Abstract
The raw material from which the Global Trends 2030 report was derived came from commissioned papers, workshops, interviews, and feedback—all largely qualitative. In addition, a number of quantitative models were used to put numbers behind the ideas that came from the consultants. The synthesis of this information was performed by an individual (or the assembled team) to form megatrends, then a few game changers that could deflect those trends, then into potential worlds (the scenarios), and finally tested with “tectonic shifts” and “black swan” developments. Specific criticisms: the report itself has very meager information about the methods employed. Other methods of synthesis might have led to fresher, more quantitative, insights about the forecasts and policy opportunities. The future developments discussed in the report are not probabilistic nor are there effects stated in quantitative terms. Thus there was no measure of the depths of uncertainty associated with any of the forecasts. Similarly, there was no information about whether all of the experts agreed (unlikely) or what the disagreements might have been. The report was weak on policy; prescriptions for policies designed to improve the future were essentially absent. I was glad to see that black swans events were considered; however the black swans of the report are were all rather expected (e.g. climate change). A more imaginative set would have been welcome. Considerations of ethics and morality are also absent. Yet the report is useful and presents information worth pondering.
Keywords
When I took on the assignment to review the methodology used by the National Intelligence Council (NIC) in preparing Global Trends 2030, I thought it would be easy to find a summary—perhaps in an appendix—of the techniques used to prepare this thought-provoking report. But lo and behold, there is neither such appendix nor could I find a description of the methods in the text itself. In fact, I scanned the report’s 164 pages looking for the word “method,” and it was mentioned only once. 1 So how was it done? I leave to others a review of the report’s content (Were the forecasts plausible? Were the recommended policies likely to be successful?); here, I will concentrate solely on the method.
It seemed to me that the process, as in previous years (this is the fifth in the series), involved synthesizing inputs from many experts on an array of topics, collected through commissioned papers, workshops, blogs, and interviews held around the world and strengthened by a few quantitative models.
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I sent this skeleton description to a few people involved in the process and asked if this was close to the mark. They agreed and were kind enough to add detail. For example,
It may also be of interest that for the first time in producing a global trends report (this was number five), a draft report was produced about nine months before the final, which enabled us to take the draft around the world for critique and input (about twenty countries were visited). The final draft was changed by about 30 percent.
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So we may add to my skeleton description of the method: “feedback of comments on the draft report by international reviewers.”
While the inputs from the papers, workshops, interviews, and feedback were largely qualitative, a number of models were used to put numbers to some of the ideas that came from the consultants. Among the models cited in the report itself and mentioned by my correspondents were Barry Hughes’ International Futures at the University of Denver, a demographic model by Richard Cincotta of the Stimson Center, and a Global Growth Model of the consulting firm, McKinsey and Co.
All my correspondents say that Mathew Burrows, a counselor to the National Intelligence Council, was the driving force behind the report, the organizer, and responsible for the structure of the report as well as its methodology. He was the synthesizer (or at least led the synthesis) of the many data streams. He was what we, in the old days, would have called the project engineer.
Certainly, running workshops, conducting interviews, reviewing the opinions carried in blogs and other sources, and commissioning expert papers all require careful thought and benefit from good organization, experience, and networking. But methodological magic in this report comes from the synthesis of information derived from all these sources. This is what has come to be called “collective intelligence,” a process in which the output is supposed to be smarter than any single input. But how can the thousands of ideas from such diverse sources be organized into a cohesive narrative, a whole that is somehow more than the parts?
In this report, that synthesis function was performed by an individual (or the assembled team)—a genius forecasting operation that crystallized the eddies of thought flowing from various source streams, first into megatrends, then a few game changers that could deflect those trends, then funneled into potential worlds (the scenarios), and finally tested with “tectonic shifts” and “black swan” developments.
