Day of AI is a free, open-source AI literacy initiative developed by MIT RAISE and designed primarily for K–12 education. It provides ready-to-teach curriculum, lesson plans, student activities, assessments, educator resources and professional development. The current curriculum offers a grade-by-grade progression from early primary education through high school, covering how AI works, data, algorithms, bias, privacy, ethics, generative AI, human oversight, careers and the societal impact of AI.
Why it matters for ENACT-AI
Day of AI is directly aligned with ENACT-AI objectives because it combines technical understanding of AI with critical thinking, responsible use, ethics, bias, privacy and human decision-making. The current curriculum specifically includes critical evaluation of generative AI, fact-checking AI-generated content, algorithmic bias, data privacy, environmental impacts, deepfakes and human oversight.
Learning outcomes
Learners will be able to:
Explain what artificial intelligence is and how AI systems use data.
Understand basic concepts such as algorithms, machine learning and predictions.
Identify how bias can enter datasets and AI systems.
Critically evaluate AI-generated information and recognise that AI can produce inaccurate or misleading content.
Understand the relationship between AI, privacy, fairness and human responsibility.
Analyse how AI affects people, society, education and employment.
Develop responsible and ethical approaches to using AI.
Recognise the importance of human judgement and oversight when using AI systems.
Reflect on how AI can influence everyday decisions and society.
Suggested activity
Use the “Thinking Critically About AI” lesson for students aged 12–13. Ask learners to compare different types of AI systems and investigate why generative AI can produce convincing but inaccurate information. Students can then analyse a few AI-generated answers or images, identify potential errors or misleading elements, and discuss why human verification remains necessary. Finish with a short discussion about when people should trust, question or independently verify AI-generated information.