Machine vision. Data wrangling. Reinforcement learning. What do these terms even mean? In AI 101, MIT researcher Brandon Leshchinskiy offers an introduction to artificial intelligence that‚Äôs designed specifically for those with little to no background in the subject. The workshop starts with a summary of key concepts in AI, followed by an interactive exercise where participants train their own algorithm. Finally, it closes with a summary of key takeaways and Q/A. All are welcome!

This resource is to support teachers and educators to run Day of AI activities in their classrooms through curriculum packages and teacher training, all of which is available at no cost to participants.
Developed by leading faculty and educators from MIT RAISE, the curriculum features up to four hours of hands-on activities that engage kids in creative discovery, discussion, and play as they learn the fundamentals of AI, investigate the societal impact of these technologies, and bring artificial intelligence to life through lessons and activities that are accessible to all, even those with no computer science or technical background.

This video aims to delve into the human problems brought out by issues in artificial intelligence, specifically with respect to bias. It is suitable for classroom use or as a standalone video for those who wish to understand the issue more deeply than is conventionally covered. For classroom use, we recommend watching the chapterized version of the video and working through the teaching materials provided for each chapter.

The emergence of transformer architectures in 2017 triggered a breakthrough in machine learning that today lets anyone create computer-generated essays, stories, pictures, music, videos, and programs from high-level prompts in natural language, all without the need to code. That has stimulated fervent discussion among educators about the implications of generative AI systems for curricula and teaching methods across a broad range of subjects. It has also raised questions of how to understand both these systems and the at times overstated claims made for them. This class will introduce the foundations of generative AI technology, and participants will explore new opportunities it enables for K–12 education. It will also describe and explore how an analytical frame of mind can help make clear the core issues underlying both the successes and failures of these systems. Much of the work will be project-based, involving implementing innovative teaching and learning tools and testing these with K–12 students and teachers.

Media Literacy in the Age of Deepfakes aims to equip students with the critical skills to better understand the past and contemporary threat of misinformation. Students will learn about different ways to analyze emerging forms of misinformation such as “deepfake” videos as well as how new technologies can be used to create a more just and equitable society. This module consists of three interconnected sections. We begin by defining and contextualizing some key terms related to misinformation. We then focus on the proliferation of deepfakes within our media environment. Lastly, we explore synthetic media for the civic good, including AI-enabled projects geared towards satire, investigative documentary, and public history. In Event of Moon Disaster, an award-winning deepfake art installation about the “failed” Apollo 11 moon landing, serves as a central case study.
This learning module also includes a suite of educator resources that consists of a syllabus, bibliography, and design prompts. We encourage teachers to draw on and adapt these resources for the purposes of their own classes.
Visit Media Literacy in the Age of Deepfakes to access the learning module and educator resources. A sample of some of these materials can be found on OCW.
This course was produced by the MIT Center for Advanced Virtuality, with support from the J-WEL: Abdul Latif Jameel World Education Lab.