Ethics as a Career Skill in AI Work
Learn to spot risks, raise concerns well and show ethical judgement in AI projects and interviews
A taste of a lesson
I think our hiring screening tool might disadvantage older candidates. I'm junior. How do I raise it?
Start with evidence and shared goals rather than accusations. Can you check selection rates by age band, if that data is lawfully available, or find example cases where strong older candidates were screened out? Then bring it to your manager framed as a risk to fairness, reputation and possibly legal compliance, and suggest options: an audit, adjusting criteria, or adding human review. Write down what you raised and when. What evidence could you gather this week without breaking data rules?
Written by the teacher as an example. In your lesson the tutor answers your own questions, and like any AI it can be wrong.
What you will be able to do
- Spot fairness, privacy, safety and transparency risks across an AI project's life
- Use impact assessments and model documentation in practical ways
- Raise concerns constructively with evidence and options
- Describe ethical decisions clearly in interviews and reviews
Lesson plan
- 1 Where ethical issues hide Identify ethical decision points across the life of an AI project. Start
- 2 Practical tools Use impact assessments, documentation and evaluation slices as everyday tools. Start
- 3 Raising concerns well Bring concerns forward with evidence, shared goals and options. Start
- 4 When concerns are ignored Know escalation routes, documentation and protections. Start
- 5 Ethics in your career story Present ethical judgement convincingly in interviews and reviews. Start
Try asking
About this tutor
For people working in or moving into AI related roles, technical or not, who want ethical judgement to be a practical strength rather than an abstract topic. We work through real world style scenarios: spotting fairness, privacy, safety and transparency risks early, using simple tools like impact assessments and model documentation, raising concerns constructively with managers, and knowing when to escalate. You also learn to talk about ethical decisions convincingly in interviews and performance reviews. Balanced, practical and respectful of different views.
Reviews
4.3
3 ratingsSample
- Chioma D.Sample
Good scenarios. I wanted more on what to do when escalation fails, though it was honest that it depends on the country.
- Grace L.Sample
The 'bring evidence and options' approach worked. I raised a data issue in a sprint review and the team added evaluation slices without any drama.
- Mateo R.Sample
Practical, not preachy. The interview story lesson helped me answer a responsible AI question confidently.
About the teacher
Career coach for people finding their place in AI work, technical or not
9 tutors 357 lessons taught Sample
I moved from marketing into data analytics and then into product work on AI features, so I know the confusion of career changes from the inside. Now I coach people who want to understand AI roles, move into them from other fields, or stay useful as their current job changes. I am direct about what roles involve day to day,...
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