Artificial intelligence in a post-pandemic world of work and skills

With its unique ability to identify and ‘learn’ from data patterns and to develop predictive mappings between variables – machine and deep learning – artificial intelligence (AI) has proved to be an indispensable tool in the fight against the coronavirus pandemic. AI has enabled the deployment of predictive models of potential disease contagion and containment, and has been used for screening and tracking patients. In addition to health care purposes,

AI has been deployed across the globe to improve understanding of the potential consequences of the viral infection for different economy sectors. Companies have increasingly relied on machine-learning-enabled systems to reengineer production delivery in the face of a massive disruption in supply chains. Policy-makers have also turned to AI technologies due to their great promise in strengthening the quality of remote education delivery, at times where schools and education systems struggle to remain accessible to learners.

Is coronavirus reinforcing automation?

Not long before the coronavirus outbreak, fears about AI and smart machines resulting in a jobless society were widespread, noted Cedefop expert Konstantinos Pouliakas in the recent symposium ‘AI in the world of work’, under the auspices of the German EU Presidency. While a 2013 University of Oxford study cautioned that about half of all jobs in advanced economies may become extinct due to advancing machine learning methods, subsequent studies deconstructing jobs by task composition tended to dispel such fears of extensive job loss. An analysis using data from the first Cedefop European skills and jobs survey  showed that the share of EU jobs facing very high risk of being automated by new digital technologies is close to 14%, although about two in five EU jobs still face a high probability of substantial transformation.

The coronavirus crisis has given new rise to concerns about automation in labour markets, with social distancing measures driving companies and societies to adopt new digital and data-driven technologies. Early predictions that Covid-19 will have a positive automation effect may, however, be overstated. Firms’ automation incentives may be partially offset by the lower aggregate demand in economies following the pandemic disruption, while higher uncertainty and credit constraints hold back their investment decisions. Occupations identified as ‘high-risk’ due to coronavirus exposure and social distancing have also been found to correlate weakly with those facing higher automation risk. Many of the occupations and sectors mostly affected by Covid-19 are typically in the service sector (hospitality, leisure, retail) and are heavily reliant on interpersonal skills, which are less susceptible to replacement by AI technologies.

From technical to economic feasibility

A recently published Cedefop report found that such earlier studies only focus on the technical feasibility of some job tasks being replaced by machine learning algorithms. They fail to acknowledge that firms’ decisions to automate depend on a combination of factors including the ‘business case’ for adopting new technologies, their cost, diffusion hurdles, the relative supply and price of skill and labour, uncertainty in investment decisions and shifting social attitudes.

The Cedefop report shows that, when accounting for such factors, firms that were early adopters of new technologies were more likely to experience future employment gains. The average employment decline in the group of occupations deemed to be ‘fully automatable’ by earlier studies has only been -2%, which is rather feeble, given that we are already a quarter to one half into the timeframe in which massive job losses were predicted.

Strengthening AI in vocational education and training

These findings highlight that AI technologies may help the transition to better-quality jobs and increase demand for skills insulated from automation, such as creativity, leadership, organisational and interpersonal communication skills. Interaction with digital devices is also a key trait of occupations with lower automation risk, all the more significant in the coronavirus era given the growing need for workers to carry out their jobs remotely.

Although not without obstacles, the transition from analogue to digital vocational education and training (VET) systems is progressing steadily in EU Member States, as revealed by a new series of Cedefop thematic insights focused on VET for the future of work. Even before the coronavirus shock, several EU countries had started investing in the development of online and open learning tools and environments. As the need for distance learning increased, more have also been looking into AI technologies as a means of improving personalised learning solutions and open education resources, which can be tailored and adapted to students’ learning abilities. AI tools can also monitor learning difficulties, identify early warning signs of possible student failure, and carry out remote assessment.

The Cedefop thematic insights reports identified several key response areas addressed by EU Member States in their efforts to adapt their VET systems to AI and automation, specifically by:

• planning for AI: adopting specific AI strategies and revising IVET and CVET strategies, developing multi-stakeholder expert groups and public-private partnerships to map AI capabilities;
• developing AI-based learning solutions for classrooms and enterprises: innovation labs and other pilot AI projects for knowledge exchange between companies and different stakeholders;
• learning (about) AI: teaching teachers and the public about AI capabilities via user-friendly online courses;
• applying AI: using AI methods for the development of new skills classifications or analysis of training curricula and VET programmes based on their match/mismatch to labour market needs;
• adapting VET systems to AI: considering the introduction of new or revised education and training curricula and programmes (such as robotics, computational thinking, machine learning, data science, cybersecurity, automation engineering);
• coping with AI: developing continuing VET programmes to support workers affected by automation and structural labour market changes.

As part of its Digitalisation, AI and the future of work project, Cedefop will continue carrying out research and collecting comparative information on the adoption of AI and new digital technologies in EU job markets and VET systems in the post-coronavirus world. Stay tuned for the 2nd wave of the Cedefop European skills and jobs survey, which will focus on the impact of changing digital technologies and automation on the skill requirements, skill mismatches and continuing education and training of EU adult workers.

Check out examples of AI reaction areas in EU Member States (+UK).