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Module 6 of 8

Ethics, Bias, and Responsible AI

One 3-hour session · a short lecture, then a long hands-on lab

Overview

AI systems inherit the biases of their training data, raise hard questions about privacy and copyright, and carry real environmental costs. This session examines those issues honestly, then runs live bias experiments and works through ethical case studies so you can form and defend your own positions.

The sharpest failures in this space are not rogue robots; they are ordinary systems that reduce a person to a score and then act on it. Automated hiring is the classic case, and playing through Survival of the Best Fit (a free ten-minute browser game about exactly that) makes the mechanism impossible to unsee.

Learning objectives

  • Explain where bias in AI systems comes from and demonstrate it with prompts.
  • Describe the privacy, copyright, and environmental issues generative AI raises.
  • Analyze an ethical case study and defend a position on it.
  • Apply a personal checklist for responsible AI use in school and work.

Session agenda

Materials

  • Bias experiment worksheet and case-study packet (provided with the module).
  • Survival of the Best Fit. Free, ten minutes, runs in a browser.
  • Any AI assistant account from earlier modules.

Homework

Write a one-page discussion of one ethical case study: the issue, the stakeholders, your position, and what evidence would change your mind. Say plainly what would change it.

Detailed slides, lab worksheets, and demos for this module are in progress and will be posted here as they are written.