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Sort -A-Snack!

 Students can categorize different snacks based on the images. It is middle school-related snacks.

Extension Comparing Bias

This is an extension activity to further highlight how bias exists in diffusion models and how prompt modification can highlight bias. Students are given two different models and are able to select adjectives and professions for image generation. This also includes a discussion about research linked with the tool that highlights gendered language in job advertising and how that might impact results.

What is AI? Storyboard Teacher Made

This is a framework and exemplar to use if you want to have students write a short storyboard of a potential AI tool. This is useful for integrating ELA into this lesson, including story elements.

Online version of Neural Networks Activity

An online version of the Neural Network Activity, where students simulate the working of a neural network by choosing 4 words to describe an image, which are fed forward through the network, and the results evaluated. The input weights are adjusted (back propagation) and the process is repeated with a second image.

Re-Curate a Dataset

This activity builds on the Cat/Dog Classifier Teachable Machine Activity to have students re-curate the data to improve the algorithm.  

Cat/Dog Classifier Activity

This activity builds on the Thumbs-Up/Thumbs-Down Teachable Machine Activity to have students upload photos of cats and dogs to train Teachable Machine, and then test the algorithm with new data.

"Is it for Winter?" Activity

This Activity continues from the PastaLand Activity, and asks students to design decision trees that group clothing by their shared traits or features that make them belong in a category of Winter or Not Winter clothes. On the second day, students are asked to classify the clothes using only information contained in an SKU barcode.

Calculate Your Carbon Footprint Activity

This activity allows students to use a simple carbon footprint calculator to determine how much carbon their regular activity releases. That number can be used to compare how much carbon is released by AI.

AI's Impact on My Future Job Activity

In this activity, students watch videos about AI's impact on certain jobs, and then explore how AI might impact the jobs they matched in previous activities.

Open AI News Articles Activity

This activity extends the Generate a Story lesson by asking groups of students to read a "news article" and identify what parts were written by a human and what parts by a GAN. Students then share their conclusions and discuss with the whole class.

GAN Art! Activity

This activity builds on the whole-class discussion in the Art or Not? Activity to allow students to use the Doodle to Pictures website to create their own "art" and share it on a google slide deck for whole-class discussion.

Thumbs-Up/Thumbs-Down

This activity introduces Teachable Machines and has students follow the "Teachable Machines Tutorial" to create training data sets and test the algorithm using the camera on the computer.

AI Investigation Activity

After a review of concepts of bias and classification systems, students look at examples of AI and identify bias in them, including:
Google image search results for “physicist”.
Google translate “she is a doctor, he is a nurse” from English to Hungarian and back to English.
Explore QuickDraw’s database of faces.
Google image search results for “outdoor recreation”

3.5 Redesign Youtube Lesson

In this lesson, students will redesign the YouTube recommendation algorithm to meet their needs and reduce bias. This is a culminating project that can span several days of work and spark student reflection on lessons learned from the curriculum.

2.3 AI Generated Art Lesson

In this lesson, students will explore various forms of AI-generated art. They will engage in a conversation about what is art and who can make art.

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