Generative AI to augment rather than destroy jobs
Generative artificial intelligence (AI) is more likely to augment jobs, by automating some tasks rather than taking over a role entirely, a new study from the International Labour Organisation (ILO) has found.
Founded in October 1919 under the League of Nations, the ILO is one of the first and oldest specialised agencies of the United Nations.
The study, “Generative AI and jobs: A global analysis of potential effects on job quantity and quality”, suggests that most jobs and industries are only partly exposed to automation and are more likely to be complemented rather than substituted by the latest wave of generative AI, such as ChatGPT.
Therefore, the ILO says, the greatest impact of this technology is likely to not be job destruction but rather the potential changes to the quality of jobs, notably work intensity and autonomy.
Since Microsoft-backed OpenAI announced the release of ChatGPT as a prototype on 30 November 2022, the chatbot has gone viral.
Among other capabilities, ChatGPT interacts in conversational dialogue form and provides responses that can appear human. The text-based chatbot can also draft prose, poetry or computer code on command.
Tech giants such as Google, Meta, Amazon Web Services, IBM and Oracle have since released their own versions of generative AI models.
The Brainy Insights estimates the generative AI market will grow from $8.65 billion in 2022 and reach $188.62 billion by 2032.
The ILO study took two principal approaches to the analysis of automation of occupations. The first was to use data on job vacancies to understand how demand for specific skills evolves over time.
The second approach was to focus on occupational structures, with the idea of estimating the automation potential of tasks or skills that make up a given job.
Clerical work was found to be the category with the greatest technological exposure, with nearly a quarter of tasks considered highly-exposed and more than half of tasks having medium-level exposure.
In other occupational groups – including managers, professionals and technicians – only a small share of tasks was found to be highly-exposed, while about a quarter had medium exposure levels, says the labour body.
The study, which is global in scope, documents notable differences in the effects on countries at different levels of development, linked to current economic structures and existing technological gaps.
It finds that 5.5% of total employment in high-income countries is potentially exposed to the automating effects of the technology, whereas in low-income countries, the risk of automation concerns only 0.4%.
On the other hand, the potential for augmentation is nearly equal across countries, suggesting that with the right policies in place, this new wave of technological transformation could offer important benefits for developing countries, ILO notes.
The potential effects of generative AI are likely to differ significantly for men and women, the study finds, with more than twice the share of female employment potentially affected by automation.
“This is due to women’s over-representation in clerical work, especially in high- and middle-income countries. Since clerical jobs have traditionally been an important source of female employment as countries develop economically, one result of generative AI could be that certain clerical jobs may never emerge in lower-income countries,” says ILO.
Wait and see
The paper concludes the socio-economic impacts of generative AI will largely depend on how its diffusion is managed.
It argues for the need to design policies that support an orderly, fair and consultative transition. Workers’ voice, skills training and adequate social protection will be key to managing the transition. Otherwise, there is a risk that only a few, well-prepared countries and market participants will benefit from the new technology.
The authors note the “outcomes of the technological transition are not pre-determined. It is humans that are behind the decision to incorporate such technologies and it is humans that need to guide the transition process.”
These findings align with some of the most recent literature on generative AI systems with a global focus.
A recent study by McKinsey (2023) points to a similar group of “knowledge work” occupations and tasks as having the highest level of exposure, though with a significantly higher suggested level of displacement.
The Word Economic Forum’s (WEF’s) global survey, which focused on large enterprises, also lists clerical and administrative jobs among occupations with the fastest expected declines (WEF 2023).
Estimates provided by Goldman Sachs (2023) suggest a slightly higher level of potential automation than ILO’s calculations, but with the general conclusion aligning with the organisation’s main finding that “most jobs and industries are only partially exposed to automation and are thus more likely to be complemented rather than substituted by AI”.