Artificial intelligence is probably the most widely thrown around buzzword in computer science and in education these days.
The reason for this is simple: from chatbots to health care to self-driving cars, the development of artificial intelligence is so revolutionary that it is changing the way in which we interact and use technology.
Whether it is machine learning, neural networks or computer vision, AI is certain to be a cornerstone of coding and technology in the very near future and it is more important than ever that our kids learn as much as they can about this exciting aspect of computer science and coding today so that they can take a more leading role in tomorrow’s brave new world.
What is AI (Artificial Intelligence)
Artificial Intelligence, or AI for short, is a broad branch of computer science that seeks to give computers and machines more advanced decision-making and problem-solving capabilities in an attempt to mimic the intelligence of human beings (or surpass it).
The overall idea is to combine more autonomous and intelligent decision making with the processing power and speed of computers in order to blow past the current capabilities and limitations of today’s processes and, hopefully, improve our daily lives in the process.
There are several different subfields within artificial intelligence, each focusing on different goals and cultivating different skills. The most popular today are:
- Neural Networks – computer systems that are modeled on the brain and nervous system
- Computer vision – which focuses on training computers to identify and understand visual inputs, such as pictures and videos
- Machine Learning – focuses on developing computer algorithms that can autonomously make decisions and improve over time using past and current data
- Speech Processing – focuses on designing computer systems that can recognize spoken words
- Natural Language Processing – focuses on enabling systems to better understand the human language and make sense of it when inputted through text or speech
Why is it important that kids learn about Artificial Intelligence?
From advanced search engines and recommendation engines to life-saving medicine, AI and AI-like algorithms are increasingly becoming central to modern software and technology and this trend is likely to only continue in the future.
If we want our kids to be ready for the future of coding and become leaders who use technology rather than just passively consuming it, then they will have to become familiar with this intriguing new branch of computer science.
Beyond coding, STEM learning and career future-proofing, however, studying Artificial intelligence can have some other positive effects on kids.
Promoting Creative Thinking Through Coding
Because AI deals with some complex problems and ideas it can really give kids a solid brain work out.
AI is all about finding creative solutions to problems while thinking through AI models and solutions.
As such, kids will have to think of various different and novel ways they can “teach” a machine to start solving problems and, of course, figure out how to translate what they want a machine to do into actual usable code.
Developing Stronger Problem Solving Skills
Learning to breakdown and approach problems sequentially and logically is a cornerstone of artificial intelligence.
To effectively understand and work with AI coding and to get machines to solve problems, students themselves need to learn to methodically approach problems and think more computationally themselves in order to assess solutions- a valuable skill that can carry over to math, science and other areas of study.
Developing Data Literacy and Fluency
Programming aside, a good part of AI is about collecting, analyzing and understanding data.
AI systems, particularly those involved in machine learning, are hungry for data, learning as they do from large data sets.
As they learn about AI and how to work with its various forms, kids will develop a better understanding of the importance of data and, more importantly, get more practice at handling and making use of it – so-called, data fluency that is increasingly critical in STEM studies and in the workplace.
Is AI something kids can really learn?
Now, obviously nobody expects kids or even high school graduates to really do a deep dive into AI or its component topics.
After all, really getting into the topic and using it requires a fairly sophisticated understanding of coding, math and computer science principles.
But there is nothing really stopping kids from learning the basic ins and outs of AI, especially if they are already starting to learn how to code.
There is nothing stopping a student, for example, from learning what AI is, how it works in principle, it’s potential applications and even trying their hand at creating simple models and systems themselves.
In fact many project-based learn to code programs and resources for kids have begun adding modules specifically around some of the concepts of machine learning, neural networks and data science.
In these programs, students can use their coding and certain AI principles to create chatbots, their own speech to text programs, object and symbol recognizers, autonomous robots, and more.
Similarly, and perhaps most helpfully, programs have even begun creating AI-centered learning modules for Scratch and other beginner-friendly visual coding programs, where kids can learn some of the concepts of machine learning, neural networks, data trees and more.
