Why is it so hard to predict the future of technology?

From Uber to drones, Amy Webb attempts to forecast how technology will change the world.

Can we ever know what is going to happen next? After a year of global shocks, during which many of the most advanced polling methods failed to tip us off to the electoral success of the Brexit campaign and Donald Trump, unfogging the future seems harder than ever.

However, there is a whole industry dedicated to trying to do just this. Futurism – a term beloved of Silicon Valley’s tech evangelists – has grown into a lucrative business that claims to be able to tell companies what will happen next. Its practitioners say they can identify the next billion-dollar start-up long before its founders have even moved out of their parents’ spare rooms. Artificial intelligence, automation and the so-called internet of things are all popular areas for these predictions, which generally reflect a utopian vision of the ideal, technology-assisted life.

In 2013 Amy Webb published Data, a Love Story, which chronicled her attempt to use statistical analysis to succeed at online dating. What was so compelling about her story (and the associated Ted Talk, which has been viewed 5.5 million times) was that Webb exposed the ways in which human failures can be revealed by the very technology designed to overcome them.

Finding that her own dating profile, which borrowed heavily from her CV and gave a great deal of detail about her likes and dislikes, was unsuccessful in attracting any promising dates, Webb delved deep into the system to gather data about what made other women’s profiles more of a hit. Her analysis enabled her to predict what would make potential dates more likely to respond to her. The shorter and vaguer her description was, the more likely it became that men would reply. Removing the reference to her fluency in Japanese, it seems, made her more attractive.

Webb has now expanded her prediction horizons to the more conventional futurist’s beat – the technology of tomorrow. In her latest book, The Signals Are Talking, she lays out a system for identifying new trends while they are still relatively minor events on the “fringe” and tracking them as they hit the mainstream. She calls this six-step process “Cipher”, which stands for “contradictions, inflections, practices, hacks, extremes, rarities”. She looks to the past to inform her conclusions – “It’s difficult to imagine it today, but two generations ago, computing was only a fringe experiment,” she writes – and exhorts people to “pressure test” their conclusions before they act. Scepticism, and the ability to tell the difference between a genuine trend and what is currently “trendy”, are key to making good predictions.

Uber, the taxi service app that first launched in San Francisco in 2011 and was valued at $62.5bn in 2015, is a pivotal case study for Webb’s method. She follows the company’s meteoric rise, tracks the acquisitions it has made, and hypothesises that by 2040 it could have “upended modern farming” by automating every element of agriculture.

Seen through Webb’s eyes, Uber ceases to be just a cab company and has the potential to become “the invisible logistics layer” in all our lives. When she lays out future scenarios according to her Cipher method, it all sounds so plausible. In another example, she predicts that drones will lead to the end of skyscrapers, as overhead space becomes more valuable for communication than for buildings. Cities that have room to accommodate what she calls “landscrapers” – long, single-storey constructions without the height that would interfere with drone traffic – will surpass cramped places like New York city.

“Our thriving urban centres of the future will be San Antonio, Kansas City and Oklahoma City,” she says.

There are caveats, however; events are chaotic and situations evolve continually rather than arriving fully formed. Webb wrote her latest book before the election of Donald Trump. Every one of her hypothetical predictions must now be rewritten in the light of Trump’s presidency, and many other factors. Her system is rational and sensible, unlike the events it seeks to interpret. The best answer to the question “What if?”, it would seem, remains: “Who knows?”