontinuous).
A concept first used by accountants: that income in the future is worth less than income now. The higher your discount rate, the less willing you are to make long-term investments. In practice, many people heavily discount the future, such that a benefit now (to you, for example) is worth many times more than a benefit in a few decades’ time (to your children).
A broad term for any force causing change, whether brought about by persons, organizations, or STEEPS3 conditions.
A classic cognitive bias where we mistakenly self-assess our cognitive or foresight ability as greater than it is, and/or imagine our expertise as being wider than it is. This bias is not restricted to “a person of low ability” as Wikipedia’s current entry mistakenly states, but the D-K effect happens even to the most learned of us when we overgeneralize our abilities and/or our areas of expertise. See David Dunning’s Self-Insight: Roadblocks and Detours on the Path to Knowing Thyself (2012) for more on this problem, and strategies for getting a more accurate self-assessment, including our true current breadth and depth of expertise.
The opposite of Utopia – an account of an undesirable future. Novels such as George Orwell’s 1984, Aldous Huxley’s Brave New World, and Eugene Zamyatin’s We are considered dystopias – which makes them dystopic.
When complex results arise from a combination of simple causes. An idea much liked by chaos theorists, who like to build simple computer models and imply that reality is equally predictable. Though this may work for (e.g) predicting the shape of ants’ nests, it doesn’t work for human society, partly because of reflexivity. See also Self-organization – a very similar concept.
Emerging issue analysis (EIA)
Similar to environmental scanning, but tries to pick up trends much earlier in their lifespan – hence the name “emerging issues”. Futurist Graham Molitor has written a lot about this. The key to EIA is to find precursors: people, places, organizations, and writing that is ahead of the rest of the world. One of Molitor’s main findings is that new ideas often begin at the fringes of society, and slowly work their way toward the mainstream.
Caused from within. For example, if a manufacturer decides to stop making one product and make another instead, the change is endogenous if the decision is a completely internal one. But if they decide to change because the market for the old product was disappearing, the decision might be endogenous, but the influence would be exogenous (the opposite).
Environmental scanning / Horizon scanning
Also known as horizon scanning, often abbreviated to just scanning. A systematic method of looking for drivers that influence the future. The process can be passive or active, continuous or occasional. “Environmental” here is not restricted to the natural environment, but covers all types of environment. See STEEPS3 foresight categories model.
In the sense used by the French philosopher Foucault: the collective worldview of a particular culture, in a certain place and time. An episteme structures the way people think, and determines what is discussable. Not quite linguistic limitations, not quite social desirability, but something in between.
Event sequence analysis
Studying sequences of historical events to determine the extent of repetition. This area has been explored not by historians or futurists, but by sociologists. See pattern language.
Evo compu devo model
A view of complex adaptive systems as evolutionary, computational (intelligent) and developmental systems, pursuing three types of adaptive foresight. Proposed by futurist John Smart in Evo Devo Universe?(PDF), 2008. See also Universal evolutionary development, the 3P’s / Three P’s model and Futures triangle.
Evolutionary developmental biology / Evo-devo biology
A theoretical approach to evolutionary, organismic, genetic, and ecosystem biology which argues that evolutionary and developmental processes are both fundamentally important to understanding long range biological adaptations and change. See also the 95/5 rule.
Caused externally. For example, when an industry, or an area changes due to pressures from outside the industry, that’s an exogenous change. The opposite of endogenous.
A generic change curve, x(t) = ce^kt, seen in many types of physical systems when the growth (or decline) in number, capacity, or performance is a function of the number present at any time. Think of population growth in a resource-unlimited environment, or exponential decay. Also seen in the growth of velocity under a force (gravitational and other acceleration), and perhaps, in the growth in computing power in local areas of the universe over time (law of accelerating returns). The shape of exponential curves look the same at every point along the curve. Compare to J-curve / superexponential curve.
The awareness that certain processes of scientific, informational, technological, economic, and social change grow exponentially, often for long periods of time. For an application of this insight to management, entrepreneurship, and innovation, see Salim Ismael’s Exponential Organizations, 2014. See also Acceleration awareness and Accelerating change.
Elise Boulding’s idea that the “present” is not just the moment when you are reading this word, but extends several generations before and after that, perhaps 100 years from now in each direction. For geologists, the extended present might be plus or minus a million years from now. To think of the present as longer-lasting helps put our present time into a larger perspective.
A method used in forecasting – much the same as projection. If you drank one cup of coffee yesterday and two today, then you will drink 3 tomorrow (by arithmetical extrapolation: adding one each time) or 4 (by geometric extrapolation – doubling each time). You can do this with letters too. A little puzzle: what comes next, after A H I M ?
Think of a tree as having a trunk, that spreads out into a number of branches above and a number of roots below. If the trunk represents an event. the roots are the causes and the branches are the effects. Used in Midcasting, to create interlinked networks of event trees. This concept is an adaptation of the problem trees used in ZOPP.
Evo devo universe
An emerging discipline in complexity research, systems theory, theoretical biology, and astrobiology (see Development and Evolution, Stan Salthe, 1993 and Life’s Solution, Simon Conway Morris, 2004) that explores the relationship between processes of evolution and development at both universal and subsystem scales. The process of “convergent evolution” may be seen as a process of universal development at these scales, and much can be learned from the emerging science of evolutionary developmental biology and applied to universal scales. For more, see our Evo Devo Universe complexity research and discussion group, or my explainer article at the link above.
Evolutionary development (aka “evo devo” or ED)
A term used as a replacement for the more general term evolution, whenever any scholar thinks both contingent and stochastic processes (random within constraints) and convergent and statistically and collectively predictable processes, including replication (life cycle), may be occurring in any complex system. The hyphenated evo-devo is commonly used for living systems, most prominently in evo-devo genetics, and the unhyphenated evo devo can be used for the theory of any potentially replicating complex system (star, prebiotic system, gene, cell, meme (concept), behavior, technology), whether living or nonliving. See also universal evolutionary development. For more, see my explainer article at the link above.
…where X is a number, usually 10 or 20. It represents the increase in efficiency needed in rich countries’ use of the earth’s resources to attain sustainability a few decades in the future. When X is 20, it means we need to reduce resource usage to 5% of the present figure. It will have to happen – and due to the special nature of nanotech and infotech in our universe, this adjustment may be much less difficult than many acceleration-unaware folks presently anticipate. More detail at www.factor10-institute.org
The psychological counterpart of Determinism: the belief that the future will happen anyway, and there’s nothing that anybody can do about it. It follows that it’s useless to try and improve the human condition. The concept of fate is not quite so fatalistic: the endpoint may be predetermined, but the routes to it may not. See also Determinism.
