Erik Brynjolfsson, director, MIT Initiative on the Digital Economy (USA)
Machine learning has advanced tremendously over the past decade, yet US productivity growth has fallen by 50% since 2004. It’s not uncommon with powerful new general-purpose technologies to see first a dip in productivity growth followed by an increase. It takes time. With the steam engine, we saw the rise of industrialization. With electricity, factories were reinvented. Computers obviously changed many aspects of society, but e-commerce is still a minority of total retail trade, 25 years after Amazon was started. Likewise, machine learning is going to take a while to propagate through the economy. What’s needed is investments in new skills, and businesses that are willing to fundamentally rethink their supply chains, their relationships with customers, and the kinds of products and services they deliver. As they do that, the productivity is going to come online.
Wanuri Kahiu, science fiction writer and filmmaker (Kenya)
Just as Kenya has been a place where digital payment technologies took off, I think it will become a testing ground for how people interact with AI and robots. The barriers to entry are low and there are few laws or social mores around AI, so it’s like a blank slate for experiments in coexistence between humans and machines. In Kinshasa almost 10 years ago, they installed robotic traffic cops and people obeyed them more than the human police, because the robots were not corrupt. There’s lots of potential for localized AI applications that help Africa deal with African problems, which is important because by 2050, one in four people will be African.
Helena Leurent, director-general, Consumers International (UK)
Consumers will be part of data trusts and cooperatives that can safeguard their rights, negotiate for them on how their data is used, alert them to how they are being watched, and audit organizations that use their data. As an example, consumers might want their respective data trusts to connect directly to farmers who guarantee to use sustainable growing practices. The consumers would get better prices and have more information about what they’re buying; the farmers could get data and guarantees about purchasing patterns and would be able to differentiate their products. This “agricultural data commons” could spark innovation in products and services that both give consumers more choice and lead to greater sustainability.
Michael Casey, chief content officer, CoinDesk (USA)
The dollar is the reserve currency because of its stability. If companies in two different countries sign a contract with payment due in 90 days, they set the transaction in dollars to protect against exchange-rate fluctuations. But when there are digital currencies with programmable smart contracts that can convert at an agreed rate and keep the payment in escrow until it’s due, they won’t need the dollar any more. This means the advantages to traditional US companies will diminish, but innovative, decentralized, globally minded companies will succeed.
Genevieve Bell, director, 3A Institute and senior fellow, Intel (Australia)
Over the last six weeks my country has been on fire, and I think 2030 looks like the world I’m now living in. One, the climate is changing faster and faster. Two, Australians are suddenly having to think much harder about how both their own personal data and government data is made accessible so they can get timely fire projections, evacuation requests, air-quality reports, and so on—so the questions about data that only those of us at the forefront of technology were asking are now mainstream. And three, we’ll have to contend with the fact that all the infrastructures of the 20th century—electricity, water, communications, civil society itself—are brittle, and this brittleness will make the 21st century harder to deliver.
Zachary Bogue, managing partner, Data Collective Venture Capital (USA)
For the last 80 or 90 years our innovation in materials has been driven by petroleum—by recombining petroleum compounds into fuels, plastics, drugs, and so on. I think we’ll look back on the 2020s as a decade of innovation driven by biology. Genetically engineering plants to synthesize chemical compounds opens up a design space exponentially larger than petroleum, to create new materials that will let us live more sustainably and propel the economy forward. It’s already starting to happen—one of the companies we invest in makes a microbe that produces a palm-oil replacement, for example. What’s enabling all this is massive increases in computing power and AI that make it possible to model and design the necessary metabolic pathways.
Ronaldo Lemos, director, Institute for Technology and Society of Rio (Brazil)
By 2030 the most famous mobile-phone brands worldwide will be Chinese and they will run their own operating system, cutting the market penetration of Android in half.
Sharan Burrow, general secretary, International Trade Union Confederation (Australia)
3D printing, automation, and robotics will cause massive localization of manufacturing. If I can go to my local shop and I say I want my jeans with four stripes and three pockets and I want them now, the fast fashion industry is at risk. Food production will become more local too, and efforts to reduce the carbon footprint will change consumption patterns. So the supply chains on which global trade is based—dehumanizing and exploitative though they currently are—will in large part disappear from the most vulnerable countries, leaving the potential for failed states and even more desperate poverty. What we need is alternate modes of decent work, like child care, health care, elder care, education. We need to invest in human infrastructure, in support and services.
Peter Ungaro, CEO, Cray (USA)
For example, there are hundreds of companies that make components for automotive manufacturers. Today they use small computer systems to do CAD drawings of their parts and some simulations. In future, because of all the sensors that will be out there generating data, they’re going to have data sets 10, 100, 1,000 times bigger than today that they can compute on, changing how they model their parts. The technology they’ll do that with will be like a mini supercomputer. Some places will have one on the premises, and others will just access it via the cloud. And it won’t have to be one of these machines that today fill up two basketball courts and consume 30 megawatts. We’ll have it down to a single cabinet.