Technology, education and inequality
Part one: Some are more equal than others
Does technology cause inequality? Perhaps surprisingly, in our age of increased access to information, open platforms and ability to self-educate, there are rumblings that this is the case. Writing recently at the World Economic Forum, Kaushik Basu, Chief Economist at The World Bank argues that ‘the only countries recording high rates of annual GDP growth are emerging economies, including Vietnam (6.5%), India, China, Bangladesh, and Rwanda (around 7%), and Ethiopia (over 9%).’ Basu then goes on to postulate that, despite the growth of labour-saving technology (‘global sales of industrial robots… reached 225,000 in 2014, up 27% year on year),’ we are now seeing ‘disparate performance,’ created by technology. ‘High- and middle-income countries will come under strain, as their workers compete for jobs in the globalized labor market. Their income disparities will tend to rise, as will the frequency and intensity of political conflict.’
This trend is likely to be maintained, Basu believes. ‘As the march of technology continues, these strains will eventually spread to the entire world, exacerbating global inequality — already intolerably high — as workers’ earnings diminish. As this happens, the challenge will be to ensure that all income growth does not end up with those who own the machines and the shares.’
Similarly, Rolf Brynjolfsson has attributed the rise of inequality to technology. ‘There’s globalization, there are institutional changes, cultural changes, but I think most economists would agree that the biggest chunk of it is due to technology,’ he says in Business Insider. ‘And that’s because of what economists call skill-biased technical change — favoring skilled workers versus less-skilled workers.’
Brynjolfsson’s concern is primarily the way robots are squeezing out lower-paid jobs. Despite admitting that productivity has slightly grown in the last decade, ‘central to Brynjolfsson’s argument is the idea that innovation is rapidly accelerating as trends in computing and networking advance at an exponential rate,’ writes Joe Wiesenthal. While the GDP pie is increasing, ‘not everyone is benefiting,’ and Brynjolfsson lays this problem squarely with technology.
‘The biggest factor is that the technology-driven economy greatly favors a small group of successful individuals by amplifying their talent and luck,’ Brynjolfsson observes. These individuals, Brynjolfsson argues, reach stratospheric levels of income because successful ideas can be widely experienced and distributed. We don’t have lots of regional Facebooks, tailored to communities, countries or even continents. We have one Facebook, and the competition doesn’t stand a chance. This ‘Google-isation’ of our commodities is, for Brynjolfsson, an explanation for why very few people are earning huge amounts of money. ‘Why use a search engine that is almost as good as Google?’ as MIT Editor David Rotman puts it.
And for Brynjolfsson, what is the common factor? It’s that these super-fast, super-rich entrepreneurs all make their money via technology. This money does not trickle down to employees; it stays locked in the hands of a new technology elite.
Certainly, inequality is rising globally. And when it comes to higher education, the differences between haves and have-nots are becoming acute. Some 42% of young people now cannot afford to go to university, and 59% of graduates are unemployed. Yet, we would argue that this has not come about because of technology. Correlation is not causation — these unfortunate figures are part of a much wider platform of political infrastructure and global recession. The huge cuts in higher education funding worldwide have increased inequality far more than technology has.
It doesn’t take long to find figures critical of Basu or Brynjolfsson’s stance. Colin Gordon, professor of history at the University of Iowa, says ‘the notion that inequality is generated by rapid technological change and skill shortages is not sustained by the recent American experience. If demand for certain workers or certain skills were reflected in wages, we would expect to see wage gains where that demand was highest and wage stagnation where it was weakest.’ For Gordon, this is not the case. ‘Since 1969 labor’s share of income has fallen most rapidly in those sectors where union presence withered, not where computers displaced labor.’
Gordon point outs that ‘across our last two business cycles, income concentrated not in sectors or regions where skills were most in demand but where speculative bubbles (dot-com, housing, finance) bloomed and burst. During our most recent recession and recovery, the notion of a “skills shortage” was belied by the fact that job openings and available workers were distributed fairly evenly across the economy, and that skilled workers saw no “bidding up” of their wages or increase in their work hours. Indeed, most of the growth in wage inequality across the last generation can be found within occupations, and not in their relative share of the labor market.’
Gordon argues that ‘whatever causal importance we assign to technological change, it is hard to see it as a credible account of the different trajectories of inequality across countries. Technological change is a challenge faced by all national economies, and the secular decline in labor’s share of national income is common to most advanced economies. And yet on key measures of inequality, differences across national settings (and especially the outlying status of the United States) remain profound.’ He concludes that ‘in both 1985 and 2007, the United States leads the pack in both educational attainment and inequality.’
In part two of this article, published Tuesday, we’ll examine the fact that technology is a tool, and it’s how we choose to use this tool that counts.
Originally published at http://elu2016.wordpress.com/
Sources are at the end of the final part of this article.