Ethics isn’t just about rules. It’s about doing the right thing, day after day, in the real world. Below, you’ll find a role-play scenario and other activities to help you practice making ethical decisions with AI.

Putting Ethics into Action

A. Role-Playing in Real-Life Situations

Why Do It?

• Role-play helps you think from different viewpoints and understand the impact of AI on various people.
• You’ll act out a scenario, debate solutions, and learn how to handle moral, legal, and social challenges.

Ideas for Role-Playing:

1. AI Developer – You built the AI. Explain how it works and why it might be biased.
2. HR Manager – You use the AI to hire employees but need to address complaints about unfair rejections.
3. Applicant (Victim) – You believe the AI unfairly rejected you because of your background.
4. Ethics and Legal Expert – You analyze if the AI breaks any laws and how to fix the problem ethically.

B. Simulation Exercises

Why Do It?

• By simulating AI-related decisions, you see what happens if ethical guidelines are ignored.
• Mistakes in the simulation will help you learn to be more careful in real life.

Scenario: Bias in an AI-Powered Hiring Tool

• Context: A company called “TechTalent AI” uses an AI tool to handle job applications. It’s found to be unfairly rejecting people from certain groups.
• Your Task: Investigate the problem, debate solutions, and decide on a plan that respects ethics, laws, and the company’s reputation.

Role Play Script Steps:

1. Setting the Stage

   • Multiple applicants complain they were unfairly turned down.
   • A meeting is called with the AI Developer, HR Manager, Applicant, and Ethics Expert.

2. Role-Specific Prompts

   • AI Developer: “The data we used wasn’t diverse enough. How do we fix the model?”
   • HR Manager: “We saved time, but we can’t ignore unfair outcomes. What can we do?”
   • Applicant: “I have strong skills, but I never got an interview. How will you fix this?”
   • Ethics/Legal Expert: “We might be breaking anti-discrimination laws. How can we correct things?”

3. Discussion and Resolution

   • Everyone proposes solutions (e.g., retraining the AI, using more diverse data, adding a human review stage).
   • Talk about the pros and cons of each idea and pick the best plan.

Discussion Topics:

1. Efficiency vs. Ethics: How can companies keep the AI fast without being unfair?
2. Preventing Bias: What steps can prevent bias in AI systems? Who’s responsible if things go wrong?
3. Long-Term Effects: How does biased AI hurt a company’s image and the trust people have in it?

Reflection Activities for Long-Lasting Change

A. Ethics Journals

• What to Do: After every AI-related project, write about any ethical concerns you faced and how you handled them.
• Why It Helps: Keeping track of your thoughts helps you see patterns and learn from your experiences.

B. Community Feedback

• What to Do: Ask classmates or team members for honest feedback on how you handled ethical situations.
• Why It Helps: Hearing different perspectives helps you improve your ethical awareness and decision-making skills.

Key Takeaway:
By practicing ethics in everyday AI scenarios—through role-play, simulations, and self-reflection—you develop strong habits that guide you in doing the right thing. Good ethical decision-making isn’t just about following rules; it’s about making choices that respect people’s rights, build trust, and promote fairness for all.

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