The process by which the effect of an event can also cause that event. There are two forms: positive feedback (strengthening the event) and negative feedback (weakening it). Simple examples of feedback are hard with audio systems. If a microphone picks up the sounds from a loudspeaker that it’s connected to, positive feedback amplifies some of the sounds, and the result is a high-pitched screech. When an audio amplifying system works as intended, it uses negative feedback: the (loud) output signal of an amplifier is compared with the (soft) input signal, and automatically modified so that it becomes an accurate reflection of the input, but louder.
Field anomaly relaxation (FAR)
A concept developed by Russell Rhyne, used in morphological analysis. It involves a systematic approach to reduce the number of combinations of future possibilities to a manageable level, by excluding combinations that are implausible.
A scenario development method popularized by futurist consulting firm Global Business Network, and discussed in The Art of the Long View, Peter Schwartz (1996). Involves taking two “important but uncertain” dichotomies or dimensions of possible outcome, such as whether the economy will grow or not over the coming decade, whether individual actors or collective policies will have more influence, or whether virtual or physical firms will be more productive (that’s three, but only two of these would be picked to four-box the outcomes) and charting the four possible combinations of the two dichotomies/dimensions. Each combination is then made into a scenario, leaving four possible futures. See Dimensional analysis for more.
This method, developed in the 1950s by psychologist Kurt Lewin, compares the forces helping and the forces hindering a desired outcome. One set of forces tries to change the status quo, and the other tries to keep it. Identifying these opposing forces helps people to plan ways of dealing with them.
Predicting that an event will happen, to a defined extent, and sometimes with a defined probability. For example “there’s a 50-50 chance that at least 1 millimetre of rain will fall in this area tomorrow” is a forecast. Forecasts are usually applied to short-term futures – no more than a few years ahead. A forecast is considered to be less certain than prediction, but more certain than conjecture or anticipation.
Foresight / Strategic foresight
A broad term covering all methods of envisaging the future. These who do professional foresight usually consider it to include strategy that leads to action or decision, which is expressed in the phrase Strategic foresight. Thus forecasting alone is not enough to qualify as foresight, though it is a part of it. Compare with Future(s) studies.
Foresighter / Foresight professional
One who looks to and analyzes the future, for a client. If one also speaks or writes publicly about their analysis, they are typically also called Futurists (see that term as well) by many of their clients, whether they want that identification or not. Thus an investor, risk manager, forecaster, change manager, designer, entrepreneur, consultant, or life coach are all examples of folks who do professional foresight, so we can call them Foresighters / foresight professionals, but they may or may not be futurists, doing public-facing work. The foresighter term was coined by futurists John Smart and Andy Hines (though Andy does not yet use it) as a single-word descriptor for foresight professionals.
Improving our human ability to think about the future and to act effectively now to build a better future. Foresight development thus includes futures studies plus foresighted thinking and behaviors. Assumes that the human response to the future is both a mental/psychological skill that can be improved (like hindsight or insight) and a set of behavior habits (like organizing, predicting, planning, investing, insurance, etc.) that can be strengthened with study and practice. These are often divided into various skillsets (eg., CDM foresight skills model).
A psychological setting that gives specific meaning to a statement. For example, a child might be scared by a horror film, so a parent may say “don’t be afraid, it’s only a movie. ” Proposed by Gregory Bateson in “A theory of play and fantasy”, in Steps to An Ecology of Mind. When you are thinking inside a frame, and aren’t aware of it, you won’t realize that it can change. See also Reframing.
This common word is mentioned here because it actually has two major meanings, which could be called future-as-time and future-as-image. If you ask “when is the future?” the answer is that it’s some time ahead, but probably not this year. But if you ask “where is the future?” the present tense gives it away: it’s inside people’s heads, and as such it’s here right now. These two different meanings can cause confusion.
When you have mentally prepared for a situation in advance, you recognize the early warning signs (precursors) that you had anticipated. In that sense, you are remembering your earlier vision of the future. This enables you to quickly put your plans into action.
Future shock / future nausea
Being psychologically traumatized by the speed of change, as an individual, organization, or culture. Popularized in the 1970 book of the same name by futurist Alvin Toffler. Future nausea, coined by Venkatesh Rao, is a variation. Feeling or seeing change may not traumatize us, but it can make us feel nauseous, so we are tempted to remove its signals from our environment. See manufactured normalcy / manufactured stasis. That withdrawal eventually exposes us to even greater disruption from the future. Better to take your Dramamine, and keep scanning and interpreting the key changes constantly occurring.
The study of the ways in which the future or futures could happen. Note the plural: this makes it clear that at least some aspects of our futures are not predetermined. Futures studies is an academic discipline that reflects on how today’s changes and continuities become tomorrow’s reality. It attempts to analyze the sources, patterns, and causes of change and stability in order to develop foresight and to map alternative futures. Unfortunately, the plural “futures” causes some confusion with market trading of commodity futures. See also the alternative word Foresight.
A triangle is used to help discern the plausible future and develop strategy. The three points of the triangle represent the pull or image of the future (visual), the push or drivers of the present (quantitative) and the weight or barriers of the past (deep structures). There are dominant and contending images, with various weights. This method was developed by futurist Sohail Inayatullah; see Causal layered analysis. See also the (Toffler-Amara) Three P’s foresight model, which is also depicted as a triangle by futurist John Smart. The base is possible (evolutionary, unpredictable) and probable (developmental, predictable) futures, and the peak is preferable futures, which only intelligent systems can have. As both unpredictable (chaotic) and predictable (classical) physics appear to predate the emergence of life and intelligence in our universe, they are the base of the triangle. Intelligence, as it emerges, generates its own preferences (“computation”), creating the third corner of the triangle.
Beginning from the present, consider a number of possibilities that might occur. From each of those possibilities, what other possibilities follow? Continue this process, in the form of a diagram (similar to a mind-map), and it will take a shape resembling a wheel.
Architechture that does one or all of the three following things. It employs lateral thinking, it uses a futuristic style, or it solves a future problem. It can be very modern, futuristic, daring, sustainable, artificially intelligent, or otherwise inspiring. Term and definition coined in 2007 by Aaron Otrin, student at University of Advancing Technology.
