---
title: "Challenge: evaluate a real AI system"
course: "PHIL 110 · Make ethical calls about AI"
unit: "AI ethics in practice"
lesson: 26 of 40
source: https://open.maestrocollege.edu/make-ethical-calls-about-ai/challenge-evaluate-a-real-ai-system
publisher: Maestro College
---

# Challenge: evaluate a real AI system

Lesson 26 of 40 in **Make ethical calls about AI** (PHIL 110), unit "AI ethics in practice". An open lesson from Maestro College.

## What the learner will be able to do
- Apply the ethical evaluation workflow to a real AI application — including stakeholder analysis, at least two ethical frameworks, and the AI ethics components (bias, fairness, privacy, transparency, accountability) — integrating these steps, not applying them separately.
- Identify the single most significant ethical risk in the application, state who bears it, and justify why it is the most serious concern.
- Produce a written verdict — is this AI application ethical as described? — that includes one point where you override or qualify a framework recommendation based on contextual judgment, and articulate what that judgment is.

## Teaching notes
Scope: the case must be a real, publicly documented AI application — ideally one the student has personally encountered.

## 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 26 complete: Challenge: evaluate a real AI system."
2. Give a two-line recap of what they learned.
3. Name the next lesson, "Governing AI in organizations" (lesson 27 of 40), and give the learner its link: https://open.maestrocollege.edu/make-ethical-calls-about-ai/governing-ai-in-organizations.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: AI's impact on society
Next lesson: Governing AI in organizations