The Ethics Landscape

More Than Thought Experiments

When people hear “AI ethics,” they often think of sci-fi scenarios. Killer robots. Superintelligent takeovers.

Those conversations exist. But they’re not what this course is about.

This course is about the ethical questions you face right now, using AI tools that already exist:

• Should I disclose that AI helped write this?
• Is it okay to use AI for this decision?
• What happens to the data I share with these tools?
• Is this AI output fair and accurate?
• Am I using this responsibly?

These aren’t hypothetical. They’re everyday.

What to Expect

This course is broken into focused, practical lessons. Each one builds on the last, with hands-on exercises and quizzes to lock in what you learn. You can work through the whole course in one sitting or tackle a lesson a day.

What You’ll Learn

By the end of this course, you’ll be able to:

• Identify common AI biases and understand their real-world impacts
• Create informed decisions about privacy and data when using AI tools
• Apply transparency principles when AI assists your work
• Recognize when AI should and shouldn’t be used for specific decisions
• Evaluate AI outputs critically instead of accepting them blindly
• Develop a personal framework for responsible AI use

What’s Actually at Stake

Scale amplification: AI works fast and at scale. That’s its value. But it also means mistakes, biases, and harms happen fast and at scale.

A human makes a biased hiring decision: one person affected. An AI screening system has the same bias: thousands affected.

Hidden decision-making: AI often works behind the scenes. Loan approvals. Content recommendations. Resume filtering. Decisions that affect people without them knowing AI was involved.

Trust erosion: When AI generates misinformation, fakes content, or makes unfair decisions, it erodes trust—in AI itself, and in institutions that use it.

Real harms to real people: Not abstract. Real people denied jobs because of biased algorithms. Real students flagged as cheaters by faulty systems. Real communities affected by AI-driven decisions.

The Everyday Ethics Moments

You probably face ethical AI choices more often than you realize:

When you use AI to write:

• Is this fair to present as my work?
• Should I disclose AI assistance?
• Am I spreading AI hallucinations?

When you use AI to decide:

• Should AI have influence over this choice?
• Am I accounting for possible bias?
• What if AI is wrong here?

When you use AI with data:

• What am I sharing with this system?
• Who else might see this?
• Am I violating anyone’s privacy?

When you use AI to create:

• Is this original or plagiarized?
• Does this perpetuate harmful stereotypes?
• Am I considering who this might affect?

Why This Matters to You

“I’m just using ChatGPT for emails. This doesn’t apply to me.”

Actually, it does. Consider:

You influence others: What you create with AI reaches other people. If it’s biased, misleading, or harmful, that impact spreads.

You normalize behaviors: How you use AI contributes to broader norms. Responsible use encourages others. Careless use does the opposite.

You have choices: AI isn’t inevitable. How you use it—or whether you use it for certain things—is a choice you make.

You can do better: Understanding ethics isn’t about being perfect. It’s about being thoughtful. That’s achievable.

The Framework We’ll Build

By the end of this course, you’ll have practical guidance for:

Bias: How to recognize it and what to do when you find it

Privacy: How to protect yourself and others

Transparency: When and how to disclose AI use

Limits: What AI shouldn’t do, and why human judgment matters

Evaluation: How to critically assess AI outputs

Practice: Daily habits for responsible AI use

Ground Rules for This Course

This isn’t about perfection. No one uses AI perfectly ethically. The goal is awareness and improvement, not sainthood.

There aren’t always right answers. Many ethical questions involve trade-offs. We’ll explore the considerations, but you’ll need to make your own judgments.

Context matters. What’s appropriate varies by situation. An approach that works in one context might not in another.

Ethics evolve. The ethical landscape of AI is changing rapidly. What we consider appropriate today may shift. Stay curious.

Exercise: Map Your AI Use

Before we dive into specific issues, take stock of how you use AI:

1. List the AI tools you regularly use
2. For each, note: What do you use it for? What data do you share?
3. Identify: Where do you feel uncertain about whether your use is appropriate?
4. Consider: Have you ever felt uncomfortable about how you or others used AI?

Keep your answers in mind. We’ll address these situations throughout the course.

Key Takeaways

• AI ethics isn’t sci-fi—it’s everyday decisions about how we use AI now
• AI amplifies impact: good decisions scale, but so do bad ones
• You face ethical AI choices constantly: writing, deciding, creating, sharing data
• Understanding ethics means being thoughtful, not perfect
• This course builds practical frameworks for real situations

Next: Understanding where AI bias comes from and how to recognize it.

Up next: In the next lesson, we’ll dive into Understanding AI Bias.