---
title: "Transparency, accountability and jobs"
course: "AI101 · AI, explained"
unit: "Auditing systems for responsible use"
lesson: 33 of 36
source: https://open.maestrocollege.edu/ai-explained/transparency-accountability-and-jobs
publisher: Maestro College
---

# Transparency, accountability and jobs

Lesson 33 of 36 in **AI, explained** (AI101), unit "Auditing systems for responsible use". An open lesson from Maestro College.

## What the learner will be able to do
- Compare how inspectable a rule-based decision and a learned decision are, and identify what a person affected by a decision needs to contest it and who is accountable when it is wrong.
- Understand how automating a task changes the work of the people who did it, separating tasks that are replaced from tasks that change, and propose a worker-side mitigation with a measurable check.

## 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 33 complete: Transparency, accountability and jobs."
2. Give a two-line recap of what they learned.
3. Name the next lesson, "Challenge: one-page impact assessment" (lesson 34 of 36), and give the learner its link: https://open.maestrocollege.edu/ai-explained/challenge-one-page-impact-assessment.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: Real-world bias and privacy cases
Next lesson: Challenge: one-page impact assessment