“Human in the loop” gets used as a reassurance more often than a specification. The Canadian sources that actually use the phrase are more precise than the slogan, and worth reading directly.
Key takeaways
The Federal Court’s Notice to the Parties and the Profession on AI, dated May 7, 2024, names “Human in the loop” as one of three governing principles for materials filed with the court, alongside Caution and Neutrality. The Alberta Court of Appeal, Court of King’s Bench and Alberta Court of Justice, in their joint tri-court notice on large language models dated October 6, 2023, use the identical heading for the same underlying concern, in the same setting — court submissions.
The Federal Court’s wording is specific: “The Court urges verification of any AI-created content.” Alberta’s three courts go further on what “verified” has to mean: “any AI-generated submissions must be verified with meaningful human control. Verification can be achieved through cross-referencing with reliable legal databases.” Both instruments name the same underlying failure they exist to prevent — see where AI agents still fail for what that failure looks like when it isn’t caught.
It is also worth naming the contrast plainly: Alberta’s notice urges caution and verification but does not require disclosure of AI use, where the Federal Court’s notice requires a formal Declaration in the document itself. “Human in the loop” as a principle and a disclosure requirement are two separate things, and not every Canadian court that has adopted one has adopted the other.
The same court applies the phrase to its own internal use of AI, in a separate, later document — its Interim Principles and Guidelines on the Court’s Use of Artificial Intelligence, dated September 29, 2025: “The Court will ensure that members of the Court and their law clerks are aware of the need to verify the results of any AI-generated outputs that they may be inclined to use in their work.” The same document states plainly that “the Court will not use AI, and more specifically automated decision-making tools, in making its judgments and orders, without first engaging in public consultations.” Two documents, two different audiences — one aimed at the profession, one at the institution itself — converging on the same requirement. Quebec goes further than any of the above: it gives an individual a personal, statutory right to a human check on an automated decision made about them. A business that renders a decision based exclusively on automated processing of personal information must tell the person that was how it was decided, and “the person concerned must be given the opportunity to submit observations to a member of the personnel of the enterprise who is in a position to review the decision.” Act respecting the protection of personal information in the private sector, s.12.1 That hands the reviewed person a right to trigger the check, rather than only binding an institution’s own conduct.
The Treasury Board’s Directive on Automated Decision-Making — binding on federal departments, not private businesses, though any vendor selling automated decision tools into government has to meet it — sets a more specific standard than the courts’ wording. Section 6.2, Transparency, requires “providing notice through all service delivery channels in use that the decision will be made or assisted by an automated decision system” before the decision, and “providing a meaningful explanation to clients of how and why the decision was made” after it. That’s a stronger commitment than a generic assurance that a person is involved somewhere — it specifies notice timing and the content of what has to be explained afterward.
The same directive ties the level of required review to how much is at stake, rather than applying one blanket standard to every automated decision. Its Appendix B sets four Impact Assessment Levels, keyed to how reversible the decision is and how long its impacts last, weighed against things like rights, equality, dignity, privacy and economic interests, and section 6.1 requires completing an algorithmic impact assessment and publishing it “prior to the production of any automated decision system.” The underlying logic generalizes well beyond government: a higher-stakes decision earns a higher bar for review before the system goes anywhere near it, decided in advance rather than worked out after something has already gone wrong.
None of the sources above solves the practical problem of telling genuine review from a rubber stamp, and there is no Canadian figure that quantifies where that line sits — the honest answer is structural, not numerical. Genuine review requires three things together: the reviewer has enough time to actually check the specific item, enough information to know what “correct” looks like for it, and the actual authority to change or block the outcome rather than only note a concern after the fact. Remove any one of the three and the label “human in the loop” still applies technically, while the check it’s meant to provide has stopped happening.
Say a reviewer is handed a drafted refund message alongside the original complaint and the account history, with the ability to approve, edit or reject before anything is sent — time, information and authority, all three present. Now say the same reviewer is instead handed a queue of two hundred drafted messages with no supporting context, expected to click approve quickly to keep up with the volume. Both setups can be described, accurately, as “human in the loop.” Only one of them is actually providing the check the phrase implies.
Related: for how this checkpoint fits into a longer automated process, see what orchestration means in AI; for why the checkpoint matters more once a system can act, not just answer, see why AI agents need guardrails.
Not as one named law. Several specific Canadian sources build the same underlying expectation in their own context — the Federal Court and Alberta courts’ own notices, the federal Treasury Board directive for government systems, and the OPC’s own generative-AI principles, which separately call for an “effective challenge mechanism” letting an affected person “request human review” of a significant automated decision (see the OPC’s principles). None of these is a single blanket statute.
No — it means a person can meaningfully review and intervene before an output is relied on, not that a person has to be the one running the tool step by step.
A fully automated decision with no review point at all. The Treasury Board directive is written specifically to govern that situation for federal automated decision systems — requiring notice and explanation precisely because no person is reviewing the individual decision before it’s made.
Genuine oversight is a design decision, made before a process goes live.