A possible future. The term comes from Bertrand de Jouvenel, in The Art of Conjecture (1967), one of the earliest books on future studies – first published in English in 1967, in French a few years earlier.
Futurists usually look out more than just a few years ahead. Fortune tellers and prophets don’t qualify, because they have no scientific basis for their predictions. Most forecasters don’t qualify either, because their focus is short-term and focused on just a few measures. Futurists at the Acceleration Studies Foundation have described twelve common futurist types–six social types, and six methodological types. See Twelve Types of Futurist def. See Wikipedia def.
An older term for the study of the future, used mainly in the US around the 1960s. The “ology” ending has connotations that the future is scientifically predictable. These days, the terms “foresight” and “futures studies” are more preferred, and experts in this area are called Foresight Professionals or Futurists, not Futurologists.
Generations X, Y (Millennials), and Z (Centennials)
These are supposed to be people born in the decades after the baby boomers: perhaps the 1960s for Generation X and the 1970s for Generation Y (Millennials). A theory often mentioned by “pop futurists” and marketing gurus. It might be worth considering – if it could be established that all people born in a certain decade have characteristics in common that do not relate to their age group at the time. In other words, this is a type of cohort theory. It has much currency among marketers, but not much evidence yet. Be careful of overinterpreting the data.
Generic growth scenarios / SBJ scenarios / Dator’s Four Futures
Four classic growth alternatives for complex systems, told in scenario format: Continuation, Limits and Discipline, Decline and Collapse, and Transformation. The four outcomes are represented by different parts of the S-, B-, and J-curves. All four of these outcomes probably operate in various parts of complex systems as any major change occurs. Each is a very important perspective on the process of change. First described by futurist Jim Dator in 1979. Compare to Four-box scenarios.
A holistic perception of something – seeing it as a whole.
The opposite of foresight: the ability to review the past, to say what has happened, and why. Hindsight is a lot easier than foresight. Looking back into the past, you can say “How can anybody have been so stupid as not to see that X would happen?” But if you wanted to be critical about hindsight, you could dismiss it as post-hoc rationalization – reinterpreting history to suit your purpose.
Considering a system as a whole, not as a collection of parts. (That would be considered atomistic.) Atomistic views of you include your separate roles as (perhaps) employee, consumer, mother … – or as head, arms, torso … – or as skin, bone, blood … – and so on. Though there are many kinds of atomistic view, there is only one holistic view: of you as an entire person. Compare with gestalt.
A holon is a system that contains other systems, and is itself contained within a larger system. For example, you are a holon, because your body contains a number of systems (nervous system, digestion system, brain, etc) but you are part of a larger system (a family), which is also part of a larger system (a settlement) … and so on. This useful concept was originated by Arthur Koestler, in his 1967 book Ghost in the Machine.
Human Choice is Entirely Free Bias / Evolutionary vs Evo Devo Universe Bias
A very common cultural bias where we assume that we have fully free choice, and thus the potential to fully control our futures. Those who think that the universe, biological life, culture and technology are fundamentally evolutionary (contingent, random, unpredictable) also have this bias. But if the universe, life, culture, and technology are not just evolutionary, but evo devo, then we don’t have fully free choice. The 95/5 rule tells us we are largely free, particularly on a day to day basis, but there are also a significant number of processes and destinations that are not under our control. They are going to happen whether we want them to or not, and we ignore them at the cost of our own continued ignorance. See also IDABDAK stages.
The common developmental stages (Ignoring, Denying, Anger, Bargaining, Depression, Acceptance, Knowledge-Building) seen when individuals or groups react negatively to any potentially threatening or unpleasant idea, evidence, model, or theory that seems to require us to painfully update our conceptions of self or society. Seeing inevitable accelerating change (Chapter 2), and more generally, an evo devo universe, with developmental processes and destinations outside our full control (Chapter 3) are both disturbing yet highly future-important hypotheses that are still early in the IDABDAK stages, so a full science of either has yet to develop.
A mental picture of the future – similar to Vision. Popularized by futurist Fred Polak, in his foresight classic The Image of the Future (1973).
Imagining yourself to be living in a particular future scenario, and working through its implications. A method developed mainly by futurists Jim Dator and Wendy Schultz.
A confusing term, because innovation surveys use various definitions, as explained in the OECD’s Oslo Manual (90-page PDF). The key points are (a) that invention is not innovation, but the use of invention is, (b) innovation can be a process as well as a product, and (c) an innovation is new in its context, not necessarily in all world history. In the 1930s mirrors were not an innovation in Europe, but they caused much surprise in the highlands of New Guinea. Innovation can be considered either incremental or discontinuous. An incremental innovation is an improvement to an existing system – such as the move from videotape to DVD, while a discontinuous (or radical) innovation is something quite new – such as the move from nothing to videotape. But whether an innovation is classed as incremental or radical depends on the context you see it in. For television audiences, videotape was discontinuous. For recordists it was an incremental advance from audio to video, but for maintenance people the helical scanning technology made it discontinuous.
Innovation 80/20 Rule
In a classic dynamic based on power law effects in economic markets, most useful innovation (evolutionary change) usually comes first from the small to mid-sized players in a market, with the biggest players usually being counterinnovative and developmental (seeking to converge control, slow down, and patent and sit on innovation as long as possible). Fortunately, once a really useful new innovation emerges from one of the smaller players in the long tail, and that firm starts gaining market share because of it, the big players in the fat head have to respond by rolling out the innovation their own engineers and innovators have long wanted to do but have been prevented from doing by executive priorities. This big company behavior isn’t intended to hurt society, top execs in big companies are just doing what is smart for their firm. As long as economic concentration exists (a fat head or oligopoly at the top), big company incentives will typically be aligned to try to control and slow down innovation, maximizing current shareholder return. Their natural incentives, once they are big, is to more frequently act in counterinnovative ways themselves, and be on the lookout for small firms they can acquire once they prove they can grow market share. Apple, Google, and others show us there are big company exceptions to this rule (company culture can easily be more powerful than this market pattern), and society needs big companies to do big R&D and create scale, but the general rule clearly exists, and should be heeded. Because of this rule, those who care about innovation should always fund and patronize a good fraction of small firms and their early stage R&D and innovation. As a few of them will one day become large as a result, and that small-firm support, when they do good things, will keep the large firms accountable to the customer. A great books that explains how this rule works in the defense industry, where small contractors have a long track record of being more innovative, is James Hasik’s Arms and Innovation: Entrepreneurship and Alliances in the Twenty-First Century Defense Industry (2008).
