Inclusive and Bias-Aware AI Use

Develop critical awareness of bias in AI tools and build inclusive prompting strategies to ensure AI-generated content is fair, representative, and appropriate for diverse learners.

DigCompEdu-Kompetenzbereich(e)

Evaluation, Lernerorientierung, Förderung der digitalen Kompetenz der Lernenden

Zeit

Vorbereitung: 15 Min.

Umsetzung: 30 Min.

Progressionsniveau der Lehrkräfte

Insider

Zielgruppe

Educators and adult learners Primary: educators, Secondary: learners

Niveau der digitalen Kompetenzen

Mittelstufe

Sprachniveau der Lernenden

B1 - B2

🎓 Lernziele

Educators and learners will be able to:

  • Observe and become aware of inclusion, representation, and potential bias in AI-supported teaching materials.
  • Reflect on how AI outputs can reinforce or challenge stereotypes and inclusion.
  • Make informed professional choices about adapting, contextualising, or rejecting AI-generated materials before classroom use.
  • Apply inclusive prompting strategies to generate more representative AI content.

Zutaten

Ressource Anzahl Zweck
AI image generation tool (e.g. DALL-E, Canva AI) 1 pro Lehrkraft To generate images for bias analysis
ChatGPT or similar LLM 1 pro Lehrkraft To generate text for bias analysis
Bias observation worksheet 1 pro Person Structured reflection tool
Gerät mit Internetzugang 1 pro Person Zugriff auf KI-Tools

Zubehör

  • Computer oder Tablet mit Internetzugang
  • Access to an AI image generator and a text-based AI tool
  • Printed or digital bias observation worksheet

🥣 Vorbereitung – Vor dem Einsatz im Unterricht

  • Select 3-5 example prompts that are likely to reveal bias in AI outputs (e.g. “a doctor”, “a teacher”, “a refugee”).
  • Generate sample AI images and text outputs using these prompts before the session.
  • Prepare the bias observation worksheet with guided questions.
  • Prepare a set of “inclusive prompting” strategies to share with participants.

🔥 Umsetzung (Im Unterricht / Synchron )

  • Introduction (5 min): Explain that AI tools learn from existing data, which may contain historical biases.
  • Observation activity (15 min): Generate AI images or text using the prepared prompts. Participants complete the bias observation worksheet.
  • Discussion (10 min): What patterns did you notice? Who is represented? Who is missing? What assumptions does the AI make?
  • Inclusive prompting (10 min): Introduce strategies for more inclusive prompts (e.g. specifying diversity, avoiding stereotyped roles).
  • Practice (10 min): Participants rewrite one prompt using inclusive strategies and compare the outputs.
  • Reflection (5 min): How will you apply this awareness in your teaching practice?

🧂 Differenzierung & Inklusion

  • For less experienced educators: Focus on image generation bias as it is more immediately visible.
  • For advanced participants: Explore intersectional bias and how multiple identity factors interact in AI outputs.
  • For learner-facing activities: Adapt the observation worksheet to use simpler language

🥄 Evaluation & Feedback

Instrument/Kriterium Ausgezeichnet Gut Verbesserungswürdig
Bias identification Accurately identifies multiple forms of bias in AI outputs Identifies some bias with support Struggles to identify bias in AI-generated content
Inclusive prompting Rewrites prompts effectively to produce more inclusive outputs Makes some improvements to prompts Prompts show limited awareness of inclusive strategies
Critical reflection Demonstrates deep critical awareness of AI limitations and ethical implications Shows some critical awareness Limited reflection on bias and inclusion

⚠️ Ethik, Datenschutz & Schutzmaßnahmen

  • Acknowledge that AI bias is a systemic issue, not a personal failing of individual users.
  • Avoid generating or sharing AI content that could be harmful or offensive to learners.
  • Be transparent with learners about the limitations of AI tools.
  • Encourage ongoing critical evaluation of AI-generated materials before classroom use.
  • Follow institutional policies on AI use in education.

🍱 Erweiterungen / Weiterverfolgung

  • Develop a classroom “AI Bias Checklist” for reviewing AI-generated materials.
  • Explore how bias manifests differently across text, image, and audio AI tools.
  • Connect to broader media literacy: how does bias appear in traditional media vs AI?

🔗 Fächerübergreifender Bezug

📚 Weiterführende Literatur & Ressourcen