Artificial intelligence (AI), robotics and other forms of 'smart automation' are advancing at a rapid pace and have the potential to bring great benefits to the economy, by boosting productivity and creating new and better products and services. For advanced economies like the US, the EU and Japan, these technologies could also produce a lot of disruption, not least to the jobs market. To explore this further we have analysed a dataset compiled by the OECD that looks in detail at the tasks involved in the jobs of over 200,000 workers across 29 countries (27 from the OECD plus Singapore and Rus
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Artificial intelligence (AI), robotics and other forms of 'smart automation' are advancing at a rapid pace and have the potential to bring great benefits to the economy, by boosting productivity and creating new and better products and services. For advanced economies like the US, the EU and Japan, these technologies could also produce a lot of disruption, not least to the jobs market. To explore this further we have analysed a dataset compiled by the OECD that looks in detail at the tasks involved in the jobs of over 200,000 workers across 29 countries (27 from the OECD plus Singapore and Russia). Building on previous research by Frey and Osborne (Oxford University, 2013) [available in VOCEDplus at TD/TNC 123.687] and Arntz, Gregory and Zierahn (OECD, 2016) [available in VOCEDplus at TD/TNC 124.386], we estimated the proportion of existing jobs that might be of high risk of automation by the 2030s for: each of these 29 countries; different industry sectors; occupations within industries; and workers of different genders, ages and education levels.
We also identify how this process might unfold over the period to the 2030s in three overlapping waves: (1) algorithm wave: focused on automation of simple computational tasks and analysis of structured data in areas like finance, information and communications - this is already well underway; (2) augmentation wave: focused on automation of repeatable tasks such as filling in forms, communicating and exchanging information through dynamic technological support, and statistical analysis of unstructured data in semi-controlled environments such as aerial drones and robots in warehouses - this is also underway, but is likely to come to full maturity in the 2020s; and (3) autonomy wave: focused on automation of physical labour and manual dexterity, and problem solving in dynamic real-world situations that require responsive actions, such as in manufacturing and transport (e.g. driverless vehicles) - these technologies are under development already, but may only come to full maturity on an economy-wide scale in the 2030s.
Edited excerpts from publication.
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