In snapshot form, the megatrends—each familiar enough—were
Acceleration of individual empowerment, reduction of poverty, growth of the global middle class, universal communications, and health care education
Diffusion of power and emergence of a multipolar world
Demographic inevitabilities, aging, urbanization
Demand for resources—food, water, energy—all in more or less short supply, in collision with increasing population and economic growth
The game changers that seemed to have the potential for altering the courses of the megatrends, that is, the overriding uncertainties were,
Emergence of a crisis-prone global economy
Inadequate governance: governments overwhelmed by the rapidity of change
Technologies coming to the rescue in time to minimize the consequences of climate change, population growth, and urbanization
Increases in the number and intensity of conflicts
Regional conflicts (e.g., Middle East) spilling over into global conflicts
A changed role for the United States in this changing world
These trends and game changers were the raw material from which four scenarios were formed. These scenarios in turn were intended to mark out the corners of a plausible scenario space:
Stalled Engines—offered as the most plausible worst case in which globalization stalls and the U.S. draws inward
Fusion—the most plausible best case in which international cooperation is the mark, particularly between the United States and China
Gini Out of the Bottle—inequalities: some countries progress, others fall by the wayside
Nonstate World—in which nonstate actors take the lead and new technologies become even more important
Reflection about the scenarios led to the identification of a set of “tectonic shifts” that seem to be occurring; these were,
Growth of a global middle class
Wider access to lethal and destructive technologies
Definitive shift of economic power to the East
Unprecedented and widespread aging
Urbanization
Food and water pressure
U.S. energy independence
Then, “black swan” game changers were postulated: a set of future developments of low probability, maybe even with vanishingly small likelihood but with huge consequences if they were to occur. Examples used to make a final iteration included: pandemics, climate change, EU collapse, China collapse, a reformed Iran, nuclear war, cyber attacks, and solar storms. This was an excellent place for the report to have used new, innovative methods to find possibilities that were not yet on the futurist agenda, but the swans, black or otherwise, apparently swam from the same data streams as the other parts of the report.
So, now to the critique.
Since the method used to produce this report is not clearly described, it would be difficult for another organization, trying to produce say, European Trends, 2030, to use exactly the same technique. The road map used by the NIC is hard to find. Maybe this is because it is not definable as a stand-alone process but rather is many processes run in parallel and then synthesized to produce a coherent report.
Other means of synthesis might have led to fresher, more quantitative insights about forecasts and policy opportunities. I believe that, in collective intelligence, the synthesis engine is at least as important as the fuel feeding it. In this case, the synthesis engine was an old design: genius integration. Why not consider other means of synthesis? For example, Robust Decision Making (RDM), a technique developed by policy researchers at RAND that functions in conditions of deep uncertainty, works around multiple views of the future, and produces strategies that seem likely to work despite uncertainty and are sufficient rather than optimal? A RAND researcher says:
RDM rests on three key concepts that differentiate it from the traditional subjective expected utility decision framework: multiple views of the future, a robustness criterion, and reversing the order of traditional decision analysis by conducting an iterative process based on a vulnerability-and-response option rather than a predict-then-act decision framework. These features allow RDM to combine some of the best features of traditional risk management, its ability to quantitatively compare trade-offs among alternative strategies in the presence of uncertainty, with the cognitive benefits of traditional scenario-based planning, which can help diverse groups agree on actions without agreeing on expectations about the future.
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Trend Impact Analysis (TIA) is another synthesis engine that could be used. 5 Here, historical time series data are projected into future years using statistical techniques that fit historic data points, variable by variable. (One source of intelligence: historical data.) Then future developments that could affect the course of each variable are postulated (another source of intelligence, derived from news, blogs, interviews, etc.) and assessed in terms of their probabilities and impacts (yet another source: perhaps from Real Time Delphis). TIA synthesizes these sources to produce an amended forecast of the variables being examined and, for example, the significance of a news item or postulated policy becomes visible in terms of its consequent impacts on measurable phenomena.
The NIC scenarios do not quantify the effects of future developments and are not probabilistic. If they were probabilistic, they would offer some measure of the depths of uncertainty. I am not dealing here with the likelihood of the scenarios; they are each, like all scenarios, very unlikely. Rather I mean their intrinsic uncertainty. Imagine a projection of GDP in a given scenario. Now include error bars or surround the projection with a fan of probabilities. The length of the error bars or the size of that probabilistic fan represents the level of uncertainty of the GDP forecast. True, the report offers some model-derived economic forecasts that differ from scenario to scenario, but these are single-value lines that appear to be essentially surprise-free forecasts within the context of the scenarios. The possible effects of future policies and developments and the uncertainties they raise are not included.
The Millennium Project has, for several years, constructed global State of the Future Indexes (SOFI) in which twenty-five to thirty quantitative variables are forecasted using TIA and then aggregated to form a probabilistic index, shaped by postulated future developments to answer whether the future appears to be improving or worsening, and why. Of course, some of the variables seem likely to improve and others to worsen. Because the approach is quantitative, sensitivity tests can be run to show which future events hold promise and which do not, and, importantly, which could be the basis for policy. It could have been groundbreaking if the NIC had included SOFIs or something like them in its scenarios, which could then have been repeated in GT 2035, four years from now, to track the world’s changing prospects. The International Futures model (also used by the NIC in preparing GT 2030) has built in the beginnings of a SOFI calculation facility for essentially every nation and region of the world. The Global Futures Intelligence System, 6 currently being developed by the Millennium Project will also have this capacity.
