Bridging AI and Society 🌞🤖

📍 Now live: Banz 2025 — Course Website »

We design and deliver interdisciplinary courses and workshops that explore the technical foundations and societal implications of Artificial Intelligence (AI) and Machine Learning (ML). Our modular teaching formats are accessible, discussion-driven, and adaptable — from summer schools to university seminars.

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🧠 What We Offer

We support institutions and educators in bringing machine learning and AI into interdisciplinary classrooms. Our work includes:

  • 🧩 Tailored course design, adapted to audience, duration, and goals
  • 🐍 Hands-on projects using Python and interactive Colab notebooks
  • 💬 Discussion-based teaching formats for mixed-discipline groups
  • 🌍 Societal deep-dives on real-world AI issues — from healthcare to regulation
  • 📚 Open educational resources that can be reused or remixed

Whether for a one-day workshop or a 10-day summer academy, our materials and formats scale flexibly to suit different settings.

🧭 Our Teaching Philosophy

Our approach is built on three pillars:

1. Accessible Machine Learning

We teach the what, how, and why of ML systems — using clear examples and visual explanations, not technical jargon. Core concepts include:

  • Classification, regression, trees, and neural networks
  • How ML differs from traditional programming
  • Key challenges like generalization and interpretability

2. Exploration by Doing

Participants use real datasets and train real models. Through interactive notebooks, they:

  • Visualize decision boundaries
  • Tweak hyperparameters
  • See how learning algorithms work in practice

Our intro to Python workshop supports absolute beginners, with no coding experience required.

3. Societal Context

From bias in algorithms to the EU AI Act, we link ML methods to their real-world consequences. Topics include:

  • ⚖️ Fairness and discrimination in automated systems
  • 🏥 AI in public health and diagnostics
  • 📣 Automation, misinformation, and the future of work
  • 🧭 Legal frameworks and global regulation

Participants contribute their own disciplinary lens — we provide the structure for dialogue.

💾 Explore Our GitHub Repositories

All of our teaching materials are open-source and classroom-tested:

🔗 github.com/BridgingAISocietySummerSchools

Each repository includes setup instructions, example projects, and modular content blocks.

🌍 Where We’ve Taught

This program has been delivered in summer academies organized by the Studienstiftung des Deutschen Volkes, Germany’s national academic scholarship foundation. Past iterations include:

  • 🇬🇧 2019 — St. John’s College, Cambridge (UK), including students from St. John’s
  • 🇩🇪 2021 — Koppelsberg, Germany
  • 🇸🇮 2024 — Ljubljana, Slovenia
  • 🇩🇪 2025 — Banz Castle, Germany, with students from the College of Europe

Each event brings together students from across disciplines — from philosophy, law, and economics to physics, biology, and computer science.

We continue to refine and adapt our program based on evolving challenges in AI and feedback from learners.

💡 Curious about what the course looks like in practice? Visit our latest iteration: Banz 2025 Course Website »