On the heels of my recent foray into A.I., I’ve been reading a bunch of books on our coming technological utopia: Yuval Harari’s Homo Deus, Peter Diamandis’s Abundance, Steven Pinker’s Enlightenment Now and Ray Kurzweil’s The Singularity Is Near. They’re quick reads, because they all say basically the same thing. Thanks to emerging ‘exponential technologies’ (i.e., Artificial Intelligence, Internet of Things, 3D printing, robotics and drones, augmented reality, synthetic biology and genomics, quantum computing, and new materials like graphene), we can and will build a new and better world, free from the physical, mental and environmental limits that today constrain human progress.

It all seems so clear. So possible.

To muddy the waters, I sat down for coffee with my pal and frequent co-author Ian Goldin, who throughout his whole career—from advising Nelson Mandela in his home country South Africa, to helping shape the global aid agenda as a senior exec at the World Bank—has labored to solve poverty. (His book, Development: A Very Short Introduction, is, as the title suggests, an excellent starting point on the subject.)

I wanted to explore the ‘hard case’ with Ian. And the hard case is poverty, in its many manifestations. Whether these ‘exponential technologies’ relieve me of the burden of leaving my London flat to buy shaving blades is one thing; whether they can help relieve the burden of poor sanitation in Brazilian favelas is another thing entirely.

Question: will the sexy new technologies that scientists and techies are now hyping really give us the weapons we need to solve the hard problems that plague the world’s poor?

Answer: Not unless we first address ‘four naïvetés’ in our thinking about the relationship between ‘technology’ and ‘development.’

Vanishing Jobs: No Ladder To Climb

The first naïveté concerns jobs. Automation is making the existing model for how poor people get richer obsolete. How did China grow its economy from insignificant in the 1970s, to the world’s largest today? That ascent began with low-cost labor. Foreign manufacturers moved their factories to China. The money they saved by paying lower wages (in the early 1990s, the average Chinese factory wage was US$250 per year) more than offset the increased cost of shipping their products all the way from China to their customers.

Today, average factory wages in China are quite a lot higher (the latest stat I’ve seen is US$10,000 per year). The countries that can boast loudest about their low-cost labor supply in 2018 are places like Burundi, Malawi and Mozambique. Unfortunately for them, fewer and fewer foreign manufacturers see low-cost labor as a winning strategy. Nowadays, in industries ranging from smartphones to automobiles, increasingly capable and affordable factory robots can crank out more, better, customized products than an assembly line staffed by humans ever could. In the rapidly arriving world of robot factories, it is not the cost of labor, but rather the cost of capital, that determines a factory’s profitability. And capital—whether in the form of a bank loan, a public offering of stock, or private equity investment—is much cheaper and easier to raise in the mature financial markets of New York than in New Delhi or Côte d’Ivoire. How will Africa ever repeat China’s economic climb, if the first and lowest rung on the development ladder—i.e., a low-cost labor advantage—has been sawed off by robots?

Gravity’s Pull (and the Pooling of Scarce Skills)

The second naïveté concerns choice. It’s a safe assumption that births of big-brained people are evenly distributed across the whole of humanity. From Canada to Cameroon, a similar share of the population is born with the raw intellectual horsepower needed to understand and push the boundaries of today’s science and technology. And thanks to the internet, mobile data and digital knowledge platforms, whether in Canada or the Central African country of Cameroon, such big-brained people now have a better chance than at any other time in history to nurture that intelligence. Genius is flourishing. Globally.

But as it matures, genius tends to pool in just a few places. That’s because, while the odds of winning the intelligence lottery at birth might be distributed evenly everywhere, the opportunities to cash in that winning ticket are not. Those opportunities pool. Within countries, they pool in the cities and on the coastlines. Between countries, they pool in the fastest-growing and richest economies. If I am a talented data scientist in Cameroon, am I going to start up a business in my capital city of Yaoundé (maybe) or (more likely) get on a plane to Silicon Valley, where the LinkedIns and Facebooks of the world today dangle US$2 million starter salaries in front of people with skills like mine? (Right now, even top-tier US universities struggle to retain skilled staff when Silicon Valley comes recruiting. How on earth can Cameroon compete?)

If technology does drive progress, and if the skills needed to drive the technology are scarce, then progress will remain uneven—and poorer places will continue to lag behind.

Politics Are Unavoidable—And Decisive

The third naïveté (or maybe it’s 2(b)) concerns distribution. Every technology has strong distribution effects. It generates winners and losers. Some own it; others pay to use it. Some build it (and accumulate valuable equity); others buy it (and accumulate debt). Some talents are in high demand, and salaries soar; some talents are no longer required, and jobs are lost.

That’s life. How society chooses to respond to these distribution effects is a political question, one that every community answers for itself (albeit with varying degrees of popular awareness and participation). Public institutions and laws passed by the political system (regarding, say: property rights, taxation, transparency and oversight) shape what happens after the gains and losses are won and lost.

If the big topic we’re interested in is “progress”, then we need to take an interest in these political questions. Technologies never, ever yield progress by themselves. (For the clearest evidence, look no further than the United States. Since 1990, U.S. society has undergone an astonishing technological transformation: the advent of the Internet; the advent of mobile phones (and now, the mass adoption of mobile broadband data); the mapping of the human genome and advent of genetic medicine; the advent of autonomous vehicles; the advent of commercial space travel; the advent of e-commerce and social media; the advent of 3D printing and nanotechnology and working quantum computers; the advent of turmeric lattes. And yet, for all that, the average salary of people in the bottom 20% of US wage-earners is lower today, in real-dollar terms, than it was 28 years ago. Put another way, the bottom 20% of wage-earners are taking home less pay today than they did back when the overall US economy was only half its current size. If we’re talking about economic progress, it’s pretty clear that there’s been a lot for some, and less than none for others.

All ‘Technology’ Is A Solution AND A Problem

The fourth naïveté concerns the social nature of technology. Technology may be a solution, yes, but it is not only that. It is also a package of unintended risks and consequences that need to be managed by society. The most infamous example is the Bhopal disaster in India in 1984. A leak of toxic gas at Union Carbide’s pesticide plant killed thousands and injured hundreds of thousands more. It was the 20th century’s worst industrial accident.

The intended consequence was to catapult India’s farmers into the future. A Green Revolution was underway! New, chemical fertilizers were lifting crop yields to never-before-seen heights! By importing the latest fertilizer technology from the U.S., India would join that Revolution and banish the specter of mass starvation from its borders.

Instead, the disaster demonstrated how wrong things can go when we transfer the material components of a technology from one society to another, but ignore its social components: risk assessment, regulation, ethics, and public awareness and participation.

In short: a society is a great big, complex system. Technology is just one input. Other inputs, stocks, flows and feedback loops also determine what the eventual outputs will be.

Technology = Progress?

The deepest naïveté—the belief lurking in the background of all the above—is that technological change is a good thing.

This is one of the Biggest Ideas of our time—and also one of the least questioned…