I really liked the use of imagined artifacts to give substance to the scenarios. For example, the fictional transcript of an inaugural address of the incoming president of The Center For Global Integration, and the winning 2028 essay in a contest established by the New Marxist Review for the meaning of Marx and Communism 210 years after Marks’s birth. This is the kind of imaginative presentation that helps make scenario reading less boring and increases understanding of the scenario zeitgeist.
Were all the experts consulted in agreement? 7 Real Time Delphi or some other structured group process could help show where there was consensus or disagreement. I know it is a tall order, but imagine how useful it would have been to produce contrasting sets of scenarios that differed across a fulcrum of consensus. It also would have been instructive, for example, to learn about differences between forecasts of experts from developing countries and experts from developed countries. This kind of analysis would be particularly important in the development and implementation of global policies.
The report was weak in the area of policy. Many policy statements were very general and nonspecific. For example, the executive summary said “we are not necessarily headed into a world of scarcity, but policymakers and their private sector partners will need to be proactive to avoid scarcities in the future.” Hardly news—a gloss-over. What kinds of policy? Is global cooperation required? If so, how can it be accomplished in ways that are not currently on the table? I get the feeling that there was a great deal of effort spent on producing descriptions of possible futures but much less on how to achieve a desirable future while avoiding its looming threats.
There is little reference to normative futures, that is, what ought to be, the other side of the forecasting coin. Planning is the process of devising strategies and action plans that brings a forecasted future into alignment with a desired future. But where is the NIC research on what is desired? There are many fewer normative scenarios in the literature than scenarios that describe expected futures, but there are some. Generally, normative scenarios begin with a desired future state of affairs and then describe a plausible cause-and-effect chain that could produce that desired result. As is the case for all scenarios, there is little chance that any one of them will come true as written, but the process often uncovers useful and important possibilities. 8
There were other gloss-overs as well. Black swans are major unexpected events—pandemics, climate change, EU collapse, China collapse, a reformed Iran, nuclear war, cyber attacks, and solar storms hardly qualify. They are either scheduled already or underway. Here, we need a technology to discover earth-shaking realities of the future. In 1961, at RAND, I participated in the world’s first long-range Delphi study. It was designed to produce forecasts of future developments in science and technology. The participants were stars from around the world: from science, science fiction, and politics. Yet in forecasting the world of the next decades they omitted those things that are the essence of our lives today: MRI and CAT scans, Hubble and the Large Hadron Collider, the housing bubble, the cold war collapse, nanotechnology, Google, and HIV/AIDs. To that pioneer panel, these would have been black swans. Certainly, there are limits to the knowable; the most important future developments may not be detectable by asking what do you think will happen? People could not have known about or even postulated atomic power before there was a chain reaction or Google before there was an Internet. There has to be a decisive experiment or demonstration before its consequences enter the forecasting panorama. It seems to me that most future events are anchored in the present and can be classified as extrapolative, scheduled and planned, or already in the popular mind. Black swans are none of these; they are unanchored in the present because crucial experiments have not been demonstrated or the discontinuous theories on which they are based have not yet been proposed. These developments are nonlinear, nonextrapolated, unexpected, often seen as infeasible or undesirable, or counter paradigmatic. So, next time around, black swans should be more exciting and imaginative. Consider (not forecasts, only examples) discovery of the cause of the Big Bang, massive changes in birthing, new means for settling differences, or proof that we are indeed alone in the universe.
Also in the gloss-over category is the absence of any consideration of morality and ethics. In future, what is to become moral and ethical, what will these terms come to mean? Finally, although the report has “global” in its title, it is clearly focused on the United States. Would other nations and groups find the NIC future that is implied in the report, one that they, too, wish to achieve?
The Executive Summary of the report says,
This report is intended to stimulate thinking about the rapid and vast geopolitical changes characterizing the world today and possible global trajectories during the next 15-20 years. As with the NIC’s previous Global trends reports, we do not seek to predict the future—which would be an impossible feat—but instead provide a framework for thinking about possible futures and their implications.
Despite my critical comments, offered in the spirit of considerations for the next time, the team that produced the report gave us all something to ponder, which after all was its intent.
Footnotes
Acknowledgements
Michael Marien supplied many useful comments on the first draft of this paper; his contributions are gratefully acknowledged.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The author(s) received no financial support for the research, authorship, and/or publication of this article.