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Is AI federally regulated?

Region: Ontario Answer # 8001

In Canada today, “AI” is not regulated under a single act or statute. Instead, it is governed by several different laws already in existence, such as privacy law, and intellectual property (“IP”) law. However, this likely will change soon as legislation is emerging that will govern the legal implications, rights and responsibilities of using AI.

For instance, initiatives like Bill C-27, now known as the Artificial Intelligence and Data Act (AIDA), will be Canada’s first attempt to implement comprehensive AI legislation, likely coming into effect in 2025. The AIDA aims to establish a national framework for the design, development, and utilization of AI. Part of Bill C-27 includes a voluntary AI Code of Conduct, which is meant to act as a guide that will result in responsible development and use of generative AI.

Key elements of the Code include:

Accountability: The suggestion that organizations should have plans in place to handle risks based on how large their AI projects are. Organizations are also encouraged to learn from each other regarding what works best and check their publicly used AI systems thoroughly, sometimes even by outside groups.

Safety: Before AI is let out into the world, organizations are encouraged to check for any possible problems and have plans ready to remedy them. This helps ensure that AI which is released is safe to use.

Fairness and Equity: AI creators are encouraged to carefully choose and check the data they use to teach their AI systems to ensure that the systems do not possess any unfair biases. They are encouraged to test the AI in different ways to make sure it’s fair to everyone.

Transparency: AI developers are encouraged to be open and explicit with regards to what their AI can do and how they have trained it, so that people are aware when content has been made by AI and what the AI can do.

Human Oversight and Monitoring: Even after AI starts working, or is released into the public, organizations should monitor how it is functioning, record any issues that arise, and have ways to fix any problems that come up.

Validity and Robustness: It is important for AI to work well and be secure. Organizations should regularly test their AI against a set of quality assurance standards to ensure it remains safe and reliable.







								

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