The Responsible Use of AI Directive requires risk management and bias mitigation before deployment. Most product owners don't know how to test for that. We do.
Already have a use case to stress-test? Talk about a 2-day sprint →
You have an AI idea. AI scribes for clinicians. Benefit adjudication algorithms. Automated policy summarization. It would save time. It would improve service. And it might violate the Responsible Use of AI Directive if you deploy it without stress-testing the risks first.
The Directive doesn't just require "transparency" and "accountability" as buzzwords. It requires documented evidence that you've tested for bias, identified hallucination vectors, established human-in-the-loop controls, and produced a completed Algorithm Impact Assessment.
We run that stress test. In 2 days. Before you build.
Does the model treat all demographic groups fairly? Where's the proxy discrimination risk?
What personal information is processed? Is consent valid? Is retention compliant?
Can the system explain its decisions to affected individuals? Is that explanation meaningful?
Where can the AI produce plausible but false outputs? What's the blast radius if it does?
What outputs must be retained? What decision logs are required? Who owns the audit trail?
Where do humans intervene? Is override possible? Is the control point actually enforceable?
We don't write policy documents. We produce operational artifacts that your Digital lead and Privacy lead can jointly sign off on and hand to Internal Audit or the IPC.
Purpose, users, data inputs/outputs, decision impact. The 'what' and the 'who' in plain language. No jargon. Validated by the product owner and the business lead.
Every identified risk (bias, privacy, explainability, hallucination, records) with severity rating, likelihood, and the specific mitigation control. Not generic — tied to this use case.
The narrative document required by the Directive. Ontario-aligned. Cross-references the Risk Register. Shows you've done the work before deployment, not after a breach.
The specific conditions under which this use case can proceed to pilot, scale, or production. Quantified. Measurable. Agreed upfront.
If you proceed: success metrics, monitoring approach, what data to log, escalation triggers. The roadmap from prototype to safe deployment.