- By Jamie Shea
Automation is accelerating the race between education and technology. The ability of education systems to respond to the demand for higher-order skills will be crucial for mitigating the income inequality resulting from automation. But many of Europe’s education systems still struggle to provide basic skills to large proportions of the population.
The idea that workers would find themselves caught in a race between education and technology emerged in the 1970s with Dutch economist, and first recipient of the Nobel Memorial Prize in Economic Sciences, Jan Tinbergen’s observation that technology benefits high-skilled workers’ productivity more than that of low-skilled workers. This skill-biased technological change, many argue, is behind rising wage disparity between more and less educated workers since the 1980s in high-income countries. In this sense, rather than being the great equaliser, education has engendered further inequality.
But much has changed since Tinbergen’s era. The type of education required of workers has shifted. Advances in artificial intelligence have significantly altered our expectation of machines’ capabilities. As machines replace not only routine physical tasks, but also many types of cognitive tasks, occupations are expected to require increasingly higher-order cognitive skills – such as critical thinking and problem-solving – as well as non-cognitive skills.
Research, including that produced by the World Bank, suggests that educational attainment, cognitive skills, and general – rather than vocational – education can help workers counter automation technology. Many experts on artificial intelligence go even further, arguing that humans’ comparative advantage lies predominantly in non-cognitive skills of social intelligence and creativity. This has profound implications for education systems.
Perhaps more alarming, however, is the stagnation in learning outcomes
Despite the importance of higher-order skills, evidence suggests most European education systems struggle to provide advanced cognitive skills. For example, according to the 2015 OECD PISA study, fewer than 10% of students in most countries attained advanced science proficiency. In fact, many systems struggle to provide basic cognitive skills: the percentage of students not achieving minimum science proficiency is higher than 20% in 11 OECD European countries and higher than 50% in four emerging European countries.
Perhaps more alarming, however, is the stagnation in learning outcomes. Only one European country, Portugal, witnessed an increase in the percentage of students achieving either basic or advanced science proficiency between 2006 and 2015. European education systems can respond to demand for educational attainment – as evidenced by increasing enrolments – but they have failed to address the demand for cognitive skills directly.
Increasing skill acquisition requires drawing on learning sciences to identify and evaluate new child development or pedagogic approaches. Policymakers should also look to management and policy sciences to ensure all relevant actors in the education system are correctly incentivised and informed.
Automation’s contribution to inequality is fundamentally a result of its skill-biasedness
The use of rigorous empirical methods including randomised-control trials to evaluate and develop pedagogic or policy interventions is becoming increasingly mainstream, and governments should encourage more investment in this type of research. However, for many countries, the priority should be on basic cognitive skills rather than higher-order ones.
Several countries stream students into vocational education programmes that typically deemphasise cognitive skills. Research from the World Bank indicates that vocational students’ cognitive skills lagged far behind those of their general education peers in most countries. Streaming individuals into vocational programmes based on lower cognitive ability (even if implicit) reduces education systems’ capacity to respond to demand for cognitive skills. Vocational streaming on the basis of lower cognitive ability also implies that technical occupations will require less cognitive ability, which counters expectations of automation. Vocational streaming needs to be reformed. Poland, for example, delayed vocational streaming by one grade level as part of its 1999 education reform, resulting in a substantial increase in students’ cognitive achievement.
Debate on policy responses to automation have typically focused on active labour market policies, retraining, and wealth redistribution. But automation’s contribution to inequality is fundamentally a result of its skill-biasedness. Education can help circumvent the need for labour market programmes and wealth redistribution in the future but only if its quality can keep pace with technology. This means adopting an empirical approach to improving learning outcomes and system management, and for many countries, a focus on improving basic skills first.
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