AI Hub: Open Access Resources

Students will read and write about how TrailGuard uses computer vision to protect wild elephants from poachers, while also investigating the limits of this technology.

Students will read and write about opposing perspectives on using generative artificial intelligence to improve non-player characters (NPCs) in video games.

Students will read and write about how researchers are using large language models to try to communicate with whales.

Students will read and write about the benefits and drawbacks of AI voice cloning technology in the music industry.

Students will read a text about the pros and cons of using physical AI for NBA training.

Students will read a text about the pros and cons of an AI-powered athletic scouting tool.

Students will read and write about how researchers are using AI and audio analysis to monitor the health of coral reefs.

Students will read and write about opposing perspectives on AI influencers.

Students will read a text about the pros and cons of an AI-powered gymnastics judging tool.

Artificial intelligence technology is evolving quickly. Use this short lesson to help students get acquainted with how AI works and consider some of its potential benefits and drawbacks.

How does data determine what artificial intelligence can do?

Why are AI chatbots designed to sound so human-like, and how can that impact our everyday lives?

How can AI chatbots impact our idea of friendship?

How does AI bias happen?

What are the impacts of AI bias?

How does artificial intelligence influence what we see online?

What are the benefits and risks of facial recognition?

What is the impact of artificial intelligence on how we learn and create?

A collection of short AI literacy activities for grades 6–12, organized by core subject. Each Snapshot starts with a real-world AI scenario and one question students reason through together. No AI expertise is required to teach them, and teachers can use a Snapshot from any subject in their own classroom.

Not everyone agrees on the definition of AI, but one good definition is “a man-made system that exercises problem-solving or decision-making systems associated with humans”.

AI finds patterns in data and works best with lots and lots of high quality data.

Just like humans, AI recommendation systems can show bias in their recommendations.

AI can be both biased and inaccurate, but even imperfect AI systems can be useful.

AI can help solve problems you are passionate about.

Successful AI applications begin with narrow, well-thought-out problem statements.

Limited or poor quality data can lead to biased AI: AI that works differently for different groups of people.

AI can absorb biases from the real world, and companies and governments must take responsibility for those biases.

Teams that divide work based on each person’s strengths build the best solutions.

Depending on the grade/age level, students explore different types of machine learning, ranging from supervised, unsupervised, and reinforcement.

Explore how AI shapes everyday life with quick activities that build curiosity and responsible digital citizenship, in just 15 minutes!

Students learn how to recognize misinformation in AI content and use fact-checking strategies (lateral reading) to verify what’s true.

A self-driven lesson introduces students to the ethical principles guiding responsible artificial intelligence use.

Students uncover how AI perceives, learns, and reasons, connecting technology to real-world challenges.

A foundational set of lessons for all students to begin their AI literacy journey.

Students uncover different ways machines can learn, dive into neural networks and explore algorithmic bias.

Students investigate how generative AI creates new images and media, exploring creativity, deepfakes, and the ethics of machine-made content.

Explore how AI is used in the world today and consider some of the benefits and drawbacks of AI systems.

Learn about the role of data-driven models in AI systems and machine learning.

Create a machine learning model to classify images and explore how a limited data set can lead to bias.

Discover how and why decision trees are used in machine learning.

Train and test a machine learning model to solve a real-world problem.

Evaluate a project by creating a model card and learn about AI-related careers.

Discover the types of personal data shared with AI applications and ways to protect privacy when using them.

Explore how the use of AI tools can support the spread of misinformation and develop strategies to distinguish fact from false information.

Reflect on learners' responsibilities when using generative AI tools and the expectations to place on the developers of these tools.

This activity is designed to engage students in critical thinking about what constitutes artificial intelligence (AI). By sorting and categorizing everyday technologies, students will draw on their pre-existing knowledge to co-create a shared understanding of AI and its distinguishing features.

Through discussions, group activities, and a structured debate, students will explore the legal arguments surrounding generative AI’s use of public sources and form opinions about what constitutes plagiarism in AI-assisted writing.

In this lesson, students learn a systematic, five-step process for conducting an algorithm audit by examining TikTok’s AI Manga filter. Using a curated database of inputs and outputs, students form hypotheses, collect and analyze data, and evaluate how algorithmic behaviors may reflect bias or unintended impacts.

In this lesson, students will learn about language models and why AI models like ChatGPT are called “Large Language Models” (LLMs). They will develop a fundamental knowledge of what makes an LLM “large” and how parameters are important to understanding an LLM’s capabilities, data needs, and power requirements.

Scientists are already using AI to map environmental risks, analyze huge amounts of climate data, and make predictions to combat climate change. In this lesson, students will investigate how these technologies consume energy and water and the broader impact of AI on sustainability.

AI tools have opened up possibilities in story creation allowing for help with idea creation, story format and writing. In this lesson, students will explore how AI can be used in storytelling including how to consider the benefits and trade-offs of incorporating AI into the storytelling process.

Studies consistently show that students are using AI chatbots and search engines like ChatGPT and Perplexity. In this lesson, we’ll introduce students to the skill of lateral reading (Wineburg & McGrew, 2017) as one approach to fact-checking the information they get from AI.

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 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.