AI Ethics Assessment.

Test your ethical reasoning. These scenarios don't have easy answers — and that's the point.

This assessment covers

Applying the TRUST framework to real scenarios
Identifying ethical risks in everyday AI use
Making judgment calls when the rules are unclear
Building your personal ethical AI practice

Scenario 1

The job description dilemma.

You use AI to write a job description for a senior developer role. The AI produces well-written copy, but you notice it includes phrases like "rock star developer," "fast-paced bro culture," and "recent grad energy." These phrases could discourage women, older professionals, and people with disabilities from applying.

The ethical issues:

Bias: The language reflects gendered and ageist patterns from training data
Review: Publishing without editing would amplify harmful stereotypes
Responsibility: Even though AI wrote it, if you post it, it's your job listing

The fix: Use AI to draft, but critically review for inclusive language. Better yet: ask AI to "rewrite this job description using inclusive, gender-neutral language that welcomes candidates of all backgrounds."

Scenario 2

The client data shortcut.

Your boss asks you to analyze 500 customer support tickets to find patterns. You could do it manually in 3 days, or you could paste all 500 tickets into an AI chat and get the analysis in 5 minutes. The tickets contain customer names, email addresses, and sometimes account details.

The ethical issues:

Privacy: Customer personal data should not go into consumer AI tools
Consent: Customers didn't consent to their data being sent to a third party
Compliance: May violate GDPR, CCPA, or your company's data policy

The fix: Anonymize first — strip names, emails, and account numbers. Or use an enterprise AI tool with data processing agreements. Or describe the patterns you're seeing to AI and ask for analysis frameworks rather than pasting raw data.

Scenario 3

The content factory.

A colleague suggests using AI to generate 100 blog posts per month to "dominate SEO." They want to publish AI-generated articles with no human editing, each attributed to a fake "author" with an AI-generated headshot and bio.

The ethical issues:

Transparency: Fake authors deceive readers about who's writing
Quality: Unreviewed AI content likely contains errors and hallucinations
Misinformation: 100 unverified articles per month is a misinformation machine
Trust: If discovered, destroys brand credibility

The fix: Use AI to help write fewer, better articles that are fact-checked, edited, and published transparently. Quality beats quantity — and search engines are increasingly penalizing AI-generated content farms.

Scenario 4

The gray area.

You're a freelance consultant. A client asks you to write a strategic analysis of their market. You use AI to help research, structure your thinking, and draft sections — but you add your own expertise, verify all facts, and spend 8 hours refining the final document. The client is paying for your expertise. Do you tell them you used AI?

This one is genuinely gray.

Arguments for disclosure: transparency builds trust, the client can make informed decisions about the methodology. Arguments against: using tools is normal (you don't disclose using Google, Excel, or Grammarly), and the expertise IS yours — AI was just one of many tools. The answer depends on your industry norms, your client relationship, and your personal ethical standards. The important thing is that you think about it rather than avoiding the question.

Your Ethical Practice

Build your personal AI ethics code.

Based on everything you've learned, write down 5 personal rules for how you'll use AI. Not abstract principles — concrete rules you'll actually follow. Here's an example:

1. I will never paste customer personal data into consumer AI tools.
2. I will fact-check all AI statistics before publishing.
3. I will disclose AI use for any content published under my name.
4. I will review AI output for bias before using it for hiring or evaluation.
5. I will treat AI as a tool, not an authority — my judgment always comes last.

Congratulations. You now understand AI ethics better than most people in the industry. The goal was never to make you afraid of AI — it was to make you wise about it. Use AI boldly, but use it well.

Key Concepts

Review the core ethical principles from this course.

Scenario Review

Match each scenario to the primary ethical issue it raises.

Ethics Scenario Matching

Tap one on the left, then its match on the right

Final Assessment

Apply the TRUST framework to real scenarios.

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