Computers and the Future of Skill Demand

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Computer scientists are working on reproducing all human skills using artificial intelligence, machine learning and robotics. Unsurprisingly then, many people worry that these advances will dramatically change work skills in the years ahead and perhaps leave many workers unemployable.

This report develops a new approach to understanding these computer capabilities by using a test based on the OECD’s Survey of Adult Skills (PIAAC) to compare computers with human workers. The test assesses three skills that are widely used at work and are an important focus of education: literacy, numeracy and problem solving with computers.

Most workers in OECD countries use the three skills every day. However, computers are close to reproducing these skills at the proficiency level of most adults in the workforce. Only 13% of workers now use these skills on a daily basis with a proficiency that is clearly higher than computers.

The findings raise troubling questions about whether most workers will be able to acquire the skills they need as these new computer capabilities are increasingly used over the next few decades. To answer those questions, the report’s approach could be extended across the full range of work skills. We need to know how computers and people compare across all skills to develop successful policies for work and education for the future.



Implications of computer capabilities for policy and research

Centre for Educational Research and Innovation

This chapter offers an analysis of computer capabilities in the three cognitive skill areas addressed by the Survey for Adult Skills (PIAAC), and the resulting implications for education and labour policy. Drawing upon the analysis of changes in skills and skill use over time outlined in , the chapter assesses the potential for computers to further change the use of those skills at work in the future. The assessment is based upon the judgments of the group of computer scientists set out in about the level of current computer capabilities. The Chapter concludes with suggestions for how this project could be used for future research.



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