These programs sometimes even have access to visual coding-based pre-trained models that students can use to more easily create their own algorithms and AI-like programs.
When should kids start learning AI?
While the basic principles of AI and its models can (and should) be taught in very simple terms to kids at any age, and while coding fundamentals can be introduced easily to kids as young as 8, generally speaking Artificial intelligence and its various models are a little more advanced and complex than what might be covered in a kids coding program.
Typically, we think the best time to start is around 13 and up.
The reason for this has less to do with coding experience (although this helps) and more to do with the typical cognitive development of a young teen.
It is generally around the age of 13 and older that kids’ brains tend to begin to develop a greater capacity for abstract thought.
As this develops, young teens tend to have an easier time understanding models and symbols and don’t need concepts to be as linked to concrete representations as younger kids may.
Since much of coding AI is quite abstract, representing real life data with lines of code and developing various models to represent real world behaviors, it can be a little much for younger kids.
Similarly, it is at this age that kids tend to develop a stronger ability to follow and implement logical operations and problem solve in a more sequential way, something that’s critical to computing and AI.
Finally, and perhaps more importantly for AI, it is at this age that kids begin to think more outside themselves, better understanding other people’s points of view and, critically, how they perceive the world and approach problems.
In many ways this is perhaps the most critical cognitive development for coding AI, since the overall idea is to get a machine to ultimately think for itself, which requires understanding how the system is interpreting data and discerning why it is doing what it is doing.
Laying the groundwork for future AI Learning: Coding and Computational Thinking
Rather than only worrying about inputting lines of code to create their own learning program, to start learning about AI students really need to develop stronger skills at logic and computational thinking, that is:
- Organizing data
- Breaking a problem down
- Turning it into a series of steps
- Deriving efficient solutions
In other words, in order to better help computers and systems solve problems efficiently, kids themselves need to have a good understanding of how to approach problems sequentially and logically, a skill that can certainly be taught and sharpened at home.
That said, as both a theoretical and very practical branch of computer science, it’s probably no surprise that learning about artificial intelligence will require kids to learn some coding.
AI and Scratch
Scratch (and other visual coding programs) can be an excellent place for kids to start if they have no previous coding experience.
It makes coding simple (and some not so simple) programs quite easy – students simply drag and drop blocks of code, linking them together into functional programs.
Although they don’t learn any particular coding language, or get experience inputting and debugging lines of code, kids can learn and get experience using fundamental coding concepts important to AI, such as event listeners, variables, algorithms, automation and more, without getting frustrated or tripped up by their reading and writing skills or the syntax of code.
Scratch can and has been used to create some interesting (although somewhat simple) AI scripts and projects, usually in the form of playable games, that capture the essence of some AI concepts in a way that kids can immediately appreciate.
Invariably, however, kids will have to move on and learn a written coding language, which brings us to….
AI and Python Coding
Python is a text-based coding language that is widely used in the field of artificial intelligence due to its ability to easily handle large amounts of data, its ability to create rapid iterations and prototypes, and its large amount of support in the form of libraries and AI frameworks.
It can also be a great place for kids who are really interested in coding and AI to get started with a “real” coding language due to the fact that it’s a pretty easy to learn language with a fairly simple syntax, and is pretty forgiving of user error compared to other languages.
In fact, there are a ton of resources specifically designed for kids who want to learn to code in Python.
Due to the above factors, Python is probably the language parents want to look at if they are interested in introducing some AI into their kids coding curriculum.
Uh oh, Numbers: AI, Kids and Math
While there are courses and textbooks out there that promise kids they can learn “all about AI” with little to no math, the fact of the matter is that computer science in general, and artificial intelligence in particular (in all its types), is generally pretty math heavy.
In terms of AI, those working in the field generally have a familiarity with:
- Discrete math
- Statistics
- Graph theory
- Linear algebra
- Set Theory
As well as the usual
- Calculus
- Differential equations
- Logic and proofs
Now this math is far beyond the level of what kids can be reasonably expected to learn, and is probably what they may be expected to learn in a college-level computer science program.
But the foundations should certainly be laid down in elementary, middle and high school.
