This is the first of three blogs ahead of Nesta's upcoming event, FutureFest, where an extraordinary number of scientists and journalists, comedians and actors, entrepreneurs and authors, will share their unique visions of the future.
This is the first of three blogs ahead of Nesta's upcoming event, FutureFest, where an extraordinary number of scientists and journalists, comedians and actors, entrepreneurs and authors, will share their unique visions of the future.
Here I look at how we can think about the future.
There are many futurists, and a limitless number of people with views about what the future will bring. However, there are no experts on the future. It's not possible to be an expert on something that hasn't yet happened and most experts perform very poorly as predictors.
Some of the reasons are obvious: their models are too simple to cope with complexity, or only work in stable periods but not periods of turbulence.
But the best analysis of the future has also shown some slightly more surprising patterns. For instance, the more publicly visible a futurist is, the more likely they are to be wrong. The media reward exaggeration, in a reinforcing feedback loop that turns otherwise sensible people into quite silly ones (you could cheekily call it the TED paradox: the more coherent and articulate the picture of future possibilities, the more misleading it probably is).
Another lesson is that the more you hold onto a single dominant explanation for change, the more likely you are to be wrong - whether it's the inevitability of democratisation, technology's power to liberate humanity, or the eternal nature of ethnic conflict. The world obeys many laws, not one, and trends produce countertrends. That's why technological determinism - the assumption that new technologies will diffuse into a grateful world and drive change in a linear way - so often misleads, even though it's as popular as ever.
Serious analysis and thought does confer some advantages in understanding how patterns evolve - but only if leavened with a good deal of humility. Otherwise expertise breeds overconfidence and thus a tendency to make mistakes.
We have attempted to avoid this trap at FutureFest - our speakers are not making cast-iron predictions but are instead leading imaginative exercises, inspired by contemporary knowledge, to speculate on what challenges the future holds and how we can face them. As Helen Keller once said, "To be blind is bad, but worse is to have eyes and not see!"
In any era there are conventional views of the future. Today they focus on driverless cars, 3D printers, the internet of things - most already real and growing fast, and so fair bets. These likely contenders are represented at FutureFest, for instance with Alice Taylor, whose company uses 3D printing to create dolls.
There are others which are provocative and maybe right - the shift to new foodstuffs like locusts, learning in teacherless classrooms, living in self-managing buildings, using digital memories to supplant our own, or moving in a world where virtual beings and real ones intermingle without clear boundaries.
Many of these possible ideas have appeared in science fiction books, like Accelerando by FutureFest speaker Charles Stross, but it is hard to say how prescient this fiction will become.
There are other conventional futures which are probably wrong. For thirty years most futurists have predicted the end of work or permanent jobs, and a move to project based work. Read quite a few today and their forecasts are identical to the ones made a generation ago, suggesting that some futurists are remarkably conformist.
Yet in the OECD economies job tenure hasn't fallen at all, and employment levels have generally gone up. So it's right to be sceptical - particularly of conventional wisdoms.
Here I suggest three complementary ways of thinking about the future which provide partial protection against the pitfalls.
First, create your own composite future by engaging with the trends. There are many methods available for mapping the future - from Foresight to scenarios to the Delphi method.
Behind all are implicit views about the shapes of change. Indeed any quantitative exploration of the future uses a common language of patterns (shown in this table above) which summarises the fact that some things will go up, some go down, some change suddenly and some not at all. All of us have implicit or explicit assumptions about these.
But it's rare to interrogate them systematically and test whether our assumptions about what fits in which category are right.
Let's start with the J shaped curves. Many of the long-term trends around physical phenomena look J-curved: rising carbon emissions, water usage and energy consumption have been exponential in shape over the centuries. As we know, physical constraints mean that these simply can't go on - the J curves have to become S shaped sooner or later, or else crash. That is the ecological challenge of the 21st century.
But there are other J curves, particularly the ones associated with digital technology. Moore's Law and Metcalfe's Law describe the dramatically expanding processing power of chips, and the growing connectedness of the world. Some hope that the sheer pace of technological progress will somehow solve the ecological challenges. That hope has more to do with culture than evidence. But these J curves are much faster than the physical ones - any factor that doubles every 18 months achieves stupendous rates of change over decades.
That's why we can be pretty confident that digital technologies will continue to throw up new revolutions - whether around the Internet of Things, the quantified self, machine learning, robots, mass surveillance or new kinds of social movement. But what form these will take is much harder to predict, and most digital prediction has been unreliable - we have Youtube but not the Interactive TV many predicted (when did you last vote on how a drama should end?); relatively simple SMS and twitter spread much more than ISDN or fibre to the home. And plausible ideas like the long tail theory turned out to be largely wrong.
If the J curves are dramatic but unusual, much more of the world is shaped by straight line trends - like ageing or the rising price of disease that some predict will take costs of healthcare up towards 40 or 50% of GDP by late in the century, or incremental advances in fuel efficiency, or the likely relative growth of the Chinese economy.
Also important are the flat straight lines - the things that probably won't change in the next decade or two: the continued existence of nation states not unlike those of the 19th century? Air travel making use of fifty year old technologies?
If the Js are the most challenging trends, the most interesting ones are the 'U's'- the examples of trends bending: like crime which went up for a century and then started going down, or world population that has been going up but could start going down in the later part of this century, or divorce rates which seem to have plateaued, or Chinese labour supply which is forecast to turn down in the 2020s.
No one knows if the apparently remorseless upward trends of obesity and depression will turn downwards. No one knows if the next generation in the West will be poorer than their parents. And no one knows if democratic politics will reinvent itself and restore trust. In every case, much depends on what we do. None of these trends is a fact of nature or an act of God.
That's one reason why it's good to immerse yourself in these trends and interrogate what shape they really are. Out of that interrogation we can build a rough mental model and generate our own hypotheses - ones not based on the latest fashion or bestseller but hopefully on a sense of what the data shows and in particular what's happening to the deltas - the current rates of change of different phenomena.
In my second blog I'll look at stories of the future - and how we can construct plausible and useful accounts of what might happen, often building on our picture of what trends are possible.