Chapter 4: Learning Constituents reminded us that as we conceptualize what we want AI in edtech to accomplish, we must start and constantly revisit a human-centered vision of learning. 4.4. A Duality: Learning With and About AI As AI is brought into schools, two broad perspectives about AI in education arise: (1) AI in support of student learning; and (2) support for learning about AI and related technologies. So far, we’ve discussed AI systems and tools to support student learning and mastery of subjects like mathematics and writing. Yet, it is also important that students learn about AI, critically examine its presence in education and society, and determine its role and value in their own lives and careers. We discuss risks across each section in this report. Here, it is important for students to become more aware of and savvy to the risks of AI—including risks of bias and surveillance—as they appear in all elements of their lives. In the recent past, schools have supported students’ understanding of cybersecurity, for example. AI will bring new risks, and students need to learn about them. We are encouraged by efforts we’ve seen underway that would give students opportunities to learn about how AI works while also giving them opportunities to discuss relevant topics like privacy and security. Other learning goals are noted in the K-12 Computer Science Framework. We’ve seen that students can begin learning about AI in elementary, middle, and high school. They can use AI to design simulations and products that they find exciting. And we’ve seen that students want to talk about the ethics of products they experience in their everyday lives and have much to say about the kinds of products they’d like to see or not see in school. (And later, in the Research section, we note the desire for co-design processes that involve students in creating the next generation of AI-enabled edtech). Overall, it’s P a g e | 37
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