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How Young Is Too Young: AI For Children

How Young Is Too Young: AI For Children

  • Exposing children to AI helps them build logical reasoning skills and helps them understand the ways in which they can utilise the digital tools with higher awareness and smartness.

The future where our cars will drive themselves or robots will conduct surgeries is closer than ever before. The age of AI has arrived and is impacting and changing the world in unpredictable ways. It is important to believe that while we are slowly getting accustomed to AI, the children now will be dependent on it.

Children are not just using AI and learning to interact with it, but already making it as well. In 2018, Tanmay Bakshi (then a 14-year-old) became popular as the little AI wonder who works with Google and IBM. He became the face of AI learning for children in India. In 2019, when Siddharth Srivastav Pilli, a class 7 boy, bagged a job as a data scientist with a software company in Hyderabad, AI for Kids became popular. Parents got really interested in teaching their children AI. India’s new National Education Policy 2020 did mention the importance of emerging technologies and introduced them to children.

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Making AI Fun for Children  

AI as a subject is still far from being introduced in every school and in every education board’s syllabus in India. But, many edtech companies have introduced AI courses for children as young as 8-year-olds. “It’s a completely different ballgame when it comes to teaching kids artificial intelligence as compared to college students. The concept of AI itself is Greek and Latin to them, so the way the classes are delivered and the curriculum is designed is very different as compared to college students,” said Prabhakar Nadar, CEO, Edurific.

He also said that to teach children, they have to follow more practical applications without exposing them to the theory. “Kids get bored easily. We have to frame the classes so that they have an achievement-driven approach, or they can make something at the end of every few classes,” Nadar added. They start their AI classes by introducing children to basic AI applications like chatbots and then gamify the entire image recognition and other complex AI concepts, then move on to building basic algorithms and applications of AI.

Do Children Really Need to Learn AI?

While the edtech companies have figured out ways to teach children the technology, it surely remains a question whether children really need to learn AI. According to Dhrupal Shah, CEO, STEMpedia, “AI is very much engagement for kids. We don’t want to make them AI engineers or researchers. We want them to get fascinated and exposed to the new technologies growing around them like voice assistants (Ok, Google, Alexa), smart cameras, chatbots, etc. The curriculum designed for younger kids on AI is curated to give them application-based use cases, and it usually includes less theory or the real maths behind.”

Experts believe that children must know how AI works, not just from a development point of view but also from a consumer point of view. “They should be able to understand the dynamics as it’s going to be a major part of their life with the current development in the field,” said Nadar.

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When it comes to mental development too, AI-based activities can help kids keep higher focus as compared to just computer coding. “There are much more real-world logic-based things while making AI-based projects rather than just fictional stuff,” echoed Shah.

Wrapping Up

AI has been evolving since 1951. In fact, a lot of working applications of AI were actually written in 1951 and have been evolving since then. We are exposed to AI from phone cameras to light bulbs, making the technology very relevant for many years from now. And if children are learning AI, we should also not underestimate them. “Our students surprise me every time I have a conversation with them. They are way ahead in terms of development and using technology. Our students who are as young as 9 years are able to develop automation and base level AI applications ranging from computer automation and NLP, NLU models and image recognition models,” concluded Nadar.

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