Key take-aways

Challenges of using GenAI for simulations

Limited outputs

In the early days of GenAI, a common challenge was the AI’s reluctance to generate hypothetical news stories or political statements. When prompted to create such content, these AI models would often push back, reminding the user that the requested information was not based on actual events. This limitation made it challenging to leverage GenAI for simulations, thought experiments, or creative writing exercises that relied on fabricated scenarios. However, as GenAI has evolved, developers have found ways to work around this issue. One effective approach is to explicitly define the nature of the project upfront, framing it as a simulation. By providing this context in the project header or introduction, users can help the AI understand that the subsequent prompts will involve hypothetical situations.

Conflict-avoiding bias

The AI setting is designed to avoid conflicts and lead to compromise, often favouring cooperative resolutions even in intense conflict situations. This meant that GenAI tended to avoid escalatory statements and instead steered interactions toward collaboration. As a result, careful prompt management and some output editing were necessary to ensure that the messages and information maintained an appropriate tone for the simulation’s context.

Limited image production

The AI tools used (ChatGTP, Copilot) could not produce highly realistic images. This limitation led to using existing media photos instead of AI-generated visuals to illustrate news stories. This could partly be due to my limited skills in image creation or the significant time required to achieve the desired outcome. Specialised AI tools likely focused on generating visuals would be more effective. However, creating realistic images remains an area of ongoing development.

Some recommendations for implementation

Enhance prompt writing

The most essential element is solid prompt writing. The AI tool should be provided with detailed background knowledge to assist the teacher in the simulation. Share your scenario objectives, define the tonality, planned outcome, the genre of the text, and the perspective on whose behalf the text is composed to ensure the most accurate and relevant outcome.

Regular reviewing

AI-generated outputs should be regularly reviewed and adjusted. The ChatGPT canvas function enables optimal improvement because it allows you to add your own text to the existing output or request adjustments to specific sections. This flexibility makes it easier to fine-tune the output according to your needs. Overall, it is essential to avoid quickly copying and pasting AI-generated content and instead critically assess the output to maintain the desired pedagogical focus.

Integration of various sources

If the AI does not have other input, the outcomes tend to follow similar templates. To adjust the style, genre, and authenticity of the output, it is essential to integrate different sources. For example, providing press releases from a government’s communication as examples can guide the AI in producing the desired style. Similarly, news stories of actual events can be referenced to contextualise and adapt existing events for a new purpose. These inputs help create outputs that are more nuanced and tailored to the specific needs of the simulation.

Ethical considerations

When using generative AI tools to support simulation-based assignments—such as those involving fictional news stories or fabricated crisis events—it is essential to incorporate ethical safeguards. AI tools may mistakenly treat fictional prompts as actual events or reject requests if they appear to conflict with its content guidelines. To prevent this, instructors should clearly frame the simulation as a fictional and educational exercise. The most straightforward and effective way to do this is to structure the simulation as a “project” within the AI tool, where the project description explicitly states that the scenario is hypothetical and the news items are entirely fictional. This clarification should be provided at the beginning of the interaction to ensure the AI understands the context and does not attempt to verify or discredit the scenario. Proper contextualisation ensures ethical use of the tool, minimises misunderstandings, and enables the AI to generate relevant, appropriately framed content to support learning outcomes.

Some example prompts:

1. Prompt in the case the existing news article: Please write an article based on this news story [insert the link of the news article], emphasise more/adjust the story according to the scenario [indicate the focus of your simulation]:

2. Prompt to adjust the tone or provide a perspective: Please write another news story about it from the perspective of [indicate the actor]

3. Prompt to creat a news article of a fictional event: Write a news article about [indicate the event relevant for your scenario and add all relevant details]. Use the style of [indicate the news agency whose style you intend to use]