This module turns checkpoint recognition into a hands-on compliance review. It applies an SME-authored compliance checklist to healthcare artificial intelligence (AI) project materials in Microsoft 365, documenting findings with correct escalation routing. The checklist carries the interpretive work; the skill here is applying it consistently, documenting clearly, and routing correctly.

This module builds the vocabulary and recognition foundation for Responsible AI principles before handoff packets are evaluated against them. It covers six principles, fairness, reliability, transparency, privacy, security, and accountability, with healthcare implementation examples for each.

This module covers hands-on evaluation of a technical team's healthcare artificial intelligence (AI) handoff packet. It applies an SME-authored Responsible AI checklist across all six principles; identifies missing evidence, apparent risks, and unsupported recommendations; documents findings with correct category and severity; and escalates to senior reviewers with correct routing.

Build the vocabulary and recognition foundation for healthcare ethics concepts before analyzing case study scenarios against them. Describe the five ethics concepts—patient autonomy, beneficence, nonmaleficence, justice, and consent boundaries—with healthcare AI workflow examples for each.

Turn concept recognition into hands-on case study analysis. Analyze a Contoso case study to identify ethical concerns across three concern categories (patient impact, explainability, appropriate human decision-making roles), propose CB1-scope actions to address them, and escalate concerns to senior leads with correct routing.

Bring together supporting compliance review in Microsoft 365, reviewing Responsible AI outputs handed off from technical teams, and analyzing healthcare ethics in AI projects—to conduct a complete Responsible AI Review for the Contoso initiative in support of an upcoming governance decision. You'll produce a five-section review deliverable that gives the governance committee (compliance, Responsible AI, ethics, and clinical leadership) an integrated view of the initiative's compliance status, Responsible AI evidence, and ethics considerations, with correct escalation routing across all three lenses. The work stays observational throughout—you evaluate against checklists and frameworks, document findings with named evidence, and route to correct destinations; you do not make compliance/RAI/ethics judgments, provide final approvals, or override governance decisions.