Who Is Responsible When the Algorithm Decides?

Me with Objects

12-15 years

55 min

Learning goal :

Learning to differentiate a human being from an "intelligent" machine

Pedagogical Intention :

Identify moral differences

Target skills :

Develop a rigorous, multi-stakeholder understanding of AI moral agency and the responsibility gap. Translate abstract ethics into concrete positions on governance and oversight.

Materials :

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

Detailed Procedure :

1. 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. 2. Each group presents their case (5 min). 3. 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. 5. 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?'

Progress Indicators

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.

Research Foundations

Floridi, L. (2016): On Human Dignity as a Foundation for the Right to Privacy. / Danaher, J. (2016): Robots, Law and the Retribution Gap. / EU AI Act (2024): high-risk AI systems.