Some are more equal than others: technology, education and inequality

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 inequality is being driven by technology. 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.

 

Alternative viewpoints

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.’

Technology is a tool – and it’s how we choose to use that tool that counts. Blaming technology is a handy technique for political elites; it means they can claim inequality is not politically driven or that political decisions could not reduce it. Globally, real GDP growth has increased from just under 3% (trend) in 1980 to just over 4% (trend) in 2015 (estimated figure; source IMF). Meanwhile, poverty headcount rate has dropped dramatically, from 37.1% in 1990 to 12.7% in 2012.  (Source: World Bank.) So wealth across the world is growing; but it it’s growing at a far greater pace for the very rich than it is for everyone else.

If technology is not to blame, what is? Economist Thomas Piketty argues that the gap between rich and wealth is now far more extreme than could have been imagined just a few decades ago. In the US, the richest 1% of the population now owns over one third of the country’s accumulated wealth. 15% is owned by the top 0.1%. Recessions slow down but do not alter this trend – ‘inequality has only gotten worse since the last recession ended,’ writes David Rotman. ‘The top 1 percent captured 95 percent of income growth from 2009 to 2012, if capital gains are included.’

What are we to make of this? ‘The disparity in the portion of income earned from work—what economists call labor income—is particularly striking,’ says Rotman. Wage inequality in the US is ‘probably higher than in any other society at any time in the past, anywhere in the world,’ says Piketty. ‘In the aftermath of the recession, much of the recovery went to the very rich,’ says Rotman. ‘Meanwhile those with low levels of education are falling behind.’

For Piketty, much of the problem lies with salaries paid to ‘supermanagers’. Rotman’s article points out that according to Piketty’s figures, ‘about 70 percent of the top 0.1 percent of earners are corporate executives.’ Usually, rising inequality is explained by the race between demand and supply of high skills. ‘I think that this is an important part of the overall explanation,’ Piketty says, ‘but this is not all. In order to explain why rising inequality has been so strong at the very top in the U.S., one needs more than a skill-based explanation.’ The answer is to found in ‘pay-setting institutions and corporate governance,’ and Piketty concludes, ‘above a certain level, it is very hard to find in the data any link between pay and performance.’ Again – the problem is political, not technological.

In the UK and to an extent France the problem is slightly different; ‘accumulated wealth, much of it inherited, is returning to relative levels not seen since before the First World War,’ according to Rotman. ‘Privately held wealth in some European countries is now about 500 to 600 percent of annual national income, a level approaching that of the early 1900s.’

For Piketty, this is ‘a radical departure from how we have thought about progress.’ Inequality is supposed to reduce as countries become more technologically developed. ‘Many of us suppose that our talents, skills, training, and acumen will allow us to prosper; it is what economists like to call “human capital.” ’ But – this is not happening.

 

Creating connections

It’s at this point that the importance for higher education becomes apparent. ‘Though income growth among the top 1 percent is an important phenomenon,’ writes David Rotman, quoting his colleague David Autor, a MIT economist, ‘the disparity in skills and education among the other 99 percent is “a big deal, a much bigger deal.” The gap between median earnings for people with a high school diploma and those with a college degree was $17,411 for men and $12,887 for women in 1979; by 2012 it had risen to $34,969 and $23,280. Education, Autor says, “is the most powerful thing you can do to affect lifetime earnings.” ’

Rather than driving inequality, technology drives connectivity. From a higher education perspective, it enables people to learn anywhere, reduces access costs, reduces the costs project work and real-time modelling, enables people to stay in touch cost-free and aids collaboration.

So where from here? What we as providers need to do is to find ways of creating greater access to learning, within this changed environment. And technology is the best way to do that – as we’ll see for several reasons.

Providers do have to take some of the rap for the disconnect between what they think makes a fit-for-purpose graduate, compared with what employers think. McKinsey’s recent Education for Employment survey found that 74% of providers think graduates leave university prepared for an entry-level position. But ask employers, and the figure you get is just 35%. Nor are graduates themselves under any illusions, with 38% answering positively to the same question.

With rising inequality in mind, MIT economist Damon Acemoglu argues how essential it is for education to come to the forefront as traditional low-skill jobs become increasingly automated. ‘I think most people are not sufficiently informed about the sort of skills that they will require,’ he says. ‘There isn’t quite enough of an understanding that most U.S. workers who don’t have college degrees are not going to be able to get good-paying manufacturing jobs.’ For Acemoglu, ‘those types of bread-and-butter jobs of previous decades have gone; now those tasks are being performed by robots and computers.’ Instead, there is an ‘explosion’ of demand in the service sector; ‘in middle- and low-skill services, for example, in health care, clerical occupations or customer service.’ Acemoglu’s belief is that ‘for the most part, U.S. workers, especially U.S. males, haven’t really made the transition to performing them.’ And this is where up-skilling – via education – becomes both paramount and urgent. ‘These are jobs that workers with high school or two-year college degrees can perform.’