By developing stronger math skills and confidence earlier on parents can give their students a distinct advantage if they choose to pursue computer science and coding later on.
One of the best ways to do this is by instilling a more conceptual approach to math, one that focuses more on problem solving and understanding math and rewards finding multiple, creative solutions to problems, rather than a more traditional, computational approach that focuses on answering problems quickly and drilling math facts.
My child struggles with math but loves coding, can they still learn AI?
With all that said, it is certainly possible for kids to learn the basic concepts of AI, deep learning and more, at least on a conceptual level, without becoming a math wiz.
When it comes to kids courses, many explain the gist of what’s going on without spending too much time delving into the math, breaking complex models down with simple and intuitive explanations that are easier for kids to understand.
Students can certainly work through coding projects, pull in models and libraries and build an overall, more intuitive understanding of what’s going on, even if they don’t necessarily develop a complete understanding of specific algorithms and models.
Helpful Resources for Teaching AI to Kids
Paid Resources
Codakid
Codakid is well-known for its fun and interesting courses in coding for kids, covering Python, JavaScript, Java, Unity and more with its entertaining and kid-friendly projects, as well as its high-energy and very approachable teaching videos.
In addition to being able to give kids valuable coding knowledge and skills to build upon, many of their projects (game programming, for example) include relevant AI-topics as well.
The company also runs dedicated coding camps periodically that help students take coding to the next level and quite often include the exploration of AI models, usually in relation to gaming.
Check out our review of Codakid for more information, or you can visit their website for detailed information about their courses and prices.
IdTech
If you have a student who is becoming particularly skilled at coding and is looking to upgrade their skills in a more focused and advanced way, IdTech can be an interesting solution to look at.
The company runs offline/online courses, personal and camps for kids up to age 18 covering a variety of different topics, including a pretty interesting course in artificial intelligence and machine learning with Python (for kids 13+).
Outschool
Outschool is a provider of small-group, online classes for kids up to age 18 and offers a wide variety of subjects taught by experts in their fields.
A more formal learning environment, these classes can be a great option for students who don’t learn well on their own, and there are a wide variety of courses covering various aspects of artificial intelligence.
A cursory search led us to find conceptual classes about understanding AI and its implication, classes helping kids code robots for basic AI, machine learning courses and more.
Due to the wide variety of courses you can find on Outschool, one does have to be a little careful that the course a child is signed up for is actually practical and involves coding, but they are usually quite well structured and quite affordable, often costing a fraction of a traditional coding course for kids.
Free Resources
Machine Learning for Kids
From the UK, Machine Learning for Kids is a website that contains a lot of fun and interesting resources for helping kids learn AI.
There is a ton of information, as well as worksheets and a variety of resources for implementing AI using Scratch, including some basic but still interesting pre-trained models kids can use.
Experiments with Google
A world-leader in the development of AI and related algorithms, Google has provided a wealth of videos, experiments and projects in AI that parents, teachers and kids can try out on their own.
In terms of AI, there are quite a few on hand. These range from the fairly simple to the pretty complex and can be a great supplement to learning once kids understand the basics and have some experience at coding under their belt.
Teens In AI
Launched at the UN’s AI for Good Global Summit, Teens in AI recognizes the importance of AI to the larger world and aims to get teens 12-18 around the world interested in and learning AI.
The organization sponsors meetups, workshops, talks, hackathons and networking events aimed at kids, and can be a great place for kids to find support and like-minded friends to help them take their skills and knowledge to the next level.
Bottom Line
Artificial Intelligence is a rapidly growing field that will become central to technology, and our lives, in the coming years.
Although seemingly advanced and complicated for kids, AI is (at least in terms of fundamentals) a surprisingly approachable and interesting topic for students interested in coding.
As parents it is incumbent upon us to provide our kids with the tools they need to succeed, and understanding AI will certainly be a critical skill they’ll need to develop.
About the Author
David Belenky is a freelance writer, former science and math tutor and a tech enthusiast. When he’s not writing about educational tech, he likes to chill out with his family and dog at home.