LEARNING GOAL
Learning to differentiate a human being from an "intelligent" machine
PEDAGOGICAL INTENTION
Identify moral differences
Target SKILLS
MATERIALS
DETAILED PROCEDURE
PROGRESS INDICATORS
Three real case studies (simplified): (1) AI hiring tool discriminating by gender
(2) AI sentencing algorithm with racial bias
(3) autonomous weapon system misidentifying a civilian
Three groups each receive one case study. Task: identify (a) what decision the AI made, (b) who was harmed, (c) who should be held responsible - the developer, the organization deploying it, the user, or the AI itself.
Step 1
Each group presents their case (5 min).
Step 2
Class question: 'Can an AI be morally responsible? What conditions must be met for moral responsibility - intention, understanding, the capacity for regret, legal personhood?' 4. Introduce the concept of 'responsibility gap': when AI causes harm, human accountability tends to diffuse.
Step 3
Individual written position: 'What legal and ethical framework do you think should govern AI decision-making in high-stakes domains? What role should human oversight play?'.
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Step 10
Student produces a written position that (a) correctly identifies where moral responsibility lies in at least two cases, (b) defines the 'responsibility gap,' and (c) proposes a specific accountability mechanism.