The importance for HE is also highlighted in a new report published by the World Bank Group’s Trade and Competitiveness Global Practice. Technology, Growth and Inequality by Ivan Rossignol outlines a way for governments to promote the benefits of technology whilst protecting the economic income of citizens. Essentially, the answers are to focus energies on accelerating some areas and containing others:

 

Accelerate

  • Education
  • Skills
  • Healthcare
  • Connectivity and trade
  • Pace of reform

 

Contain 

  • Regulate new sectors
  • Protect trade and investment barriers
  • Protect social benefits

 

This is, let’s keep emphasising, a political framework. It will not happen by goodwill, good intentions and hope – it needs to be driven by governments. Where it’s sadly unlikely to fulfil its potential is that principles such as protecting social benefits and increasing healthcare provision are seen as left-wing principles, and dominant economies tend to be run by neoliberal, right-wing governments. However, we can at least lay these principles on the table, and offer them for consideration.

And what can be done is to improve things as best we can within our resources – which is to focus on giving students of all backgrounds the best chances they can get, and focus efforts on removing price barriers for them wherever possible.

A way to drive this is to emphasise that happiness and welfare are important and fundamental. They are not secondary to economies; they underpin economies. They are hard to measure – and as importance is always skewed to that which can be measured, suffer as a result.

Technology can help economies, prosperity and social wellbeing, but it has to be driven forward by real people. To do this, we need more virtuous entrepreneurs. At ELU, we try to create social capital by actively reducing the skills gap, increasing digital learning wherever possible, using asset-light campuses, focused on competency-based learning and branding EU-wide, to remove associations with elitism. Our ethos is to encourage personal freedoms and create a focus on jobs and empowerment, funnelling students to a job at the end of the process. Judicious and disruptive use of technology is a key part of this.

Consider the Legatum Prosperity Index – which attempts to resolve the ‘hard to measure’ issue by arguing that ‘national success is about more than just wealth.’ Moving beyond GDP and similarly narrow measurements of prosperity, the Index identifies successful countries and regions ‘against a broad set of metrics covering areas such as health, education, opportunity, social capital, personal freedom and more.’ In other words, it uses subjective as well as objective data – ‘both wealth and wellbeing.’ It includes factors such as democratic governance, entrepreneurial opportunity and social cohesion, all of which do not register in terms of GDP.

For example, in the UK, areas with relatively low GDP can have very high life satisfaction and overall prosperity scores – Devon, West & South of Northern Ireland and Dorset, for example – whereas London region Wandsworth emerges as number 1 for GDP per capita, but is way down the life satisfaction index at number 132 (of 170).

If nothing else, such figures demonstrate that living in areas of high GDP has no correlation with personal satisfaction and happiness. Rather than chasing GDP, we should be examining what improves people’s quality of life – and education is a key part of this.

If there is doubt that social wellbeing is important for economic development, consider the model below. Published by the Legatum Institute, it argues that the more social wellbeing flourishes, the more economic prosperity does too. In other words, social wellbeing and personal empowerment is a fundamental part of economic prosperity – not a result of economic prosperity.

 

[See image on page 2 of this link]. Source: Legatum Institute, Prosperity and its Distribution: Measuring Progress Towards a Prosperous World for All.

 

Is university a luxury club?

In today’s knowledge economy with data, knowledge and insights available at the click of a button, the traditional university – brick walls, strict entry criteria, a homogenous culture and self-perpetuating ecosystem – would never have been invented. This is not to say that traditional universities are no longer fit for purpose. But it does say that there is plenty of room for other, non-traditional learning providers to come to the fore, offer something different and enable those students who for financial, geographical, cultural or other reasons are unable to join the traditional university model.

Previous articles have discussed how technology has enabled the rise of blended learning, bootcamps and nanodegrees. Learning and transformation is the important thing, not being part of an elitist club. ELU wants to contribute to the levelling of the playing field for people who have the abilities, talent and potential for university but are excluded (or feel they are excluded) by traditional suppliers.