Making change semi-permanent by building it into a country’s institutional structure: a step that some governments try to take, so that their policies will continue after they are voted out.
An approach developed by futurist Richard A Slaughter. The label “integral” applies to the use of individual and internal futures, as well as social and political. It emphasizes that the future is brought about as much by people’s inner (mental) worlds as by external events. You could say that it’s people’s interpretation of events, not the events themselves, that create “the future.” Slaughter, based on the work of Ken Wilber, distinguishes four types of “world” that create the future: subjective intentions, subjective culture, objective social, and objective behaviour. For a more detailed explanation, see Slaughter’s paper Knowledge creation, futures methodologies, and the integral agenda, and his website www.foresightinternational.com.au. See also Critical futures.
J-curve / superexponential curve
A generic change curve, seen in special physical systems, where at some point in capacity or time, known as the “knee of the curve,” the growth (or decline) in number, capacity, or performance rapidly turns a corner, and becomes effectively asymptotic (goes vertically up or down). See technological singularity for an example. Compare to exponential curve. Superexponential curves and processes may have exponential growth as a baseline, but with additional positive (or negative) feedback cycles that push the curve steeper than exponential. In The Age of Spiritual Machines, 1999, futurist Ray Kurzweil proposed that computer performance growth has been gently superexponential over the last 110 years because computer capacity seems to grow exponentially on average over time, yet as computer power grows in an absolute sense, the computer industry becomes more useful to society, and more resources (including people and computers) are used to generate the next generation of computers, pushing the growth superexponential.
Making a numerical forecast using expert judgment or intuition, not only mathematical formulas. (Though of course the assumptions built into those formulas also make them somewhat judgmental.) Much the same as subjective forecasting or qualitative forecasting.
Describes someone who is both apathetic and ignorant, mostly used as a derogatory term, and still obscure.
A measure, usually economic, that occurs after others. The opposite of a leading indicator. Examples of lagging indicators are unemployment rates (because unemployment rises late in the standard economic cycle), and official statistics (lagging in a different sense, because they can take years to be published).
Law of accelerating returns
The proposal by futurist Ray Kurzweil that Moore’s law of exponential growth in computer power and technological ability can be extended back to the beginning of computing technology. Whenever a technology approaches some kind of a barrier, according to Kurzweil, a new technology is invented to allow us to cross that barrier. He cites numerous past examples of this to substantiate his assertions. He predicts that suchparadigm shifts have and will continue to become increasingly common, leading to “technological change so rapid and profound it represents a rupture in the fabric of human history.” See Technological singularity.
A measure, often economic, that occurs before others. For example, the number of job advertisements and new housing approvals are commonly tracked and reported as leading indicators of economic growth. The opposite of a Lagging indicator.
The time it takes for something to happen, between planning and implementation. For example, the lead time for a major construction project may be many years.
Limits to growth
The concept that the world will run out of essential minerals before long. From a controversial and very alarmist book of the same name, Limits to Growth (1972) by Donella Meadows et.al. A type of Malthusian view.
Arithmetic change (y = Mx + b) in a system over time. Compare to Exponential change.
Studying history on the largest scale, looking at the whole world over centuries, and discovering broad patterns – some of which may continue into the future.
The theory of Thomas Malthus (c.1780), who believed that the world’s population would increase to the threshold of starvation. Compare with Limits to Growth.
Manufactured Normalcy / Manufactured Stasis
All the ways we prevent ourselves and our clients from seeing the constant change occurring around us. Seeing too much change can give us future shock (psychological trauma) or future nausea (sickening disorientation), so we may remove its signals from our environment. Our normalcy or stasis bubbles then bias us against seeing that the future is constantly arriving, due to all the constant changes happening right now. Good scanning and intelligence systems fight against this, without overwhelming us. Phrase coined by Venkatesh Rao.
A method through which social change occurs; a way in which a cause is expressed. For example, a well known mechanism is that the public becomes disturbed about an issue, and votes in a new government, which changes a law, which is generally obeyed. On a smaller scale are mechanisms that apply to individuals, such as Freud’s defense mechanisms.
A scenario-building method developed by Dennis List (of Audience Dialogue), part of scenario network mapping. It involves defining a set of possible futures, and a set of present situations (as seen by different actors), and using event trees to envisaging scenarios that create paths between the presents and the futures.
A person’s habitual way of thinking or perceiving, similar to worldview, but perhaps changing in different situations or roles. You can use one mindset as a driver and another as a pedestrian, but both will spring from the same worldview.
Creating a model of what might happen in the future, using a set of equations that relate inputs to outputs – a mathematical model, that runs on a computer. Special software is available for creating these models, or you can simply use a spreadsheet, setting up a series of formulas in cells that reference one another. The difficulty lies in verifying the assumptions embodied in the equations – often not a mathematical process at all.
The observation by Gordon Moore (co-founder of Intel) in 1965 that the number of transistors on an integrated circuit (and by proxy, its computing power) doubles predictably every 18 months. Later revised up to 24 months. This 24 month doubling has been seen in many measures of computing and network performance (memory, instructions per second, clock cycles, wired and wireless bandwidth, network speed, etc.), for longer periods in some cases than in others.
A way of looking at the future, by dividing it into logically exclusive possibilities. First proposed by the medieval theologian Ramon Lull. A trivial example: what will the weather be at midday tomorrow? Looking at all possible combinations of sun, cloud, rain, and wind, not all of these are possible, and some conditional predictions can safely be made: e.g. there will not be both sun and rain in the same place unless it is windy. The website of the Swedish Morphological Society (www.swemorph.com) has a lot of information on this approach. The Relevance tree and Field Anomaly Relaxation are related approaches, as is identification of Critical uncertainty.
Considering a problem from a number of different viewpoints, either the viewpoints of different actors, or using different metaphors. The TOP approach of Harold Linstone is one of the best known multiple perspectives methods: looking at something from a Technological, Organizational/societal, or Personal/individual perspective. T emphasizes problem-solving or production; P emphasizes process and action; and P emphasizes influence and power (P). The 1993 book The Unbounded Mind by Mitroff and Linstone is a great example of problem solving using multiple perspectives.
A normative scenario is one that describes a preferred future. (That’s the futurists’ sense of the word; it has a different meaning in psychological testing, where it refers to comparing individuals.)
Another way of expressing probability, often used in betting on sports. If an event has a 10% probability of happening, there are 9 ways it can happen for every 1 that it can’t, so the odds are expressed as “9 to 1 against”.
