My responses to the first theme of the Canada AI Survey, focusing on research and talent development.
This is part 1 of “Responses to the Canada AI Survey” - a series containing my responses to the eight themes of the Canadian government’s public consultation on artificial intelligence.
Theme 1: Research and Talent
Q1: How does Canada retain and grow its AI research edge? What are the promising areas that Canada should lean in on, where it can lead the world?
It’s crucial to recognize that our current AI moment is based solely on the scaled implementation of Generative Pretrained Transformers (GPT). The technology itself is nearly 10 years old. GPTs are an extension of a series of machine learning techniques introduced through the 1980s, 1990s, and 2010s.
These methods would not have looked promising to many people at the time. They also would have had to compete with other research avenues that, though abandoned now, may have held promise at the time. For this reason, it may not be possible to identify today’s promising areas.
Canada can maintain its research edge by exploring the non-promising and non-obvious at the research stage while looking far ahead to changing capabilities that could break current assumptions about technical feasibility (such as massively scaling highly parallelized computation in the case of GPTs). For example, symbolic AI approaches offer an alternate paradigm to approaches based solely on machine learning and neural nets and could be complementary if combined or scaled in a yet to be discovered way.
Canada will not grow its research edge by competing with private industry to scale GPTs. GPTs have flaws and inherent performance limitations that are intrinsic to their structure and training. They are not the path to artificial general intelligence. Canada therefore needs to explore many other avenues to find those which may offer a stepwise increase in capabilities.
Q2: How can Canada strengthen coordination across academia, industry, government and defence to accelerate impactful AI research?
Canada should double down on the programs that are working well, tweak the ones that are not working as well as they should - all while removing as much bureaucracy as possible from them. In particular, post-doctoral researchers are highly trained, creative individuals and usually underpaid for the amount of long term value they can create. While this position was often a stepping stone to further a career in academia, industrial post-doctoral fellowships should be seen as an entryway into a lucrative technical leadership career in any sector.
Q3: What conditions are needed to ensure Canadian AI research remains globally competitive and ethically grounded?
Core ethical principles are core to our society and evolve slowly, even as technology changes rapidly. We need to equip existing oversight bodies instead of creating new ones. Due to the speed of progress, we should centralize thought leadership and debate for the most impactful areas of concern.
The slow pace of legislation may negatively impact both global competitiveness by creating uncertainty, while failing to protect people with real consequences for bad actors. For this reason, legislation should be proactive while being non-specific. It should not seek to ban or restrict specific technologies but instead focus on outcomes.
Research ethics have existed for a long time and institutions have dedicated offices and staff for their oversight. We need to make it easy for these offices to adapt to a changing landscape while cutting through the noise. I don’t think new entities are needed. I believe it would be worth centralizing thought leadership on the topic, in a Canadian cultural and legal context, for that purpose.
Q4: What efforts are needed to attract, develop and retain top AI talent across research, industry and the public sector?
Canada should continue to position itself as an attractive place for AI talent, and particularly for AI talent working at Canadian companies and institutions. The fluid situation in the United States with respect to international students and H1B visas is an opportunity to further cement Canada’s reputation as a welcoming place for this talent. Canada could see a boost in reputation that outlives these restrictions south of the border.
The academia-to-industry pathway may be one of the best opportunities to retain top talent. It should be better developed with increasing industrial partnerships and remuneration. A culture of exploration should be encouraged, where post-docs can cross disciplines at this juncture instead of only being offered to double-down on their areas of expertise. I would even go so far as renaming the industrial post-doctoral fellowship to differentiate it from the academic track and capturing the fact that we are developing the innovation leaders of tomorrow.