6 work scenarios. Nothing is graded: pick an answer to see why it holds up or not.
Your answers are kept on this device only.
Scenario 1 of 6
Every morning an AI system prepares a list of 40 employees "at risk of resigning" with suggested actions. The supervisor usually approves the whole list in two minutes. What is the main problem?
Scenario 2 of 6
Three months ago you turned down a partnership proposal after AI summarised its risks. Now the partner asks why. What kind of record should you have made at the time?
Scenario 3 of 6
A cooperative automatically rejects members' loan applications when an AI score is below a threshold, with no officer checking. A rejected member wants to challenge the decision. Under Article 10(1) of the PDP Law, what is their right?
Scenario 4 of 6
Your team is designing an objection path for AI-assisted performance reviews. A team member proposes: "If someone objects, re-run the model on the same data and send the result." Why is this proposal weak?
Scenario 5 of 6
Your company plans to use AI to give every applicant a fit score and automatically filter out low scores, starting next month. In the meeting, what should you ask first?
Scenario 6 of 6
An HR officer has finished Foundations. They want to use AI to prepare interview material and tidy the weekly leave recap, and have never built an app. What is the most sensible next step?
