Critical AI Literacy for Historians

Developing critical engagement with AI technologies in historical research practice.

This educational repository provides structured, hands-on exercises for historians to develop critical AI literacy, digital source criticism, and scholarly practice with large language models (LLMs). It aims to help learners understand how AI functions as both a research tool and a method, reflect on how it shapes historical interpretation and evidence, and apply rigorous digital source criticism to assess data provenance, representation, and bias.

Purpose

The materials promote responsible, transparent, and ethically informed use of AI in historical research—emphasizing:

• 📊 Reproducibility in research workflows
• 🔒 Privacy and ethical data handling
• ©️ Copyright awareness and proper attribution
• 🌱 Sustainability through minimal computing approaches
• 🤝 Interdisciplinary collaboration and critical reflection

By fostering interdisciplinary collaboration and critical reflection on AI as both an analytical instrument and a historical artefact, the repository encourages historians to design transparent, meaningful projects that integrate AI into their research without compromising disciplinary rigor.

Features

Multilingual Content

The exercises are available in three languages:

• 🇬🇧 English - Full curriculum with detailed exercises
• 🇩🇪 Deutsch - Vollständiger Lehrplan mit detaillierten Übungen
• 🇫🇷 Français - Programme complet avec exercices détaillés

Structured Exercises

Each exercise follows a consistent pedagogical framework:

• Clear learning objectives - What you will learn
• Difficulty levels - Beginner, Intermediate, Advanced
• Time estimates - Plan your learning journey
• Prerequisites - Know what you need to get started
• Hands-on activities - Practice critical engagement with AI
• Critical reflection prompts - Deepen your understanding
• Additional resources - Expand your knowledge

FAIR and CARE Principles

This project adheres to:

• FAIR principles (Findable, Accessible, Interoperable, Reusable) for educational materials
• CARE principles (Collective Benefit, Authority to Control, Responsibility, Ethics) for responsible data governance

Getting Started

Explore the Exercises

Visit the live website to explore exercises in your preferred language:

• 🌐 View the Website
• 🇬🇧 English Exercises
• 🇩🇪 Deutsche Übungen
• 🇫🇷 Exercices en français

For Contributors: Setup with GitHub Codespaces

1. Fork this repository to your GitHub account.

2. Click the green <> Code button at the top right of your forked repository.

3. Select the "Codespaces" tab and click "Create codespace on main". GitHub will build a container that includes:

   • ✅ Node.js (via npm)
   • ✅ Quarto

4. Once the Codespace is ready, open a terminal and preview the documentation:

   quarto preview

Note: All dependencies (Node.js, Quarto) are pre-installed in the Codespace.

👩‍💻 Advanced Local Installation

Prerequisites

• Node.js
• Quarto

Local Setup Steps

# 1. Install Node.js dependencies
npm install
npm run prepare

# 2. Preview documentation
quarto preview

For Educators and Contributors

Adding New Exercises

We welcome contributions of new exercises! Please use our exercise proposal template to suggest new exercises.

Development Workflow

Check that all files are properly formatted:

npm run check

Format all files with Prettier:

npm run format

Preview the documentation while editing:

quarto preview

Commit your changes using conventional commits:

npm run commit

Support

This project is maintained by @maehr. Please understand that we can't provide individual support via email. We also believe that help is much more valuable when it's shared publicly, so more people can benefit from it.

Type	Platforms
🚨 Bug Reports	GitHub Issue Tracker
💡 New Exercise Proposals	Exercise Proposal Template
📚 Docs Issue	GitHub Issue Tracker
🎁 Feature Requests	GitHub Issue Tracker
🛡 Report a security vulnerability	See SECURITY.md
💬 General Questions	GitHub Discussions

Roadmap

• Expand exercises to cover advanced AI topics for historians
• Add interactive elements and quizzes
• Build a community of practice for AI-literate historians

Contributing

We welcome contributions from historians, educators, digital humanists, and anyone interested in critical AI literacy! Please see CONTRIBUTING.md for details on our code of conduct and the process for submitting pull requests.

Authors and Credits

• Moritz Mähr - Project lead and initial development - maehr

See also the list of contributors who participated in this project.

License

• Educational content and exercises: Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) - You are free to share and adapt the materials for non-commercial purposes with appropriate credit and under the same license
• Code and technical infrastructure: GNU Affero General Public License v3.0 (AGPL-3.0) - Any modifications must be made available under the same license

Citation

If you use these materials in your teaching or research, please cite:

@misc{maehr2024critical,
  author = {Mähr, Moritz},
  title = {Critical AI Literacy for Historians},
  year = {2024},
  publisher = {GitHub},
  url = {https://github.com/maehr/critical-ai-literacy-for-historians}
}