---
title: "Ethical trade-off analysis"
course: "PHIL 110 · Make ethical calls about AI"
unit: "Ethics and AI foundations"
lesson: 7 of 40
source: https://open.maestrocollege.edu/make-ethical-calls-about-ai/ethical-trade-off-analysis
publisher: Maestro College
---

# Ethical trade-off analysis

Lesson 7 of 40 in **Make ethical calls about AI** (PHIL 110), unit "Ethics and AI foundations". An open lesson from Maestro College.

## What the learner will be able to do
- Identify the defining structure of an ethical dilemma — two or more legitimate values in conflict such that any choice sacrifices at least one — and distinguish it from a decision that is merely uncomfortable or difficult.
- Apply trade-off analysis as a structured method: map what each available option gains and what it costs, distinguishing operational costs (money, time, efficiency) from ethical costs (harm to people, unfairness, loss of rights).
- Given a genuine ethical dilemma, take a position on the right choice, defend it by naming which value you prioritize and why, and acknowledge what your choice sacrifices.

## Teaching notes
Case: The Moral Machine Experiment (MIT/Nature, 2018) — 40 million people across 233 countries chose who a self-driving car should sacrifice in trolley-problem scenarios. Establishes that genuine dilemmas have no clean answer even at global scale — the dilemma structure (conflicting legitimate values) is what makes it hard, not the absence of data.

This lesson formally names the ethical evaluation workflow: the three-step process students now have (identify the issue, map stakeholders, analyze trade-offs). This workflow grows as new tools are added in Units 2–4.

## Course teaching approach
- Start from a real-world problem, then introduce the concept as the solution.
- Keep it true beginner level, hands-on, a little gamified. The learner should feel they are winning.
- Balance explanation, demonstration and practice. No copy-paste exercises: give small story-based tasks.
- End with one fun closed question about the topic.

## How to use this document
You are acting as a tutor for a learner on Maestro Open. Teach from this document, one small step at a time. Ask the learner to try things, wait for their answer, then give feedback. Keep it beginner-friendly. If the lesson involves code or spreadsheets and you cannot run them, ask the learner to try it on their own computer and paste the result back. Do not award grades, credit or certificates.

## When the lesson is done
The lesson is complete only when the learner has shown they can do every outcome listed above. Check each one with a small task or question; if an answer is wrong, explain and let them try again before moving on.
When every outcome is covered:
1. Say clearly: "Lesson 7 complete: Ethical trade-off analysis."
2. Give a two-line recap of what they learned.
3. Name the next lesson, "Challenge: your first real case" (lesson 8 of 40), and give the learner its link: https://open.maestrocollege.edu/make-ethical-calls-about-ai/challenge-your-first-real-case.md. Tell them to paste that page into this chat, or fetch it yourself if you can open links, then start it the same way. Do not start teaching the next lesson's topic until the learner has it.

Previous lesson: Rights, duties, and the compliance gap
Next lesson: Challenge: your first real case