Drawing the future: What children want to be when they grow up

by Andreas Schleicher
Director, Directorate for Education and Skills

How can we tell if artificial intelligence threatens work?

by Stuart W. Elliott
U.S. National Academies of Sciences, Engineering and Medicine

New technologies tend to shift jobs and skills. New technologies bring new products, which shift jobs across occupations: with the arrival of cars, the economy needed more assembly line workers and fewer blacksmiths. New technologies also bring new work processes, which shift skills in jobs: with the arrival of copiers, office workers needed to replace ink cartridges but not use carbon paper. Economic history is full of examples of new technologies causing such shifts.

Workers often worry that new technologies will destroy old jobs without creating new ones. However, economic history suggests that job destruction and creation have always gone together, with a shift in jobs and skills that leaves most people still employed.

Will artificial intelligence (AI) differ from past technologies in the way it shifts jobs and skills? To answer that question, we need to know which skills will be supplied by AI and which will be left for people. If workers have the skills AI lacks, they will be able to find new jobs if AI automates their old jobs. In that case, AI will shift jobs and skills just like previous technologies. However, if workers do not have the skills AI lacks, these shifts will break down and the institution of work itself will be threatened.

As an example, consider literacy and numeracy. These skills are widely used in many jobs—so widely used that countries invest many years of formal education to help everyone develop them. The OECD assesses these skills in its Survey of Adult Skills (PIAAC) because they are so important for work and education.

A new OECD study uses PIAAC to assess whether AI can perform these skills as well. The study is only exploratory, but its results are sobering. Current AI techniques are close to allowing computers to perform at Level 3 on the 5-level scale in literacy and numeracy—at or above the proficiency of 89% of adults in OECD countries. Only 11% of adults are above the level that AI is close to reproducing.

If literacy and numeracy were the only work skills, this new study would suggest that AI is not like other technologies. As current AI techniques are applied, many workers with moderate proficiency in literacy and numeracy would be displaced and would not have the higher-level skills for the jobs that remain. The usual shift of workers between jobs and skills would break down.

Of course, if this happened, we would need to improve education. The results of the Survey of Adult Skills show what might be possible. For adults with tertiary education, 21% are above the computer level in literacy and 23% are above the computer level in numeracy. And in the highest performing countries, these percentages for adults with tertiary education reach 37% in literacy and 36% in numeracy, for Japan and Sweden, respectively. These results are much better than the current OECD average of 11%.

With high-quality tertiary education, many more adults could develop literacy and numeracy skills above the current computer level. However, there would still be a serious problem if literacy and numeracy were the only work skills even with high-quality tertiary education for everyone. We do not have examples of education policies at scale that bring 80% or even 50% of adults above the current computer level.

Fortunately, literacy and numeracy are not the only work skills. There are many more skills that are important for work than the ones measured by PIAAC. Many jobs involve tasks using expert knowledge like scientific reasoning. Many jobs involve physical tasks like cooking. Many jobs involve social tasks like conversation.

PIAAC does not measure the other skills needed for such tasks and cannot tell us how AI might perform on them. However, computer scientists are developing AI to reproduce these other skills as well. Do AI’s capabilities in these other skills look as proficient as their capabilities in literacy and numeracy? We do not know.

The new study using PIAAC to assess AI in literacy and numeracy is only a first step. The OECD is working with the U.S. National Academies to develop a new programme to assess AI capabilities across all work skills. In the years ahead, policymakers will need this information to know whether AI will shift jobs and skills just like other technologies have done in the past—or whether this time is different.

Links
Computers and the Future of Skill Demand
Skills Matter: Further Results from the Survey of Adult Skills
Survey of Adult Skills (PIAAC)

Follow the conversation on Twitter: #AI and #GoingDigital

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Career education that works

by Anthony Mann
Director of Policy and Research, Education and Employers Taskforce

The benefits of employers engaging with education has long been reported and promoted within policy circles. The UK’s Department for Education, for example, has recently produced guidance for schools stating the need for student learning from the world of work within careers provision. Internationally, the Organisation for Economic Cooperation and Development (OECD) has reported the benefits associated with employer involvement in education. (See, for example: Learning for Jobs).

Despite international interest surrounding the topic, research has failed to keep pace with policy instincts that career education will benefit young people going into the labour market. In a new article, published in the peer-reviewed, international Journal of Education and Work, Elnaz Kashefpakdel and Chris Percy offer new insights into the relationship between career talks with outside people experienced whilst in school and later earnings. They draw upon the limited work that already exists in the area - particularly that of Mann and Percy (2014), which surveyed 1,000 young adults aged 19-24 recalling their school days and found a significant wage premium linked to the degree of exposure young people had with school-mediated employer engagement activities.

This new work analyses data from the British Cohort Study (BCS70), which tracks 17,000 individuals throughout their lives. It provides a rich and reliable set of measurements including socio-economic factors which could potentially affect income, i.e. parental social class, academic ability, home learning environment and demographics. Through statistical analysis, it is possible to take account of such factors in assessing the impact of specific interventions in determining economic outcomes.

The BCS survey offers an interesting data set for analysis related to career interventions due to the timing of its questioning in 1986, when respondents were teenagers. During the 1980s in the UK, government was rolling out the Technical and Vocational Education Initiative (TVEI). The Initiative aimed to help prepare young people for entry into the labour market and served to drive greater activity within schools. The nature of the Initiative often meant that young people were obliged to attend career talks and related sessions, though these activities varied considerably across schools and local authorities.

Data was collected during 1986 regarding young people’s opinions of any careers talks they encountered and was compared to their earnings aged 26, using statistical analysis techniques. Results revealed that, on average, for each career talk with someone from outside of the school experienced at age 14-15 young people benefited from a 0.8% wage premium when they were 26. These findings are statistically significant at 5%, meaning that there is a 95% certainty this correlation did not occur by chance. This relationship was not found for those aged 15-16, which implies that career talks had a greater value for the younger cohort.

Analysis also found a statistically significant relationship between student perceptions of the career talks that they experienced and later earnings. Students who found career talks to be ‘very helpful’ at age 14-15 were compared with those who found careers talks ‘not at all helpful/not very helpful’. Findings demonstrated that for students aged 14-15 who found career talks ‘very helpful’ witnessed a 1.6% increase in earnings per career talk they attended. This also proved significant for young people aged 15-16; with a smaller affect size, they benefited from a 0.9% earnings boost.

These findings provide a clear relationship between the number of career talks attended, and their helpfulness, and relative earnings at age 26. This provides a solid evidence-base for increasing the volume and quality of career talks with outside speakers in education.  Findings revealed that the impact of careers talks were more pronounced for the younger age group, 14-15, than they were for the elder group, 15-16. The authors argue that at the older age group young people may be more focused on examinations, while the younger group may have been more likely to be receptive to career talks due to the year group being more of an explorative period. Thus, perhaps the most desirable age group to deliver career talks to is 14-15 year-olds.

The authors hypothesis that it is difficult to gain new knowledge and skills, known as human capital, through such short duration episodes of engagement with the labour market. However, they could gain access to new, useful and trusted information and networks while interacting with professionals in an episodic manner. It is in this realm of social and cultural capital accumulation that enables young people to gain resources of meaning from the activities, such as career talks. Additionally, the findings are in line with the argument that through the repeated encounters with people from outside schools, young people are able to find helpful information about pathways to their career ambitions.

To read more about the study, visit the website of the Education and Employers Research.
Photo Credit: Careers bulb word cloud, business concept @Shutterstock