Amid growing concerns about the rise of rogue AI agents, there is a heightened call for governmental regulations on increasingly powerful AI systems. However, some experts argue that achieving global cooperation and keeping pace with the rapid advancements in AI pose significant challenges.
While figures like U.S. President Donald Trump believe that major tech companies can self-regulate effectively, voices such as Microsoft co-founder Bill Gates and AI pioneer Geoffrey Hinton advocate for external safeguards beyond self-regulation. Jaxson Khan, an AI policy and adoption expert at the University of Toronto’s Munk School of Global Affairs, points out that most industries are subject to government oversight, making it logical for AI to follow suit.
The rapid evolution and improvement of AI models, as highlighted in a recent Anthropic report showing a doubling of agent capabilities every four months, present a major hurdle in regulatory efforts. This velocity of change makes it challenging for governments to keep up, according to Manon Paquet from McGill’s Centre for Media, Technology and Democracy.
Efforts to establish global oversight through a non-industry body, as proposed by figures like Prime Minister Mark Carney and AI pioneers Geoffrey Hinton and Yoshua Bengio, aim to address the risks associated with advanced AI systems. While international cooperation on AI governance may face obstacles, creating a global organization could set guidelines for safe AI development and enhance international collaboration.
In Canada, the absence of federal AI regulations is being addressed through proposed legislation like Bill C-34, the Safe Social Media Act, which sets standards for AI chatbots to mitigate the risk of generating harmful content. The government’s initiative to establish a national council on artificial intelligence, led by Carney, seeks to guide AI strategy and enhance safety measures.
Despite the challenges posed by the global nature of AI companies, Canada can still enforce policies requiring incident reporting and accountability from AI platforms operating within its borders. Establishing mechanisms for incident recording and reporting incidents can foster transparency, educate citizens, and demonstrate leadership in AI governance.