A set of assumptions that are so widespread in a particular society that people hardly notice they think that way. A paradigm shift is a change in a paradigm – often not noticed till it’s well under way. Paradigm shifts take years to happen – for example, the gradual acceptance of Darwin’s evolutionary theory, superseding religious creation theories.
Path dependence / Mode-locking
When it’s hard to escape from a state you’re in, due to some kind of lock-in effect. For example, once manufacturers and consumers are used to the arrangement of keys on the standard QWERTY typewriter keyboard, it becomes very difficult to get consumers of the more efficient, but differently-arranged, Dvorak keyboard: you are path-dependent (mode-locked). Mode-locking is sometimes used by physicists and related scientists to describe the phenomenon. When there is a competition between rival standards for a network, mode-locking / path dependency often occurs at some threshold of use, as Network effects / preferential attachment grow with the user community. Consider how the competition for various technical standards (e.g., Betamax vs VHS) eventually reaches a threshold where one standard is often chosen (perhaps the one with the most users, the most influential users, the most political or economic benefits, or some other such causal factors), as the network often doesn’t want to support the inefficiency of multiple standards in many competitive environments. Path dependency is another way of understanding that competitive environments, over time, naturally Consolidate to eliminate competition. Without some kind of political intervention, or continuous environmental change (as happens with the technology sector), all initially “free” enterprise industry sectors naturally drift toward oligopoly, then monopoly, and much lower rates of innovation.
A concept originated by the architect Christopher Alexander. It refers to a set of repeated patterns, on a wide range of scales, that apply in urban design and architecture. In the 1990s this idea was taken up by software developers, who found repeated patterns in the software they were writing. The same concept can be applied to time: though history never repeats itself exactly, the same general patterns occur again and again. Thus there can be a pattern language of events. See Event sequence analysis.
The condition of being multiple or plural. A condition in which numerous distinct ethnic, religious, or cultural groups are present and tolerated within a society. The belief that such a condition is desirable or socially beneficial. In philosophy, the belief that no single explanatory system or view of reality can account for all the phenomena of life.
Positive-Sum Game / Non-Zero Sum Game / Win-Win Game
A game or interaction which is designed in such a way that all participants can profit from it in one way or another. Either the number of desirable outcomes or the size of the whole resource grows by playing the game, so that even if if one’s percentage return decreases from year 1 to year 2, one’s absolute return may go up. Compare this to a zero-sum game where only one or a few can win, and where one’s getting more must always involve another’s getting less. Capitalism, democracy, fair laws, and moral/ethical codes are all often considered examples of positive-sum games that are “played” heavily by most societies on Earth today. Because playing these games (following their rules) makes certain resources more available over time, more people can “win” more every year compared to last year, even as they compete for the same things. Consider the way the size of a capitalist economy grows over time, or the way access to citizen services grows over time in a healthy democracy. See Nonzero, Robert Wright, 2001 for an excellent book on the way these games have evolved over human history and where they may go in the future.
Power poses / Power posture
Posture matters to one’s own sense of self, psychologists are now understanding. The way one sits, stands, and walks conveys both social signals, and signals to one’s own unconscious mind. Studies have shown that people who consciously improve their posture prior to and during interviews, talks, and performance evaluations rate themselves as more confident, and are also socially seen as more confident and able to lead. See Amy Cuddy’s TED talk, Your body language shapes who you are (2012).
When social trends happen earlier in some places, among some groups of people, the latter are called precursors – and studying them may provide leading indicators. Places such as Scandinavia and California are often considered precursors, as are well-educated young adults. Since the 1960s, the baby boomer generation has been a precursor group in a wide range of ways. Similar to Bellwether / Sentinel and Leading indicator. Used in Emerging issues analysis.
A specific statement that something will happen in the future. “It will rain tomorrow” is a prediction, and so is “If the wind is westerly and I sleep till after 8am, it will rain tomorrow” – but “it may rain tomorrow” is not a prediction.
The likelihood that an event will occur, on a scale ranging from 0 (no chance at all) to 1 (or 100% – totally predictable). Related to odds.
A set of expectations for a future that seems likely to occur – e.g. if world interest rates decline this year, the prognosis is that share prices will increase. A prognosis would be less certain than a prediction but more certain than a forecast.
A key term which implies that there is a positive directionality to certain types of change in complex systems. We each have our own theories for such directionality. The important thing is to develop a set of conditional hypotheses of social progress, and variables to measure, and to get started measuring them. Without this, you’re just another rootless postmodernist, with no understanding of the Big Picture, of the universal systems in which you are embedded, and which created you, from vastly less complex and adaptive precursors.
A term used in forecasting, similar to extrapolation. For example, if the population of a city was 90,000 last year and 100,000 this year, the simplest projection would be for a population of 110,000 next year. These days, forecasts often produce multiple projections, depending on various assumptions. For example, an assumption of high economic growth for the city might lead to a projection of 115,000, while low economic growth might give a projected population of 105,000.
A term used by French futurist Michel Godet to label a set of scenario-based methods he has developed for examining the future. La prospective (pronounced prospecTEEV , as in French) involves assessing the likely motives and actions of all actors involved in a situation, and produces numerical results.
Evaluating the success of a project that hasn’t yet begun. Can take the form of environmental impact analysis or social impact analysis – but cost-benefit analysis and cost-effectiveness analysis are not usually regarded as prospective evaluation.
A place that’s not perfect, or an ideal fantasy (utopia), one that is measurably better than the present, in some variables that we consider measures of Progress, from whence the term gets its name. (Progress “topos”, or place). Term popularized by futurist Kevin Kelly. Also sometimes called eutopia, a place which is “better” (eu-) than the present.
Much the same as judgmental forecasting, but focused on qualitative factors.
One reason why forecasting, in human affairs, often doesn’t work very well. If people know they are expected to behave in a certain way, they’re likely to change that way, and spoil the forecast. Stock exchanges have a good deal of reflexivity, with the investors trying to out-anticipate one another.
Looking at a situation or problem in a different way, or from a different point of view, often using multiple perspectives. For example, consider what’s missing from a situation instead of what’s present, or ask “How would a Martian visitor describe this to other Martians?” As people often can’t see their own viewpoints – particularly in an organization they’re immersed in – it helps to bring in an outsider – perhaps even a Martian. See also Framing and Episteme.
