Generative AI and Jobs:

 

Generative AI and Jobs: A global analysis of potential effects on job quantity and quality

The recent study published by ILO assesses the potential global exposure of occupations to Generative AI, particularly GPT-4. It predicts that the overwhelming effect of the technology will be to augment occupations, rather than to automate them. The greatest impact is likely to be in high and upper-middle income countries due to a higher share of employment in clerical occupations. As clerical jobs are an important source of female employment, the effects are highly gendered. Insights from this study underline the need for proactive policies that focus on job quality, ensure fair transitions, and that are based on dialogue and adequate regulation.

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. WEF’s global survey, focussed on large enterprises, also lists clerical and administrative jobs among occupations with fastest expected declines (WEF 2023). Estimates provided by Goldman Sachs (2023) suggest a slightly higher level of potential automation than our calculations, but with the general conclusion aligning with our 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”.

The more moderate effects observed in our estimations stem from several factors. First, we rely on ISCO-08 as the source of tasks and occupations, which is more adequate for a study with a global character than the US-oriented O*NET database. Second, the application of ILO’s country-level employment statistics adds important nuance to the actual number of jobs that exists in those categories, bringing out income-based differences that affect the final employment effects at the global level. Third, we do not attempt to make predictions on the evolution of the technology. While the growing capabilities of generative AI and the range of secondary applications that can be built on top of this technology are likely to increase the numbers of jobs in both the augmentation and automation categories identified in our paper, our analysis suggests that the general contours of transformation identified in this study will remain valid for the coming years.

Ultimately, we argue that in the realm of work, generative AI is neither inherently good nor bad, and that its socioeconomic impacts will largely depend on how its diffusion is managed. The questions of power balance, voice of the workers affected by labour market adjustments, respect for existing norms and rights, and adequate use of national social protection and skills training systems will be crucial elements for managing AI’s deployment in the workplace. Without proper policies in place, there is a risk that only some of the well-positioned countries and market participants will be able to harness the benefits of the transition, while the costs to affected workers could be brutal. Therefore, for policy makers, our study should not read as a calming voice, but rather as a call for harnessing policy to address the technological changes that are upon us.

(With courtesy to  ILO)  It was accessed from: https://www.ilo.org/static/english/intserv/working-papers/wp096/index.html