[26 June 2014]
I’m most often introduced at a conference or meeting as a futurist. I run quickly to the point that I am really an anti-futurist. A futurist will typically provide people with some seemingly prescient answer about the future. They will tell you, in no uncertain terms, what it will be like to work and live five, ten, even 100 years into the future.
Very often, futurists take up an opening or closing keynote slot at a conference in order to spark the imaginations of the audience, and to fuel the fervor of those already compelled to believe in a positive future associate with their industry or role within the workforce, or to hope that just enough fear will spur innovation. People like Bill Gates insist that the best way to predict the future is to create it.
Other great thinkers, like the late Peter Drucker, take a different tact: “Trying to predict the future is like trying to drive down a country road at night with no lights while looking out the back window.”
An anti-futurist has a different job. An anti-futurist helps people identify and name future uncertainties, in as exhaustive a way as possible (though I caution, with essayist Nassim Taleb’s work in mind, that infrequent, large events, ala the Black Swan Theory, may still surprise us). An anti-futurist helps people think about the future without pontificating assertions that neither they nor the audience can possibly confirm.
It was with this perspective that I opened In 100 Years: Leading Economists Predict The Future, edited by Ignacio Palacios-Huerta.
With the majority of the human race clamoring for certitude in the chaos they see around them, the word “predict” offers a useful, if not powerful salve, aimed at soothing the ache of not knowing. After all, professionals with degrees, as well as people just responsible for making ends meet over the next 50 years or so, feel compelled to establish some rhythm to their lives that can guide their actions one day to the next.
Surely economists, more so than others, should know these answers, because they work in an industry governed only by rules they have created, an industry represented by numbers designed to guide and to forecast humanity and its markets.
To reinforce the opening of this review: no one can predict the future. Economic models are filled with historical data, often in isolated models that don’t account for conditions external to the models, multitudes of assumptions all constrained by techniques that don’t accommodate feedback very well. The models, especially those that employ the new discipline of predictive analytics, may do well at adapting to moment-to-moment futures like anticipating fraud or suggesting a stock sale, but the models do very poorly at going out days, let alone weeks, months or years into the future.
The first essay, by Daron Acemoglu (and thankfully), the only one in the book that uses data in the form of charts, makes his case for trends around democracy, unrelenting growth, and in contrast, uneven growth. The last trend is the most interesting, in that Acemoglu states that gaps between rich and poor nations have increased, not narrowed.
As an anti-futurist, I would ask about the relationship between poor nations and civil disruption over the long course of history, and if the data suggests any interruption in unrelenting growth or the rights revolution as a result of those poor nations undermining current economic assumptions, what then? Acemoglu does write, in the later sections of his chapter, about influences and relationships between organization types and technology, about robots and work and innovation. Eventually, however, he goes into the art of the futurist, that of creating a myth about the future:
It would be utopian to hope that economic growth in the next century will ensure convergence between rich and poor nations. But there are reasons to expect that it will no be as uneven as twentieth-century growth.
He goes on, in a rather utopian way, to say that civil rights will continue to spread, global technology and production will increase the need for cheap labor, and that movements toward inclusiveness of governments in Africa and Asia will continue to rally. Because there is no data about the future, how these major, interconnected institutions and ideas plays out is nothing but biased speculation, often utopian biased, because people, even economists, want to live in a world that is better than the one they live in today. It is also emotionally more fulfilling to provide good news than bad.
This utopian view from Acemoglu is followed immediately with a reinforcing essay by Angus Deaton, which reminds us that John Maynard Keynes saw a good future despite the dire world in which he advised political leaders, that of the depression and the second World War. Keynes was a designer, in that he thought investment should be driven by government. So, while Deaton acknowledge the challenges and failures we face today, he ends his chapter with several “brighter sides”: Growth, Health and, in utopian fashion, Everything Else.
These two utopian prognosticators are follow by Avinash K. Dixit, who titles his chapter, “The Cone of Uncertainty of the Twenty-First Century’s Economic Hurricane”. Now that is a title an anti-futurist can respect. It’s not that Dixit is more dystopian than utopian, but because he sets out issues that are buffeting the world, and he thinks in scenarios rather than a single, mythical future narratives.
Unfortunately, like his colleagues before him, the editorial focus of the book forces him to compromise and create a myth, one he calls “a dream scenario” complete with a government that prevents crisis by acting before they occur, that public schools will regain their quality and purpose, and that all ambitious innovators will get rich if they succeed, and etc. These are indeed dreams, and that doesn’t mean they won’t come true, but Dixit has no data beyond his own wishful thinking to believe that they will.