A hierarchical way of representing all possibilities in a situation. For example, a relevance tree for an organization in ten years’ time might be:
1. Will it exist or not?
2. If it exists, will it be in the same form as now, or a different form?
As each question has several possible answers, the tree splits into several branches at each question. If the logic is rigorous, every possibility must be covered. However the shape of the tree depends on the order in which the questions are asked, and this is reliance on judgment is this method’s weakness. See Morphological analysis, which is related.
Designating one of your mentees to help you understand their generation, and to actively challenge you, in private at first, whenever they think you are exhibiting attitudes, models, or behaviors that they consider outmoded. An excellent technique for staying open-minded, intelligently optimistic, and growing more nuanced, restrained, and wiser with age. Also see Unlearning.
Do you already know what risk is? But perhaps you’re not aware that it has two senses: the negative and the positive. Risks are usually seen as threats – the risk of something bad happening – but they can also be opportunities. To perceive risk only as a threat is a recipe for inaction: “We’d better not do X because it has risks.” A balanced view of risk can be more helpful in making decisions.
S-curve / Sigmoid curve / Logistic growth
Also called a Sigmoid or Logistic curve. A generic change curve, seen in many types of natural and social systems: they begin very slowly, gradually accelerate, then slow down again as penetration approaches 100% of the population. Think of population growth in a finite environment, adoption of consumer products, the growth in types of knowledge, etc.
Scanning / Enviromental scanning
Abbreviation for Environmental scanning, typically simplified to “scanning when there is no ambiguity. STEEP is a classic scanning framework.
Normally (in futures studies) this refers to brief description of a possible future. This is known as a snapshot scenario, because it’s like a snapshot or photo of the future. A slightly different meaning, also used in futures studies, is that a scenario is a description of the route from now to a possible future. This is known as a chain scenario. Unlike a forecast, which predicts future values of a few specific variables, a scenario is more descriptive than numerical. Dennis List’s Scenario network mapping is a variant of scenario planning, more similar to Causal Layered Analysis.
Scenario planning / Scenario learning
What do you do with scenarios when you’ve created a set of them? There are two main uses. You could use them to make a plan, perhaps to help with your strategic planning. Alternatively, you could focus on the learning process among the people who created the scenarios, a sort of fusion of scenario production and the Delphi method. Of course, many scenario ensembles are used for both purposes.
A prediction that helps itself to come true: for example, the belief that the price of a company’s shares will drop is often self-fulfilling. The opposite, maybe more common, is the self-defeating prophecy: for example, Herman Kahn’s books outlining scenarios for nuclear war (though not exactly prophecies) perhaps convinced US and Soviet government officials that nobody would gain from such a war, thus helping to prevent it.
The opposite of a self-fulfilling prophecy. A dramatic scare story, told by pragmatists, to try to induce difficult change and prevent impending problems. These are difficult to sort out from opportunistic dramas. See Drama bias.
Similar to emergence – what happens when a group of people (or animals) spontaneously organize themselves for some purpose, without any control from “above”. This covers everything from birds flying in formation to spontaneous independence movements.
Modelling with an element of time, using either a computer program or a game with human players. A series of events is simulated, to find out what’s likely to happen next.
A scenario, usually written in the present tense, describing an environment at some time in the future as a fait accomplis (an accomplished event), but leaving out the steps by which this environment emerged from the present day. Most published scenarios are of this type. See Chain scenario for the alternative.
An evo devo theory of intelligence and adaptation. All replicating complex adaptive systems, whether they be replicating stars in galactic evolutionary development, replicating prebiotic chemicals in molecular evolutionary development, replicating organisms, replicating ideas, human-replicated processes and architectures or self-replicating technological systems, can be observed to partition their information and intelligence into three different systems, their seed (replication processes and parameters), their organism (body, soma), and their environment (the space in which they exist, which they increasingly alter (niche-construct) to be habitable for them. If you’re just looking at the intelligence of one of these systems, you’re missing the full picture, and need to widen your scope if you wish to truly understand its past, present, and future dynamics and informatics.
STEEPS3 foresight scanning framework (Pronounced: “Steeps three”) and STEEP foresight scanning framework
STEEPS3 is an environmental scanning framework that groups relevant issues, actors and change drivers into eight subject categories, as follows:
Science (abbreviated “S zero”),
Technology & Information Issues, Actors, and Drivers (“T”),
Environment, Energy, Resources, and Global Issues, Actors, and Drivers (“E1”),
Economics, Globalization & Capitalism Issues, Actors and Drivers (“E2”),
Politics, Security & Democracy Issues, Actors, and Drivers (“P”),
Society (Big): Culture, Media, Education & Religion Issues, Actors, and Drivers (“S1”),
Society (Medium): Business & Organizations Issues, Actors, and Drivers (“S2”), and
Society (Small): Personal & Career Issues, Actors, and Drivers (“S3“).
STEEPS3 is Foresight University’s expansion of the traditional STEEP foresight scanning framework, and its variants (STREEP, PEST, PESTLE, etc.) which are much less systematic and useful, in our view. In STEEP, S stands for Society, treated as a single category (with no division into the three key levels of culture, organizations, and individuals). Science is lumped in with Technology, even though these are two very different things. A major advantage of STEEPS3 over other foresight scanning frameworks is that it roughly stacks environmental actors and change drivers in the order of fastest, most powerful, most fundamental, and/or most irreversible first. Consider that you, as a foresight professional, don’t have a rough understanding of what’s happening in the relevant science labs and theory impacting your problem, you often cannot adequately evaluate Technology and information futures and option for that domain, as the state of and changes in science are typically driving and constraining those Technology futures. Likewise, if you don’t understand Technology changes relevant to your problem, your understanding of environmental and resource issues will in turn be seriously naive, and so on down the list. It is of course a judgment to consider STEEP drivers as often faster, more powerful, more fundamental, or more irreversible than the S3 factors (big, medium, and small dimensions of Society), and to believe that, for example STEEP drivers often shape and constrain Society’s options even more than society shapes and constrains them. It not necessary to accept this view to use the STEEPS3 model as a scanning framework. Acceleration awareness (see entry) argues that Science and Technology are typically the fastest moving sectors, even over Resources and Economics, and these in turn move faster than Politics, as complex systems. Where Society fits in this hierarchy of speed is perhaps arguable, but we place it at the end, as many cultures, organizations, and people are increasingly seeking to slow down and simplify as our science and technology speeds up and complexifies all around us. We can expect even more of this behavior, an even greater difference between human and machine speeds, if technical advances like Artificial / Natural Intelligence, and political advances like the Basic Income emerge. In addition, the Universal evolutionary development model would argue that human society is not fully controlling science and technology, but is rather only controlling its evolutionary aspects, while being subject to its developmental aspects. Though these may be small in number, per the 95/5 rule, developmental processes may be, equally as strong as evolutionary ones in their future effect. In Evo-devo biology, a good case can be made that development and evolution are equally important to describing change in living systems. Finally, we need to recognize that all categorical foresight frameworks are incomplete. They are ways to start an environmental scanning process, but we always need to consider “What else?” Foor this reason, good frameworks often include a Multifactoral / Other category, to elicit this kind of thinking.
