Scientific method pushes futurology past tea leaves and crystal balls
Futurologists use computer modelling to analyse trends and predict likely outcomes
French president François Hollande shakes hands with Cybedroid robot Leenby at the Élysée Palace in Paris during the Viva Technology conference. Photograph: Michel Euler/AFP/Getty Images
Futurology, futurism and future studies all vary considerably in meaning, depending on who you ask. In reality they’re all about as different as the People’s Front of Judea, the Judean People’s Front and the Judean Popular People’s Front: “splitters!”
Futurologists have been an easy target for jokes since the 1960s. Mainly because the term and discipline came of age at a time when best-sellers such as Alvin Toffler’s Future Shock, published in 1970, got things so wrong. The literary perception of the future in the 1960s and 1970s would make even Buck Rogers blush.
Futurology is most simply defined as the formal study of predicting the future. We’re not talking about fortune-tellers with crystal balls, or their social science equivalent: economists.
The discipline has become increasingly grounded in scientific methodology using computer modelling to analyse past and current trends to determine the likelihood of various outcomes in the future.
Back in the 1960s and 1970s they weren’t observing a world during a time of profound technological change. (Social change perhaps, but not technological.) Telephones, television sets, aircraft and electricity were all well-established, not to mention well-understood, technologies.
Jump ahead to 2017 and the rapid pace by which everything from digital communications to quantum computing, nanotech to artificial intelligence (AI), all seem to be moving would suggest futurology needs to make a comeback.
With a greater emphasis on predicting short-term, small-scale trends, futurism is being taken seriously once more by many of the biggest companies in the world aiming to strategise their next move in brave new markets. “Firms are taking futurism very seriously because if they don’t understand game-changing trends they will be left behind,” says Prof Rodney Culver Hill from Texas A&M University. Originally an architecture expert, Hill has been giving talks at the World Future Society’s annual conferences for more than 20 years.
“By 2030, there will be up to three billion jobs lost worldwide to AI and robots,” says Hill. “Foxconn replaced 60,000 workers with robots last year. IBM’s Watson already has Legal Watson, Medical Watson and Financial Watson, all of which have begun to replace existing workers while also greatly enhancing productivity in those professions.”
According to Hill, more than three billion people will be added to the world population by 2050. To cater for all these people, futurologists have calculated the need for 100 new cities, each of which being able to cater for 600,000-plus inhabitants, to be built annually for the next 34 years. “No one can build that fast or create the infrastructure to meet such demand,” he says.
“There is a huge shortage of doctors expected too,” he adds. “However, there will be a switch to wearables that monitor your body so you will only see a doctor when you are notified of problems reported by your wearables.”
Telemedicine is already here with apps such as Doctor on Demand and is going to become increasingly commonplace in medicine. Even organs are being 3D printed based on individual patients’ own stem cells to avoid rejection.
According to futurist Thomas Frey from the DaVinci Institute think tank, within two decades the largest internet-based firm in the world will be an “education-based company we haven’t heard of yet.”
Frey’s prediction is set against the backdrop of already booming AI research: Google’s DeepMind, IBM’s Watson and Amazon’s drone delivery, to name just a few. The future of education is yet to be defined by any tech giants already investing heavily in AI but Frey says it’s coming and, when it does, it’ll be big.
Abdul Razack is head of big data and analytics at InfoSys. He also believes AI will drive change in the workplace of the future. Companies such as Toyota have already made huge investments in AI for more precise-decision making and others are bound to follow their lead.
In a recent interview, Razack also proposed how AI could cause a paradigm shift in established enterprise culture. “AI will impact the way people work, with a shift from problem-solving being the most coveted skill set to to problem-finding becoming the way to rise the ranks within a firm and drive innovation.”
The coming age of driverless cars will have widespread implications for the future labour landscape too. “Insurance companies and auto repair shops will downsize,” says Hill.
“Many small-town police forces make their budgets off speeding tickets,” he says. “But driverless cars always obey the rules so there will be a significant loss of revenue.” Driverless cars have already started taking over the taxi industry, while interstate driverless trucks are expected to be the norm within a decade, leaving up to three million truck drivers without work. These tectonic labour shifts will have countless indirect implications. Interstate truck stops will become ghost stops as the new driverless trucks will be able to “keep on keepin’ on” 24/7, 365 days a year.
No sector is immune to the rise and rise of automation. Oil and gas workers in the United States and elsewhere have traditionally enjoyed some of the highest-paid blue-collar work. Every day, however, more and more manual tasks once the responsibility of an oil man/woman have been automated through wireless technologies which allow a small group of geoscientists and engineers – working remotely – to oversee the drilling and completion duties of several wells simultaneously. Swiss technology company ABB recently established two new factories in Houston, Texas, for the manufacture of robotics specific to oilfield operations.
“We’re heading toward artificial intelligence and machine learning, analysing thousands of algorithms,” says Joey Hall, Pioneer’s executive vice-president for Permian operations, of the Texan oil and gas industry. “Through repetitive operations you learn the patterns, and through patterns you learn to make automated decisions.”
While increased automation of day-to-day operations in oil and gas or any other field means job losses for some, innovation can create opportunities for early adopters. Future economies will depend upon workers with specialised skill sets. Data analysts, maths scientists, communications specialists and robotic design engineers will have their pick of careers.
That being said, Prof Paul Springer from the University of East London School of arts and digital industries warns of adopting new tech too early. “Incremental steps make money, radical ones don’t,” he says. “Make decisions in real time – you need to be iterative and responsive to quick change – and don’t get carried away by new media and formats.”