This is a collection of constantly growing and developing resources. Be sure to check back regularly for new resources.
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How can we mitigate bias in AI design?
This lesson introduces students to the concept of bias in AI training data and its societal implications. Using a real-world example of Google’s Gemini AI, students will explore how overrepresentation and underrepresentation in datasets affect various groups.
- Created by Chelsea Dixon
- Adapted by Chris Mah
What is the global significance of foundation models?
This lesson introduces students to the concept of foundation models, focusing on their role in AI development and the countries at the forefront of their creation. Students will learn the significance of foundation models and explore the implications of a concentrated geographical distribution of these models.
- 75 minutes
- AI & Social Studies
How is AI reshaping warfare?
In this lesson, students will consider ethical dilemmas raised by the increasing use of AI in warfare. After listening to a podcast from the New York Times The Daily, about Ukraine’s use of emerging AI technologies in their war against Russia, students will develop their own positions about the ethics of AI warfare through discussion with peers.
What principles should guide ethical use of AI?
This gamified lesson effectively introduces students to the ethical challenges of AI. It boosts critical thinking and ethical reasoning through engaging discussions. It also enhances collaborative skills and decision-making, providing a rich learning experience.
- Created by Matt Matilla, CRAFT Co-Design Fellow 2023-2024
- Adapted by Chris Mah
How does algorithmic bias impact different AI applications?
In this lesson, students start to understand the possible consequences of algorithmic bias. They consider a range of applications for which algorithmic bias presents a problem. This could be the 2nd lesson of a 2 part sequence.
- Created by Parth Sarin and Jacob Wolf
- Adapted by Chris Mah
What is algorithmic bias?
In this lesson, students are introduced to the concept of algorithmic bias. Students play a game that illustrates the concept through a hiring simulation. This could be the 1st lesson of a 4 part sequence.
- Created by Parth Sarin and Jacob Wolf
- Adapted by Chris Mah
How should (or shouldn’t) my data be used in AI Algorithms?
In this lesson, students are introduced to the concept of a digital footprint. They consider data publicly available about them online, including on social media. Then, they consider the ethics of having their data used in AI algorithms.
- Created by Parth Sarin and Jacob Wolf
- Adapted by Chris Mah