Statistics Canada Study on AI Occupational Exposure

Recent research from Statistics Canada has produced experimental estimates regarding the potential occupational exposure to artificial intelligence (AI) among Canadian workers. The study, titled "Experimental Estimates of Potential Artificial Intelligence Occupational Exposure in Canada," categorizes workers based on their job tasks and the degree of exposure to AI technologies.

The study identifies three classifications of workers:

• High Exposure and High Complementarity: Jobs that are highly exposed to AI and where tasks may benefit from AI capabilities.
• High Exposure and Low Complementarity: Jobs that are highly exposed to AI but where tasks may be replaced by AI.
• Low Exposure: Jobs that are not significantly affected by AI.

According to the findings from May 2021, 29% of Canadian workers were in jobs that were highly exposed to and complementary with AI. Additionally, 31% were in jobs that were highly exposed but had low complementarity with AI, while 40% were in jobs not highly exposed to AI. The distribution of AI occupational exposure was similar to that observed in May 2016.

The study also indicates that AI may have a more transformative impact on highly educated workers compared to those with lower levels of education. For example, 50% of workers with a bachelor's degree or higher were found to be in jobs that are highly exposed to and complementary with AI, compared to only 13% of workers with a high school diploma or less. Furthermore, 36% of highly educated workers held jobs that were highly exposed to AI and whose tasks might be replaced by AI, compared to 25% of less educated workers.

It is important to note that these estimates are based on a limited range of AI applications and their interaction with human abilities. The study cautions that as technology evolves, the applicability of these findings may change, and higher occupational exposure does not necessarily correlate with an increased risk of job loss due to various factors such as financial and institutional considerations.