AI (Artificial Intelligence) is becoming a topic of increasing social importance. Political reactions like the publication of the AI strategy of the German Government in late 2018 are one indicator for that. But more importantly, we are already interacting with AI systems as if it were the most natural thing in the world, for example, when using language assistants such as Siri or Alexa. Nevertheless, according to surveys, over 50% of Germans do not know what artificial intelligence is.

To address this issue, we have put together a collection of Unplugged Activities related to the topic of AI. Unplugged Activities provide approaches that help learners of all ages to experience the ideas and concepts of computer science actively and do
without the use of a computer.

This brochure contains five activities you can use to teach ideas and concepts of artificial intelligence to learners of all ages.

Nowadays, AI is primarily realized through machine learning, but artificial intelligence is far more than that: AI is not only about technical aspects, but also raises questions of social relevance. This brochure shows possibilities, how these topics can be discussed with children and adults

Vera Cubero created this framework to establish a common understanding between students and teachers regarding AI use in assignments. It addresses both the disclosure requirements and extent of AI usage.

Students will learn about the basics of machine learning and create their own apps that implement these concepts through image classification. The students will take photos with their mobile devices and the apps will identify objects within those photos. Each classification comes with a confidence level, a value of how confident the app is with its classification. Students will use MIT App Inventor’s machine learning extension called the LookExtension when creating this app.

This Introduction to Machine Learning includes tutorial lessons as well as suggestions for student explorations and project work. The unit also includes supplementary teaching materials: lesson plans, slides, unit outlines, assessments and mappings against the Computer Science Teachers of America (CSTA) computing standards.

Prompt engineering (PE) is the process of communicating effectively with an AI to achieve desired results. As AI technology continues to rapidly advance, the ability to master prompt engineering has become a particularly valuable skill. Prompt engineering techniques can be applied to a wide variety of tasks, making it a useful tool for anyone seeking to improve their efficiency in both everyday and innovative activities.

This course is tailored to beginners, making it the perfect starting point if you're new to AI and PE. However, even if you're not a beginner, you'll still find valuable insights within this course. This course is the most comprehensive prompt engineering course available, and the content ranges from an introduction to AI to advanced PE techniques.

These days Artificial Intelligence and Machine Learning are all the craze, but have you ever wondered how in the world is it really possible to teach a machine to learn something, anything really, and become, well, artificially intelligent? In this project, using the context of one of the simplest children's games, Rock-Paper-Scissors, you are challenged to create a program that allows the machine to observe and learn from its user's game choices using a Markov Model to quickly become intelligent enough to repeatedly beat the user at the game.

In an extremely controversial case, Wisconsin v. Loomis, a machine learning algorithm was used to assist a sentencing decision. This case has triggered an impassioned debate in the legal community regarding the proper use, if any, of artificial intelligence (AI) and machine learning in the justice system. In response to this case and advances in technology, the US Supreme Court and its justices are beginning to contemplate AI and more generally, technology's role, in influencing law.You will review three articles exploring the controversial case in Wisconsin and strong arguments for and against using artificial intelligence in the justice system. After reading the articles, you will answer short response questions and prepare for your class debate.