How to teach AI in schools — What in AI should be taught?

When teaching AI in schools, there are two things to teach: either AI theory or AI implementation. 

There are various attempts around the world to teach AI in schools. How effective is it? How much should be allowed? To what extent should other subjects be taught if AI is included as a subject? Should it be integrated into Mathematics and ICT, or included in children’s Computer Science books? Perhaps it should be a separate subject. Adding AI as a separate subject would increase the study load on children, so some subjects’ syllabi must be adjusted. The same applies to Quantum computing. If you want to teach Quantum computing as a subject, some subjects should be unloaded to ensure that Quantum computing doesn’t burden the student, as students also need to engage in physical education, art, or other activities like cooking/clay modelling/swimming.

There are many inventions and advancements around the world in various fields such as AI, quantum computing, and similar areas. This does not mean we would teach children everything that is happening in the job market or in inventions related to AI. It’s about how much the child can absorb and how much background knowledge the child has.

Teaching complex mathematical concepts based on today’s deep learning is not advisable. But have you noticed that today’s children, even those in preschools, know how to operate smart TVs and navigate YouTube channels? Primary school kids are becoming experts at querying YouTube and Netflix with perfect search strings. This means some of them could be great prompt engineers. This means that 6th grade is the ideal time to start teaching the usage of AI, right? From 6th grade onwards, we can introduce AI applications; we won’t dive into the intricacies of deep learning mathematics without first covering differentials, but we would focus on AI applications, such as using ChatGPT, crafting effective prompts, generating images with ChatGPT, detecting fake news through ChatGPT, and editing videos using ChatGPT.

The basics of neural networks can be taught to students. It should be ensured that AI is fun for children; there are some visual Quantum Computing topics that young students grasp well. One should follow this approach. Other areas that should be taught to children include the basics of networking, computer organization, and architecture, especially to high school students, as these topics are essential for understanding AI.

In summary, the way forward can involve credit-based subjects, where students can choose from options such as Quantum Computing, Artificial Intelligence, or Computer Security, to name a few. This approach allows children to acquire knowledge in the areas they are most passionate about. It also enables students to pursue a major in these fields in the next academic session. Flexible credit-based subjects can help parents understand which subjects their children find interesting, aiding in the selection of graduation degree courses with the support of the students. Imagine a student pursuing both AI and Quantum Computing because he or she is particularly inclined toward these subjects. It’s time to change how we teach our young learners. 

To be continued…

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