Consider the German model of ‘dual’ Vocational Education and Training. In essence, this system offers apprenticeships in the workplace combined with a ‘vocational school’, offering classroom-based education. ‘Perhaps the most striking feature of this system, for those unfamiliar with it, is the engagement of businesses (and employers in general) in the conception and implementation of dual apprenticeships,’ says the Bertelsmann Stiftung report Cooperation in action:  the dual vocational training system in Germany. In practice, this means that ‘co-operation between employers, vocational schools, chambers, governmental bodies and labour unions is at the heart.’ The dual system ‘seeks to provide the labour market with the skilled workforce it requires and to equip young apprentices with market-relevant skills for their future professional lives. Given that it is employers who are the ultimate users of skills, it is eminently sensible to involve them in both the conception and the implementation of dual training programmes.’

Recently in the news is Andela, a company that assesses tens of thousands of tech applicants from across Africa and then selects the top 1% of talent. As well as match-making high-achieving individuals with companies, the model is creating social prosperity too – enabling talent that might otherwise not have access to good jobs, to reach large corporates and build a successful career. The company’s innovative model has now been recognised by Facebook founder Mark Zuckerberg, who along with Priscilla Chan has shown confidence in Andela’s potential by investing $24 million in it.

There are several ways to define the non-traditional university, for students who want to achieve their potential but feel they won’t be accepted on the classical model.

 

  • Rethink the role of academics – the learning experience is shaped to the ultimate workplace, not the campus.
  • Equality becomes part of the university brand. Many classical models present themselves to the world as exclusive and best-in-class. Whilst the quality of the teaching should be peerless, the university itself should not be advertised as elitist.
  • Help less privileged students – financially, socially and culturally.
  • Be a connection hotspot. University is about learning, incubating talent, and facilitating growth. It is not a static, self-perpetuating ecosystem where responsibilities stop the moment the student graduates.
  • Focus on the freelancer economy. Jobs are no longer for life. Help students thrive in the new flexible contract world.
  • A lifelong learning approach. Continuous professional development is the key to success in this new world. Help students adopt this mentality, rather than sustaining the sense that learning stops when you graduate.
  • Empower students to become entrepreneurs – build that philosophy as part of their armoury.

 

Technology is not going to solve inequality, because that can only be done by political will; regulation and taxation with voter support. In MIT Technology Review, David Rotman writes, ‘Since the 1950s, economics has been dominated by the idea—notably formulated by Simon Kuznets, a Harvard economist and Nobel laureate—that inequality diminishes as countries become more technologically developed and more people are able to take advantage of the resulting opportunities. Many of us suppose that our talents, skills, training, and acumen will allow us to prosper; it is what economists like to call “human capital.” ’ Quoted in the article, Thomas Piketty states dolefully that the hope that technology will lead to ‘the triumph of human capital over financial capital and real estate, capable managers over fat cat stockholders, and skill over nepotism’ is ‘largely illusory.’

No one would deny that there’s considerable work to be done. But let’s move away from blaming technology for inequality and see where the real perpetuating and widening of inequality lies – with political decision-making that protects the interests of a very small elite. Recent scandals such as the Panama Papers show how such elites are able to drain economic sources whilst avoiding contributing to the host countries where they pay staff as little as they can get away with. If that can be stopped, inequality will reduce as a consequence. Technology, meanwhile, rather than being scapegoated, should be embraced.

 

Sources

Kaushik Basu comments: https://www.weforum.org/agenda/2016/01/is-technology-making-inequality-worse/

Colin Gordon comments: https://www.dissentmagazine.org/article/the-computer-did-it-technology-and-inequality

Daron Acemoglu on inequality: https://minneapolisfed.org/publications/the-region/interview-with-daron-acemoglu

Stats on tech and inequality:

MIT Technology review quotes (Brynjolfsson, Steve Jurvetson and Thomas Piketty): https://www.technologyreview.com/s/531726/technology-and-inequality/

Further Brynjolfsson quotes: http://www.businessinsider.com/erik-brynjolfsson-2014-1?IR=T

Further Brynjolfsson: https://www.technologyreview.com/s/515926/how-technology-is-destroying-jobs/

Legatum Prosperity Index: http://www.li.com/programmes/prosperity-index

Fundación Innovación Bankinter  model: https://www.fundacionbankinter.org/ftf_j2016

Andela: https://andela.com/

Andela financing: http://money.cnn.com/2016/06/16/technology/andela-24-million-chan-zuckerberg-foundation/index.html

Dual vocational system in Germany: http://www.bertelsmann-stiftung.de/en/publications/publication/did/cooperation-in-action-the-dual-vocational-training-system-in-germany/

World Bank and IMF growth figures and Ivan Rossignol material:

https://www.fundacionbankinter.org/documents/20183/85804/Ivan+Rossignol+June+2_Technology+Growth+and+Inequality/8ff7578d-71bd-42bd-b218-2622f90d8aaa

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