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From Pivot Magazine

Artificial intelligence: an opportunity or cause for concern?

David-Alexandre Brassard, CPA Canada’s chief economist, on the range of AI’s true influence and the challenges surrounding its regulation

Artificial intelligence (AI) has taken centre stage, and all of the accompanying spotlight that comes with it. In 2023 alone, AI has seen a quadrupling of Google searches and triggered significant stock market enthusiasm and investment. Is AI at the peak of the hype cycle or could it be the driving factor behind the fifth Industrial Revolution disrupting the way we live and work? The potential is evident, but so are the concerns.

Contextually, job market disruptions are nothing new: 60 per cent of jobs in 2018 did not exist in 1940. Will the disruption be faster this time around? I argue that the short-term impacts should be greater: displacing workers from old roles is quicker than re-employing them in new ones. This will also be widespread. Goldman Sachs estimated that AI could do one-fourth of current work-related tasks.

AI stands out because it brings the disruptions to a new crowd. Automation introduced machines and automated processes into factory work, either modifying blue-collar jobs or displacing them. AI, on the other hand, introduces algorithms into white-collar or office work. Whether white-collar workers will be displaced or their role changed is still unknown, but AI is prone to take over low-risk information interpretation and decision-making.

Canada is well positioned on the research and development (R&D) side with several of the largest AI tech hubs within its borders (Mila in Montreal, Vector Institute in Toronto, and Amii in Edmonton). We might very well win the R&D race, but the million-dollar question is whether Canada will be able to implement or transfer that R&D to the private sector. We have had that challenge with prior innovation. Regardless, if it could help with our well-known struggles with productivity growth, now stale for the last eight years, it would be welcome. Canada has historically done better transferring productivity gains to worker compensation, thus reducing risks of rising inequalities: two-thirds of productivity gains have transferred to compensation in Canada compared to 45 per cent in the United States since 1980.

Additionally, the aging population has led to labour constraints being the most cited factors limiting sales or production growth for independent businesses. In terms of addressing labour shortage, the impact of AI should be systemic rather than direct. Industries with high exposure to AI (professional services, finance, information and culture, etc.) currently have lower vacancy rates, in other words, less severe labour shortages. Hence, AI could free up workers from these industries, who would need to join more labour-constrained industries. This might imply job or career transitions, but the displaced workers being white-collar tends to lend itself better to reskilling.

I have no fear that we will have plenty of job needs. Health care and construction, to name two, could benefit greatly from additional labour supply, to address end-of-life care needs of baby boomers and housing supply needs.

The trials and tribulations of regulating AI

The challenge is figuring out how to regulate AI: what do we regulate, who does it and how much regulation is really needed? AI pioneers, researchers and legislators are split on the call. Too much regulation can stifle innovation, but too little could lead to major consequences. A letter from AI experts demanding a pause on the development of high-impact frontier AI projects impacted regulators but has not resonated throughout the industry, with AI development still running at full steam.

Canada’s government has essentially “plugged” AI into a privacy bill under study (Bill C27). It leads to many, including CPA Canada, to wonder if the legislation received adequate study and consideration given the probable impact of AI on all facets of society. Until legislation catches up, the government has created a voluntary code of conduct (Responsible Development and Management of Advanced Generative AI Systems) to bridge the gap. It is discretionary and not all companies are on board, once again indicating the split of the industry.

It proves particularly complex with tech companies having bigger market capitalization than many countries’ GDP, and AI models spreading across frontiers. With the need for regulation to span internationally, 28 countries signed the Bletchley Declaration, calling for international co-operation at the United Kingdom’s global AI Safety Summit. Canada’s role, as a smaller open economy, has yet to be determined. CEO of Shopify Tobias Lütke had an interesting take on X (formerly Twitter): “We don’t need more referees in Canada. We need more builders. Let other countries regulate while we take the more courageous path and say, ‘Come build here.’” This contrasts with Canada’s overall strong and heavy legal and regulatory frameworks.

In the United States, a country that has historically been relatively hands-off in regulating its massive tech sector, the recent introduction of the Executive Order on Safe, Secure, and Trustworthy Artificial Intelligence signals a significantly new direction.

The wheels are in motion across the globe to tackle the question of regulation. But the picture of how things will look in 12 months and 12 years is unclear, and it’s not yet a singular and coordinated (or consistent) effort. And if we favour a less regulated approach, the question becomes: Can we trust large tech companies to self-regulate?


View CPA Canada’s extensive tech resources and learn more about ChatGPT. Plus, check out our RPA certificate and advanced data management certificate.

Photo caption: Health care and construction could benefit greatly from additional labour supply to address end-of-life care needs of baby boomers and housing supply needs (Getty Images)