Explore and create: Deep-dive Creation lab 
Preregistration Required
Purpose:
To equip educators with the knowledge, tools, and pedagogical skills necessary to effectively deliver Code.org’s How AI Works curriculum that intertwines technical content with societal and ethical considerations, leveraging video content, hands-on activities, simulations, and reflective discussions.
Objectives:
Participants will be well-acquainted with the entirety of the AI curriculum, including its associated activities and video content.
Participants will gain a foundational understanding of AI essentials such as computer vision, recommendation mechanisms, and AI's text-learning processes.
Participants will develop the skills to initiate and moderate insightful classroom conversations about AI's implications, its innate creativity, and the provenance of AI-created outputs.
Participants will be equipped with resources and knowledge to elucidate the ethical quandaries of AI and expound on its broader societal ramifications.
Participants will recognize the paramount importance of multifaceted perspectives, particularly when delving into AI's decision-making and recommendation processes.
Participants will be introduced to, and achieve competence in, various interactive platforms wherein students can directly collaborate with AI for a hands-on learning experience.
Evidence of Success:
By the conclusion of the training, educators should be adept in delivering the AI curriculum with confidence, ensuring their students not only understand AI's foundational concepts but also critically engage with its societal and ethical implications.
Ice Breaker (5 minutes) - engaging activity to get participants comfortable
Introduction to Machine learning (10 minutes) - Teachers will be introduced to a form of artificial intelligence called machine learning and will learn how they can use the Problem Solving Process to help train a robot to solve problems. They participate in three hands-on machine learning activities where a robot - AI Bot - is learning how to detect patterns in fish.
Computer Vision (15 minutes) Teachers learn how computer vision works and engage in a group unplugged activity where they design an algorithm that uses a network to decide what number the seven segment display is displaying..
Lesson JigSaw (35 minutes) Teachers will be broken into groups and assigned one of four remaining lessons: Neural Networks, Chatbots and LLMs, Generative Images, Algorithmic bias. In the groups, they will examine the lesson and prepare a short presentation for the whole group.
AI Code of Ethics (15 minutes) In small groups, participants examine articles and videos that expose ethical pitfalls in an artificial intelligence area of their choice. Afterward, each group develops at least one solution-oriented principle that addresses their chosen area. These principles are then assembled into a class-wide “Our AI Code of Ethics” resource (e.g. a slide presentation, document, or webpage) for AI creators and legislators everywhere.
Wrap-up (10 minutes) Answer questions and provide further resources.
https://hai.stanford.edu/news/ai-will-transform-teaching-and-learning-lets-get-it-right
How to Teach Artificial Intelligence (AI) in School? - STEMpedia Blog (thestempedia.com)
Artificial Intelligence (AI) vs. Machine Learning | Columbia AI
https://tech.ed.gov/ai/
https://teachai.org/
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