Learn what the Machine is not

Let's imagine that your everyday job tasks are considered routine and repetitive, putting them at high risk of technology-driven displacement in a few years. What is the solution?

As skill sets become more exposed to Artificial Intelligence (AI), the risk of automation and replacement of repetitive tasks increases for various occupations. The level of exposure depends on the occupation and the economic sector where the skills and jobs are performed. For instance, skill sets in information processing industries have a higher exposure to AI developments compared to industries such as manufacturing, agriculture, and mining (Eloundou et al., 2023). In addition, As the OECD indicates, the AI workforce is low but rapidly growing, with the proportion of workers with AI skills in OECD countries increasing significantly from 0.07% in 2011 to 0.34% in 2019. (OECD, 2023) To address this evolving landscape, the following learning and policy approach is presented:

Learning Services Providers Have the Key: Optimistic approaches to skills development for new and yet-to-exist jobs, rely on training where humans have a comparative advantage over tasks that AI can execute. However, this advantage varies among economic sectors. It is now the duty of learning services providers to identify this comparative advantage and create learning content related to skills preparation to maintain a relevant curriculum. Skills related to the comparative advantage, such as critical thinking and problem-solving, should be the focus, with specific efforts tailored to the exposure level and the industry to enhance the quality of content.

Policy-Making Insights: From a lifelong learning approach, there are two specific policy streams to attend: the empowerment of users over their learning paths and the protection of occupations that are highly exposed to automation.

It is vital to enhance the transparency and ease readability of data gathered by governments and think-tanks about the labour market trends per industry, as well as occupations and activities changes. The availability of readable information about transforming job activities and required skill sets empowers users on their learning path. Indeed, this allows them to better target their chosen industry and enhance their capacity related to skill set exposure to AI over time.

Finally, considering that the skill sets in some industries' occupations are highly exposed, job protection is needed through regulation with displacement anticipation and transition planning to avoid the high impact of routine-biased technological change.

ACTUA contributes to the improvement of learning and opens the discussion about new trends in education and labour market among stakeholders to generate impactful decision-making. Do not hesitate to contact ACTUA for professional services!

By: Juliana Lopez

#AI #Futureskills #Learning

References:

• Green, A. and L. Lamby (2023), "The supply, demand and characteristics of the AI workforce across OECD countries", OECD Social, Employment and Migration Working Papers, No. 287, OECD Publishing, Paris, https://doi.org/10.1787/bb17314a-en

• Eloundou, Tyna & Manning, Sam & Mishkin, Pamela & Rock, Daniel. (2023). GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models. https://www.researchgate.net/publication/369369163_GPTs_are_GPTs_An_Early_Look_at_the_Labor_Market_Impact_Potential_of_Large_Language_Models