The skills that matter in the race between education and technology

Depending on to whom you listen, automation, robotics, and artificial intelligence (AI) will either solve all our problems or end the human race. Sometime in the near future, machine intelligence is predicted to surpass human intelligence, a point in time known as “the singularity.” Whether the rise of the machines is an existential threat to mankind or not, I believe that there is a more mundane issue: robots are currently being used to automate production.

Economist Richard Freeman argues that robots can be a substitute for workers, even highly skilled professionals. In addition, MIT professors Erik Brynjolfsson and Andrew McAfee suggest that, as computers get more powerful, companies have less need for some kinds of workers. A bigger impact can be felt in developing countries. If computerization makes high-income countries more self-sufficient—less offshoring and more “reshoring”—then developing countries may lose their wage advantage. Besides slowing employment growth, automation may also increase income inequality. Technological disruption is widely being debated in industrialized, high-income countries; however, policymakers in developing countries need to start worrying about the impact of automation as well.

There is a critical skills gap
Technology rapidly changes the workplace and the skills demanded, immediately making current workers less employable. Meanwhile, education systems are slow to change in terms of the creation of new skills. As the demand for new skills increases, the challenge will be to anticipate what those skills might be. For some the answer is science, technology, engineering, and mathematics (STEM) skills as well as coding so that people can develop or work with the technology.
 
An alternative approach is to think about the kind of work that technology cannot replace. The Oxford Martin School stud­ies the vulnerability of jobs to automation point to those that draw most on creative and social skills, and complex perception and manipulation. Future workers need to make themselves “im­mune” to automation as much as possible. I believe that this does not mean that basic skills do not matter. In fact, we are seeing high returns to cognitive skills, especially non-routine skills.
 
These skills are:

• Problem-solving skills to think critically and analyze
• Learning skills to acquire new knowledge
• Communication skills, including reading and writing
• Personal skills for self-management, making sound judgments and managing risks
• Social skills for collaboration, teamwork, management, leadership, and conflict resolution

Prepare students for the future world of work
Automation implies both deskilling and the need for new skills. For many developing countries, nurturing basic skills remains the most urgent priority. Early reading fluency is paramount, since in the digital economy lifelong learning becomes the key to success. In addition, skills needed for success are not likely to come from the usual sources. The most promising models of education and training that can deliver basic and new skills focus on the elements of effective education systems. Systems that do well prepare children early on, reform continuously, and use information for improvement and accountability.

The following components are necessary to achieving such reform:

1. Assessment: Measurement is the cornerstone of education planning and reform aiming to improve quality. Countries that are unable to determine where their education system stands currently will find it difficult to make improvements or to reach their goals. One example of success in this area can be found in Jordan, where use of international tests for benchmark­ing and the use of feedback loops led to impressive gains.  
2. Autonomy: Empowering schools will support quality improvements. This includes giving them ownership, resources, and voice.  
3. Accountability: Accountability increases time on task and academic achievement. An ac­countability-based system usually entails a shift of decision-making authority from the gov­ernment to the community, which is represented by school governing boards and integrated by teachers, parents, and community members.  
4. Attention to teachers: Studies across the world show that a good teacher—one that adds value to the learning process—can be effective in helping students to improve their learning out­comes. The top-performing school systems recruit their teachers from the top third of each graduate cohort.  
5. Attention to early childhood development (ECD): Such programs may be the most cost-effective investment. Empirical evi­dence demonstrates that quality ECD interventions increase educational success and adult productivity, and decrease public expenditures later on, as in the case of Jamaica.  
6. Attention to culture: Culture is important and often neglected. The use of the mother tongue as the language of instruction is one cultural area frequently disputed in many countries. In many countries, a significant number of students do not speak the national language in the home, which has practical implications for education. Schools using mother tongues as the language of instruction have higher attendance and promotion rates, and lower repetition and dropout rates.

To improve learning outcomes and prepare students for the world of work, countries must develop a system to determine current learning levels and future learning aims. Policymakers need to consider each aspect of the education system in defining an appropriate reform that will provide an inclusive and holistic approach to improving education outcomes. If this happened, then it wouldn’t matter much whether or not the robots are coming.
 
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A paper under the same title as this blog post was prepared for the 2016 Brookings Blum Roundtable.

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