STEM (Space, Time, Energy, and Matter) compression / STEM efficiency and density increase
Futurist John Smart’s explanation for the physically observable effects of accelerating change in complex systems. Leading systems continually increase their efficiency and density of use of Space, Time, Energy, and Matter (physical resources) to produce adaptive complexity (information, intelligence). See Evo Devo Universe?, 2008. Futurist Buckminster Fuller developed the first half of this idea in his concept of Ephemeralization, which is about the increasing efficiency of the use of resources by leading systems. But increasing density of use of STEM resources is also constantly occurring. This means that leading systems are increasingly localized in space, accelerated in time, and densified in their energy flows and material structures. If this apparently universal process continues, things get weird. In the long term, universal intelligences increasingly tend toward structures which look, curiously, like black holes. See Transcension hypothesis.
Strategic intent / Strategic purpose
Statements of Strategic Intent – much the same as Strategic purpose – are becoming popular with large organizations. These are shorter and looser than a Strategic plan, but more detailed than a mission or vision statement. They describe what the organization is trying to accomplish, in practical terms.
Strategic planning is usually about one organization, and rarely. When it’s done for industry or technology it’s typically done as Roadmapping. See also Scenario planning, in which scenario production and learning is done as an early and important step in strategic planning.Strategic planning implies that the organization can set and achieve its targets regardless of its environment; scenario planning takes a broader range of factors into account, sometimes implying that the organization has no control over its environment.
Much the same as Judgmental forecasting. The result is still expressed in numerical terms, but human judgment is involved in predicting the correct numerical outcome, taking into account factors that a forecast based solely on past trends will not reflect. For example, if a new government policy is likely to change the demand for a product or service, its effect can only be assessed subjectively.
Similar to Conjecture – a recognition that something may happen, and what might then follow from that.
When a gap suddenly arises between your perceptions and your expectations of a situation, that’s surprise. It can happen either because your expectations were unrealistic, or your perceptions are wrong. As expectations gradually adjust, the level of surprise fades away. Managers of organizations dislike surprises, regarding them as bad news, but for young children, surprises (often stage-managed by parents) are good news. Is there room for rapprochement here? Notice that “surprise” has two different meanings – it’s both a cause and an effect – a surprise [cause] surprises [effect] you. The surprise that you then feel is an effect. Failure to notice this distinction has caused some confusion in writings on surprise. See also Wildcard and Discontinuity.
“Development that meets the needs of the present without compromising the ability of future generations to meet their own needs.” This elegantly succinct definition comes from the Brundtland Commission of 1983.
The view of history as a set of situations (rather than events) occurring at the same time and influencing one another. The counterpart of diachronic.
When two factors are combined, something can happen that doesn’t happen with either of them separately. For example, with two-pack epoxy glue, the glue doesn’t work until the two liquids are mixed. And nichrome alloy (steel, nickel, chromium) is tougher than any of its three component metals. And it takes both a woman and a man to produce a baby. The inventor and futurist Buckminster Fuller defined synergy concisely as “the behaviour of whole systems unpredicted by the behaviour of their parts.”
An approach popularized by Jay Forrester and the Club of Rome in the 1970s with their controversial book Limits to Growth (1972). Social change is described in terms of stocks and flows, with loops of positive and negative feedback, and various time lags. This can be either a qualitative or quantitative method, but it is usually the latter. Numbers aer attached to the various inputs, and software calculates outputs – which are often not intuitive. This approach is not as well suited to situations that can’t be readily quantified.
Thinking about things as if they are systems – with inputs, processes, and outputs, and boundaries. Systems often contain subsystems, and/or are part of larger systems (see holon). It’s important to realize that systems are a human’s view of the world, not intrinsic properties of a world, so (specially for social systems) boundaries are usually arguable. Even something seemingly as immutable as the Solar System can be redefined – e.g. with the recent decision that Pluto is not a planet after all.
The point at which machine intelligence becomes generally human-surpassing (general artificial intelligence) not just in very specific areas of intelligence (a has already occurred today), but in a generalized sense, and including all our “higher” mental features (imagination, creativity, emotion, empathy, morality, linguistic ability). Alternatively, the point at which machines successfully claim to be conscious (perhaps in a court of law), even if they are not yet human-surpassing in all aspects of their intelligence. Another more scientific/physical definition of the singularity is a phase change (phase transition) in a complex system (like Earth’s human-machine intelligence system), like the move from gas to liquid or from liquid to solid. New dynamical models, both different from and at least partially unpredicted from their predecessors, emerge. A third definition, perhaps the weakest, is based on the human-observed pace of technological change, which is ever-increasing. When the observed rate of change starts to look infinite or instantaneous to today’s unaugmented biological human observers, a singularity may be said to have occurred. See Wikipedia definition. See also J-curve / Superexponential change.
A term normally used in a public policy context: planning for sustainable technology development. Futures methods such as Delphi are commonly used in technology foresight. See Constructive technology assessment.
When a new invention goes into production, there are often many suppliers and intermediaries who need to be coordinated. Technology roadmapping (TRM for short) is becoming a popular method for doing this; the end result is a timetable-like graph showing who needs to do what, at what point on the time-line.
Terminal scenario / Developmental attractor / Endstate / Portal
A scenario describing a future situation that no longer changes substantially, because it is in some way terminal, or an Endstate. In The End of History (2006), Frank Fukuyama popularized the idea that capitalist social democracy may be an endstate scenario for all civilized governments of humans by humans. Endstates are often dependent upon the level of complexity of local actors and the environment. Presumably, government of humans by AIs would be a new set of actors and environment, with potentially new and different endstates. Universal evo devo theory calls such future states Developmental attractors / Portals, potentially “ideal” configurations for complex systems in our universe. These may discovered haphazardly and chaotically by life forms throughout our universe, which each take unpredictably different evolutionary paths toward the these presumably predictable developmental endstates.
