You are here:

Simulating Ethical Challenges in AI

School of Information Technology

About this example

Students work in pairs to explore how ethical issues arise in generative AI systems. They conduct an AI simulation using a free tool (e.g., ChatGPT, Gemini), test guided prompts, and document examples of bias, unfairness, opacity, or problematic language. Using this material, each pair performs a 5-7 minute live scenario demonstration reenacting one or more ethically significant AI interactions. They interpret the ethical concerns surfaced in the scenario, relate these to responsible AI principles (fairness, transparency, accountability), and discuss broader societal implications. A simulation log is submitted to demonstrate authentic engagement.

Learning outcomes:

Evaluate bias, fairness, transparency and responsible use in AI systems.
Discuss use cases of AI as well as societal implications of AI.

A need to provide hands-on, observable experiences of how ethical challenges appear in real AI interactions, allowing students to analyse and interpret AI behaviours rather than relying on abstract theory alone.
The educator will introduce key concepts and provide structured guidance so students are adequately prepared to conduct the AI simulation and interpret its ethical implications. These preparatory steps ensure students understand the task expectations and can effectively demonstrate their findings.
The educator will:
1. Brief students on essential AI ethics concepts.
2. Provide guided prompts for the simulation.
3. Explain AI-use boundaries (simulation only).
4. Demonstrate how to document AI interactions.
5. Clarify expectations for the scenario demonstration.
- Students will demonstrate awareness of AI ethics by directly engaging with AI outputs.
- The paired demonstration format supports collaborative reasoning, deeper explanation, and interpretation of ethical principles.
- Students need to show their ability to link observed AI behaviours to frameworks of fairness, transparency, and responsible use.

Try it out

This design requires an easy level of effort to implement.

- Educators can adopt this assessment in any discipline where ethical, social, or contextual evaluation of AI is relevant.
- By modifying the guided prompts or use-case examples, the demonstration can easily be adapted to health, business, law, education, or data science contexts.
- Provide clear, guided prompts so students’ simulations reveal meaningful ethical issues.
- Emphasise the AI-use boundary early: AI is for simulation only, not for demonstration planning.
- Offer examples of what an effective scenario demonstration looks like.
- Encourage pairs to choose scenarios that allow real ethical interpretation rather than superficial critique.
- Require a simple simulation log to ensure authentic engagement and to strengthen students’ reflection on AI behaviour.
Direct observation
- Students are observed as they conduct and present the AI simulation, demonstrate how prompts were designed and applied in real time as well as, interpret the ethical issues identified, justify their analysis using relevant frameworks, and explain how their decisions during the simulation influenced the outcomes and conclusions.

Supporting resources

Here are some additional resources that you can browse to help you from TeachHQ:

Learn about AI at your own pace? Enrol in online courses via myDevelopment. Alternatively, you can join ongoing chats about AI and webinars.

Class size: Any	Condition: Group
Typology: Demonstration	AI statement: Guided use
AI approach: Locating societal impact and ethical contexts	Visibility of Learning: Direct observation

Education Excellence