The economist and author speaks to AIQ about the new technological breakthroughs reshaping economies and societies in both East and West.
Erik Brynjolfsson, a professor at the Massachusetts Institute of Technology and director of the Initiative on the Digital Economy at the Institute, is a world-renowned expert on technological innovation.
He is the co-author, with Andrew McAfee, of The Second Machine Age, a bestselling study of the economic consequences of new technological advances.
His most recent book, Machine, Platform, Crowd (also co-authored with McAfee), examines a ‘triple revolution’ in technology, comprising three shifts: a shift from human decision making to machine-based learning; a shift from products to platforms (such as Uber and Airbnb); and a shift from companies’ ‘core’ (or internal) expertise to crowd-sourced learning and problem-solving.
Professor Brynjolfsson spoke to AIQ about these seismic shifts in innovation, and the changing balance of power in technology between East and West.
The first part of the ‘triple revolution’ you describe in Machine, Platform, Crowd is the shift from human-to machine-based decision-making. How are machine algorithms improving decision-making?
Today, for the first time in human history, we have literally billions of people who can communicate on a digital infrastructure, the internet, and you can tap into them.
Over the past couple of decades, more and more digital data has become available, and that’s the lifeblood of data-driven decision-making and artificial intelligence. It’s worth distinguishing here between two approaches. One is data-driven decision-making, which is using large data sets to make better decisions; this is something that’s spread through the American economy and worldwide. Data-driven decision-makers are about five per cent more productive than competitors that don’t use data-driven approaches.
The second big wave we’ve seen is in machine learning and AI. It’s still early days, but for certain categories – advertising, medical imaging and some manufacturing applications – machine learning has been really effective in helping with decision-making as well. I expect that to accelerate a lot in the coming years.
Human-machine ‘partnerships’ are also key to what you call ‘the shift from core to crowd’. How is this opening up new opportunities for innovation?
The same digital platforms that provide digital data also connect people. Today, for the first time in human history, we have literally billions of people who can communicate on a digital infrastructure, the internet, and you can tap into them. Companies have begun to use the power of the crowd to innovate and solve problems their ‘core’ researchers and executives aren’t able to solve.
For instance, in medicine, the crowd has massively improved experts’ ability to sequence the DNA in white blood cells. The National Institute of Health and Harvard Medical School were working on this, and though they had a lot of expertise, ultimately the big breakthrough came when they opened the problem up to a crowd of experts across the world. These experts had very different approaches to the problem; they came from areas as diverse as petroleum engineering or crystallography, and some of the techniques they applied led to a 100-fold improvement in the performance of the relevant algorithms. There are many examples like this, of the crowd developing software faster, finding bugs, solving puzzles.
Chinese companies have proved adept at exploiting the power of the platform and the crowd. Are there any areas in which China is moving ahead?
China has been successful in so-called ‘O2O’ or online-to-offline innovation. In many ways, China is ahead of the West in terms of using smartphones and the smartphone platform for payment systems. If you compare the US to China, the number of people using payment systems on their mobile phones is literally 50 times higher in China; that’s a real, fundamental difference. It makes a self-reinforcing virtuous cycle, where other people start putting their businesses on this platform and that starts generating even more users.
You argued in The Second Machine Age that technological innovation would lead to higher growth and productivity. Are you still optimistic these benefits will soon begin to show in Western economies?
Companies have begun to use the power of the crowd to innovate and solve problems.
I am. There’s a lot of pent-up innovation in areas like machine learning. What you see in the laboratories is remarkable, but most of it hasn’t really made its way out into the marketplace yet. That doesn’t mean those benefits are not coming; I think they’re in the pipeline. This is very common with these fundamental technologies, going back to electricity or the steam engine. It can take literally years or decades before the full impact of investment in these core technologies happens in an economy.
The real bottleneck these days is less in inventing amazing new technologies; it’s in implementing them; it’s in organisational change, management culture, regulation. These can be obstacles to the adoption of some of these new technologies.
Does the Chinese political system give its companies any advantages or disadvantages over Western firms when it comes to implementing the innovations you describe?
There’s a culture of innovation and entrepreneurship in China, which is pretty infectious. And there are very few regulatory barriers from the government – for better or worse – that impede organisations and entrepreneurs from setting up all sorts of businesses.
This is something that’s happening rapidly, and the idea of ‘permissionless innovation’ is a very powerful one. Chinese companies can try a lot of new things without a lot of respect for, say, privacy or environmental regulations, and that allows them to innovate faster. The flipside is that some of the water in China isn’t all that clean and some of the air isn’t all that clean and the privacy protections aren’t in the place where Westerners would feel comfortable. So it’s a mixed bag, and every society and culture is trying to find the right balance.