What you’ll learn
- Choose appropriate AI tasks
- Design human review and stop rules
- Test an automation before activation
Who this course is for
Recruiters and operations leaders evaluating technology
Before you start
No purchase or account is required. Use fictional information in exercises. Read the explanation, study the worked example, try the exercise before revealing the response, then revisit the idea in the course knowledge check. Practical assignments take longer than reading alone.
Course assignment
Assemble the lesson exercises into a practical plan. Identify assumptions, evidence still needed, an accountable owner, and a review date. Explain one decision you changed and why.
Evaluate an AI-assisted recruiting pilot
A fictional team proposes AI interview summaries and an automated outreach flow. Sample summaries omit scheduling constraints. The sequence keeps sending after an interview booking. The vendor calls its scoring objective.
- Classify the tasks by impact and data requirements.
- Create a fictional prompt with factuality checks.
- Write vendor, accessibility and human-review questions.
- Test stop conditions and define correction, monitoring and shutdown criteria.
Review a model recommendation
The recommendation separates low-risk drafting from real selection, protects information, investigates omissions and blocks a sequence that ignores changed status.
Self-review rubric
- Evidence: distinguish confirmed facts, fictional assumptions and unresolved questions.
- Application: connect the proposed actions to the actual person, role and operating conditions.
- Accountability: identify owners, dependencies, stop conditions and review dates.
- Judgment: explain the trade-offs and why an alternative was rejected.
This is learning feedback, not a hiring assessment or credential.
Return and retrieve
After a few days, explain the main decision without reopening the worked response. Then compare your reasoning and revise one weak part of your plan.
Knowledge check
After the lessons, test your decisions on three scenarios. Feedback explains the reasoning; results are practice feedback, not certification.
Take the knowledge checkConnect this course to the complete process
Work through the connected case, practice the conversations and add this course’s work to your final project.
Sources & further reading
- NIST: AI Risk Management Framework ↗
- EEOC: Employment Tests and Selection Procedures ↗
- U.S. Department of Justice: AI and Disability Discrimination in Hiring ↗
Instruction, cases, exercises and worked responses are original academy material. External references support concepts; they do not endorse the academy.