The goal, of course, is not to throw 23 million people out of work, but to refocus their talents on productive activities. If each of these individuals contributed $148,000 to the economy, rather than zero, GDP would increase by roughly $3.4 trillion. That gain, if achieved in equal increments over the next ten years, would add nearly 1.6 percent to annual productivity growth, which would more than double the 1.3 percent rate turned in between 2007 and 2018. Achieving similar gains across the OECD would add $10 trillion to global output.
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Rather than deskilling work, we need to upskill employees. Rather than outsourcing low-value jobs, we need to increase the creative content of every role. Instead of assuming that middle-class jobs must ultimately fall to globalization and automation, we need to redesign work environments so they elicit the everyday genius of every human being.
By taking labor ever more out of the equation, automation removes any advantage countries with lower wage demands might have, because the costs of technology, unlike labor, are pretty much the same everywhere.
However, automation is not only likely to entrench further structural inequality between countries. Without a fundamental shift in the way economies are organized, it will dramatically exacerbate inequality within many countries as well. It will do this firstly by diminishing opportunities for unskilled and semi-skilled people to find decent employment, while simultaneously inflating the incomes of those few who continue to manage what are largely automated businesses. As importantly, it will increase returns on capital rather than labor, so expanding the wealth of those who have cash invested in businesses, rather than those who depend on taking cash from them in exchange for labor. This means straightforwardly that automation will generate further wealth for the already wealthy, while further disadvantaging those who do not have the means to purchase stakes in companies and so free-ride off the work done by automata. Of course, this would not be as much of a challenge were it not the case that since the Great Decoupling, the wealthiest 1 percent of people globally has captured twice as much of the new wealth generated by economic growth as the rest of us. The richest 10 percent of people on earth now own an estimated 85 percent of all global assets, and the richest 1 percent own 45 percent of all global assets.
In a recent article called “Are Ideas Getting Harder to Find?,” economists from Stanford and LSE analysed this phenomenon quantitatively. Across a range of industries, across firms, and in the aggregate economic data they found the same thing: progress becomes harder and harder. Based on their numbers, in order to double our overall level of technological advancement, we need to put in, conservatively, four times as much research effort as we did for the previous doubling. To illustrate, suppose (simplistically) that initially it took 10 person-years of “research” to double the world’s level of technological advancement: to move from knowing only how to make a stone axe to knowing how to make both an axe and a spear. In order to get the next doubling of technological progress, it would take 40 person-years of research. The next doubling would take 160 person-years, then 640 person-years, then 2,560 person-years, and so on.
So to think about whether we can sustain technological progress, we have to think about whether we can keep exponentially growing the number of researchers. Consider that there are two ways to do this. First, you can increase the share of the population that is devoted to research. Indeed, we’ve been doing a lot of that, so that’s been the source of most of US technological progress in the last few decades. Technology-driven growth of US per-capita incomes has averaged about 1.3 percent per year. A full percentage point of that comes from increasing the fraction of the population doing R&D and from improving the allocation of talent, such as by reducing gender and racial discrimination.
The second way by which you can increase the number of researchers is by increasing the total size of the labour force: that is, you can grow the population. Over the last few decades, population growth has contributed about 0.3 percentage points to the United States’ technologically driven per-capita growth rate.
My critique of GDP measurement in practice relates to its inability to report sufficiently accurately what it is intended to measure: the value of economic output. And pronouncements based on such data about long-run trends in income or the rate of increase of productivity should be taken with a grain of salt – or several. When pundits fret over whether the latest figure for GDP growth is an annual rate of 1.8 per cent or 1.9 per cent, they are fussing over differences that are insignificant in relation to the fundamental and inescapable uncertainties in the data they are citing.