The National Educational Policy (NEP) 2020 was introduced this year. One of the highlights of NEP has been the emphasis on introducing artificial intelligence, machine learning, and related technologies into the curriculum. When we think of exposing children to technology-based learning, there is often a certain amount of scepticism involved. Parents and teachers are often torn between the question — how soon is too soon. However, it doesn’t need to be as intimidating as it is made out to be. There are a lot of resources available for children to start their baby steps into this field in a fun and engaging way. We list some of them below:
Experiments with Google
Experiments with Google is an open-source platform which has a good collection of experiments on artificial intelligence, virtual reality, Android, digital well-being, and Chrome experiments. Users can use simple tools to do basic AI experiments through various media such as pictures, drawings, language, and music.
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As per the website, there are over 1,500 projects to choose from. Some of the more interesting ones are — AR insects in Google Search, Creating Your Own Art Colouring Book, Creating Shared Piano for Remote Learning, and Customising Google Assistant for Storytelling.
Broadly, these experiments are categorised into 18 categories. Some of the more prominent ones are listed here:
- Teachable Machine: These experiments enable children to create codeless machine learning models. Children can train their systems to recognise images and sounds, exporting the model to sites and apps.
- AR Experiments: There are a range of augmented reality-based projects that children can explore
- Voice Experiments: It makes it easier for developers to create new voice experiences.
- Digital well-being experiments: It basically showcases ideas and tools to strike a better balance with technology.
For those just beginning to learn to code, Scratch is a good programming language to start with. Scratch is a block-based visual programming language and website, targeted mainly at younger children to develop projects using a block-like interface. MIT Media Labs invented this service to specifically meet the requirements of children aged between 8-16; however, it is now being used by people of all ages. The latest version, Scratch 3, is available in 40+ languages.
It has over 40 million projects submitted by users from 150 countries. Some of the popular AI projects on its website include– AI Chatbot, AI Tank Battle, and AI Tic-Tac-Toe.
Machine Learning for Kids
The brainchild of IBM, Machine Learning for Kids is a free, web-based tool to introduce children to machine learning systems and applications of AI in the real world. Machine Learning for Kids is built by Dale Lane using APIs from IBM Watson. It provides hands-on experiments to train ML systems that recognise texts, images, sounds, and numbers. It leverages platforms such as Scratch and App Inventor to create interesting projects and games. It is also being used in schools as a significant resource to teach AI and ML to students. Teachers can also form their own admin page to manage their access to students.
A product from the MIT Media Lab, Cognimates is an open-source AI learning platform for young children starting from age 7. Children can learn how to build games, robots, and train their own AI modes. Like Machine Learning for Kids, Cognimates is also based on Scratch programming language. It provides a library of tools and activities for learning AI. This platform even allows children to program intelligent devices such as Alexa.
Another offering from Google in order to make learning AI fun and engaging is AIY. The name is an intelligent wordplay with AI and do-it-yourself (DIY). The products available under AIY are one of the two variants — voice kit which allows users to build projects in voice recognition; and vision kit for developing projects with image recognition and ML.
AIY is a physical kit which helps beginners to get hands-on experience to learn and experiment with AI. Generally, each of these kits contain a cardboard shell, vision bonnet, a speaker or a lens, and a tripod stand. These can be connected to other peripheral devices as well.
Now that we have discussed the go-to resources to learn AI and machine learning, it is equally important that parents, guardians and teachers adopt these approaches towards it. Before getting hands dirty, children should be made to understand the whys and hows. Sure, AI and ML are touted as the technologies of the future which are going to dominate the job market, but that should not be the sole motivation to introduce these technologies to children, especially among the younger ones. It should be looked at from an angle of problem solving and skill development.
Another important factor that should be considered is the interest level of the child. No two children are the same, and understandably one cannot expect each child to have an interest in technology. Thrusting one’s own interest upon children is not only distressing but also an exercise in futility.