This is a Keynsian leaning book, in which the economists suggest ways that their dreams, myths and visions can come true. Dixit suggests that the phrase “Being a Keynesian means being one in both parts of the cycle” be plastered on the walks of treasury departments around the world, while Edward Glaeser states matter-of-factly that “much of what Keynes wrote about the economic future seems as true today as it was in 1930.” Which to an anti-futurist implies that Keynes’ future was one of stagnation, not growth and innovation.
Indeed, it implies a belief in a myth that hasn’t occurred yet, and therefore, like Christians awaiting the return of Jesus, Jews awaiting the Messianic era to commence, or Muslims also awaiting the return of Jesus, but a very different Jesus than that of Christian thought, the economists await a world in which economic manipulations and design can create a more inclusive, democratic and thrivingly integrated economy—one that was forecasted in the ‘30s, but that just took a little longer than expected to arrive.
In In 100 Years, negative views of the future are seen as threats, such as in the section Glaeser titles, “Where Be Dragons? Threats to Future Prosperity”. As an anti-futurist, the value of grappling with uncertainty aims at not predicting the future, but at being watchful as it unfolds, so that individuals and institutions can better navigate it, regardless of how positive or negative it ends up.
What Glaeser explores are threats to the prosperity codified in his myth, and because he has only one myth, he has a hard time imagining prosperity in an alternative story because neither he, nor his clients, will likely be a recipient of that prosperity. In every historical shift there are winners and losers, but when looking at a self-perpetuating forecast, anything that disrupts that forecast is a threat even if the resulting new state creates greater prosperity than the current state.
The writers here hint at, but don’t delve, into the displacement of workers by artificial intelligence and robotics. Many of the jobs returning to the United States from low wage countries are being filled by robots, which operate at roughly the same cost per-hour, but greatly decrease the logistics components related to shipping and distribution. The automation of jobs and the reduction in supply chain complexity eliminates jobs that were once critical to building the middle class, a question not really addressed by these economists, but one which Erik Brynjolfsson and Andrew McAfee face address in their book, Race Against the Machine: How the Digital Revolution Is Accelerating Innovation, Driving Productivity, and Irreversibly Transforming Employment (Digital Frontier Press, January 2012), albeit with their own utopian leanings toward the end.
So how does one gain value from a book that is clearly not predicting the future, because even the futures predicted from within the Keynesian sphere of influence don’t converge into a concise narrative? First, accept In 100 Years as a work of speculative fiction. The historical data may be fact, but anything about the future is fiction. Second, these are people of thought, who do attempt to identify what could happen in the future, and in that speculation, lies uncertainties that could easily end up with vastly different values than the ones presented, from the future of China, to the distribution of wealth to the hours worked in the US to climate change. Write down those uncertainties and start a multi-dimensional list of potential values drawn from the book, and from your own speculation. Turn every answer into a question.
Then watch what happens, and as it happens, speculate along not just one dimension, but along many and imagine what you or your organization would do if one thing happened rather than another. With this you may not gain immediate clarity, but you will attain a form of mental agility and nimbleness, two words often spread liberally through “leadership training” programs, usually with very poor definitions when it comes to what individuals can actually do to become more agile.
When it comes to the future, how we approach it is, of course, important. In 100 Years could have been a very good book about how to think about the future, but that isn’t the way Palacios-Huerta took his charges. Although there is a modicum of caution and no small amount of analysis and thought, in the end, each of the economists did what most smart people do when asked about the future: they attempted to tell a story, their story, with their biases, their blind spots, and their voice – often with little humility and even less humor.
As a collection, In 100 Years presents the anti-futurist with ample evidence that can be used to reinforce a bias against prediction. The problem is, those who predict the future are never wrong today, thus, it’s difficult for the anti-futurist to make his or her case about how wrong predictions are because they have no more evidence than the forecasters about what will happen tomorrow.
And that is the point that needs reinforcing. Looking back over millennia of forecasts and speculation, some people do guess right, get lucky in the moment, and in the 20th and now the 21st centuries, some of those people were economists. Peter Schiff may have predicted the 2008 recession, but everyday, somewhere in Los Angeles, a person arises, looks out over the dry horizon of the San Fernando Valley and says, “looks like earthquake weather.” As with all past Los Angeles earthquakes, some person saying that, said it on the day of a big earthquake.
That isn’t to say that the economists writing In 100 Years don’t offer a more reasoned view than a gut feel, but if we look back at this book from 2114, we will likely find very little in it that matches the details of the future that unfolded.
If you buy In 100 Years, do so recognizing that it is but one component in an arsenal that is designed to help navigate the future—it represents one set of paths through the wilderness. It is not a definitive map.