A hands-on version of the AI or Not? sorting activity in which students sort pictures of contemporary technology into two groups: technology with AI and technology without AI. The activity is designed to get students thinking about the three parts of machine learning (dataset, learning algorithm, prediction) as a tool for determining whether the technology in their everyday life uses AI or not.
This activity introduces students to data classification and prediction, by having students play a game (hands-on or using Nearpod) to predict whether pieces of technology use AI or not. It is an introduction to the first Teachable Machine Activity (Thumbs-up/Thumbs-Down).
The AI Career Portfolio Activity includes this activity and others. Students can complete this activity as a stand-alone, or include it within the AI Career Portfolio.
The AI Career Portfolio Activity includes this activity and others. Students can complete this activity as a stand-alone, or include it within the AI Career Portfolio.
The AI Career Portfolio Activity includes this activity and others. Students can complete this activity as a stand-alone, or include it within the AI Career Portfolio.
The AI Career Portfolio Activity includes this specific activity and others, and is an alternative to this stand-alone activity.
This activity allows students to explore online GANs tools (GANimals, Sketch RNN, Pix2Pix, AI Duet, and handwriting) to determine how GANs work.
This activity builds on the Cat/Dog Classifier Teachable Machine Activity to have students re-curate the data to improve the algorithm.
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.
This activity suggests that if several of the AI careers activities will be used, the student work could be collected into a career portfolio.