How far into the future a person or organization considers possibilities. If a company has a 3-year plan, and never looks beyond that, its time horizon is three years.
TINA: There Is No Alternative (to the force or trend)
An expression of determinism in certain future forces or trends. First used by the Thatcher government in the UK in the 1980s, then applied to globalization, and generalized, perhaps first by futurist Pierre Wack at Shell, to the concept of unstoppable forces driving the future.
TOP: Technological, Organizational, Personal decisionmaking model
An acronym used in multiple perspectives thinking and decisionmaking, examining the world using three broad kinds of perspective: the Technological, the Organizational, and the Personal. Developed by Harold Linstone and Ian Mitroff, and explained in their excellent book on decisionmaking under conditions of complexity and change, The Unbounded Mind, 1995.
The idea, proposed by Guide author John Smart, in The Transcension Hypothesis (2011), that because of STEM compression, the increasingly efficient and dense use of physical resources to produce informational complexity and intelligence, all increasingly advanced civilizations may look increasingly like black holes, from a universal perspective. This hypothesis has implications for the Fermi paradox, the question of why Earth observers have found no signs of intelligent life, even though we are billions of years older than other presumably life-supporting planets that have emerged in our galaxy. If our universe allows black-hole-like transcension any advanced civilizations, so that they can meet each other instantaneously via their own black-hole-like process of development, then as they mature they may invariably decide that the most ethical policy is not to interfere with evolving civilizations before they arrive at their own transcensions, as a way to maximize evolutionary diversity for the universe as a whole. The hypothesis argues that something like Star Trek’s Prime Directive, thus emerges in a predictable universal process of moral development, in all advanced civilizations. Transcension can’t just be an evolutionary choice, as evolution would allow some civilizations to choose instead to colonize their galaxies with advanced technology. It has to be universal development, a process directly analogous to biological development.
A measure that has been changing steadily. “The trend over the last 20 years has been for more and more people to go to university.”
Lack of political, business, or social awareness of an obvious trend. Dan Burrus describes baby boomer needs as an obvious example. The baby boom started in 1946, lasted to 1964. At first, there weren’t enough hospitals. Then not enough schools. Now not enough social security and health care. The trend was obvious, but we were repeatedly blind to its implications. Coined by foresight professional Daniel Burrus, Flash Foresight (2011).
Contrasts with a Trend. A trend is something that’s gradually happening. An uncertainty is a trend or event that has a reasonable chance of happening. If it would make a major difference, it’s known as a Critical uncertainty. A Wildcard usually isn’t considered a critical uncertainty, because it is too unlikely. A wildcard is that the Earth could be hit by a giant comet next week. Though this might be catastrophic, it wouldn’t be considered a critical uncertainty, as it is so improbable.
The recognition, by psychologists and good managers, that the older we get, the higher the percentage of ideas, attitudes, models, and behaviors are no longer adaptive in a changing world. We need to unlearn those less adaptive neural structures continuously. For a good primer, see Jack Uldrich, Higher Unlearning (2011). See also Reverse mentoring, for one great unlearning technique all mature leaders should use.
UPGO strategic foresight education and practice domains
Foresight University divides strategic foresight education and practice into four fundamental domains, taught in a particular order. We begin with Universal foresight, to help students understand current thinking on the Big Picture processes of change affecting us all. Then we proceed to Personal foresight, to help foresight professionals to “walk their talk”, to be aware of their own biases, learn techniques for guiding their own futures, and to seek to embody the kinds of outcomes that the universe itself appears to be striving to create. Then we move to Global foresight, to understand global trends in universal context, and how we can effect them on personal levels. Once these three domains have been introduced (for the student) and considered (for the practitioner), we think this provides the best context for study and work in Organizational foresight, the oldest, largest and best-paid of these four particularly fundamental domains.
A proposed perfect future society (never so good-looking when examined closely!) The most famous example is the book Utopia by Sir Thomas More (1516). For a broad collection of presumed utopias, and the various deluded leaders and writers who have proposed them, and the tragic forms of social control that have resulted, from 1490 BCE to 1998 CE, see the Faber Book of Utopias (1999) edited by John Carey. See also Protopia, a place that’s not perfect, but is measurably, progressively better than the present, along some set of variables.
A vision is a clear view of the future, usually one that an organization is working toward achieving for itself. Note that a vision is usually singular: an organization with a unified vision statement is not thinking about alternative futures.
The combination of volunteeering, as service work or capacity-building activities with people who need it, donations of goods or capital, and tourism, either at home or around the world. It is most often done in areas one rarely visits. Needy communities can easily be found very close to just about every major tourism destination. See Voluntourism.org for more.
VUCA: Volatility, Uncertainty, Complexity, Ambiguity
A U.S. army way of describing a difficult situation. Iraq today, perhaps. “We live in times of VUCA.”
An event which is highly unlikely to happen, but would have a huge impact if it did. An example might be an asteroid colliding with the earth. But though the probability of any one wild card event is very low, so many different wild cards are possible that the combined chance of one of them happening – somewhere in the world, over some time extended period – can be quite high. Though winning a lottery is an example of a positive wildcard, they are usually bad news – unpleasant surprises. Similar to Discontinuity.
Worldview / Weltanschauung
The way in which people see the world, with an emphasis on their unconscious assumptions, mindsets, and the principles that they will not question. The German word for worldview, also used, is Weltanschauung. Similar to Paradigm. See also Mindset.
German for “spirit of the times”. A concept that people implicitly believe in for years, without realizing it, or being able to express it in words. Usually the zeitgeist becomes obvious only when it changes.
Zero-Sum Game / Win-Lose Game
A game or interaction where one’s winning must come at the cost of another, because the desired resources or outcomes are scarce and can’t be easily substituted with an alternative. Games like tic-tac-toe, and chess (where only one can win), and many political contests over scarce resources are zero-sum games. Curiously, the more futures-oriented and long-term the view the politician, the more often they are able to see and support the growth of total resources over time, and therefore the more they are willing to change their interactions into Positive sum (win-win) games.
Ziel-Orienterte Projekt Planung (in German) – in English, Objectives- Oriented Project Planning (OOPP). A complex method of planning projects in the developing countries, based on Logical Framework Analysis, and created by the German aid agency GTZ,. Explained further on GTZ’s website at www.gtz.de. Part of ZOPP is the Problem tree, which can be converted into an Event tree for use in futures work