This is a collection of constantly growing and developing resources. Be sure to check back regularly for new resources.
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In this lesson, students compare AI and human-generated texts to analyze the affordances and limitations of large language models. They’ll score, guess origins, and discuss differences, then decide which aspects to adopt or avoid in their writing. The lesson culminates in a discussion of what aspects of the AI-generated writing students should emulate in their own writing and what aspects they should avoid.
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.
In this lesson, students will watch an online video presenting the history of artificial intelligence, which goes back to the 1950s. They will also learn how current artificial intelligence technologies build on that history.
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.
In this lesson, students will explore the idea of Artificial Intelligence (AI) by looking at a concrete example of AI which uses machine learning to distinguish objects in an application called Teachable Machines.
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.
In this lesson students explore the prevalence of artificial intelligence in their personal lives. As students think through examples of AI in their lives, they explore different concepts of AI to better understand what AI is, what tasks it can do, and how it can do those.