This guide is for educators who teach visual and performing arts, physical education, foreign languages, and other electives or special courses that don’t fall neatly into the four core academic areas of English/language arts, social sciences, mathematics, and science...Until recently, conventional wisdom has held that the areas of study targeted in this guide are unaffected by AI—that creativity demands human input. For now, this may be true to an extent, but it is entirely likely that in the not-too distant future, people who want careers in these fields will be required to incorporate AI into their work to some degree. In many instances, this will simply necessitate that the end-user (director, choreographer, coach, journalist, or educator, for example) understand how to use an AI tool to block a play, choreograph a dance, profile an athlete’s strengths and weaknesses using data collected with wearable technology, access a curated collection of news images, or teach students how to use a tool that will help them learn a new language most efficiently. In other cases, an artist may need to create their own machine learning model that will classify images they wish to use. Each of these examples emphasize that, while the people who design these tools will likely be coming from math, science, and computer science disciplines, end-users like artists, performers, coaches, and educators must be participants in the conversation if these tools are to effectively meet their needs. -- Pages 6-7