It’s not easy to teach your kids about machine learning. While it may not be as simple as singing rhymes or learning times tables, it certainly is possible.
Learning about AI and machine learning can be really rewarding for children. They can enjoy the knowledge of both subjects as a hobby or they could even turn it into a future career! There are many ways to make machine learning and AI fun and engaging for children.
This article will discuss both machine learning and artificial intelligence for kids and look at different ways to introduce your child to these fields.
What Is Machine Learning?
What exactly is machine learning? Machine learning is the process of using artificial intelligence to teach a machine to do something on its own without human interference. The machines access data from the real world, process it with their complex algorithms, and take actions based on what they learn.
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Teaching machine learning to children can be challenging. The field of machine learning has become very popular in recent years, and it requires a good understanding of science and mathematics.
If you’d like to explain machine learning to your child, use this as an example: imagine a child-sized battery powered vehicle. It relies on the steering, gearbox, and clutch to work properly. In order to successfully drive the car, it’s important to know how and when to use these tools.
Using machine learning, you can teach a simple toy car what to do through the use of data, examples, direct experience, and instructions. You know the saying: “Give a man a fish, and you feed him for a day. Teach a man to fish, and you feed him for a lifetime.” This quote can apply to machine learning; you want a machine to be able to learn without human assistance so that it can perform tasks on its own.
This example with the toy car is an easy way to introduce machine learning to your child. The toy car learns how to drive independently through practice, simulations, data, and trial and error. Through these practices, you are able to tell what works and what does not. You will then be able to create a toy car that can drive on its own without a human at the steering wheel.
Of course, the car does not have a human brain. Instead, electronics are used to run an artificial intelligence alongside the car so that it processes data, understands its environment with sensors, and then self-evaluates its progress to learn to perform better. This is machine learning in action.
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Teaching Your Children About Machines
There are two major ways to teach children about machines: through supervised learning and unsupervised learning.
Supervised learning is all about building a model that makes predictions based on evidence. It accounts for information you are unsure about and what the machine does not know. This type of learning uses algorithms to receive input data, calculate known responses to that same data, and train a model to make reasonable responses.
If you’re having a hard time picturing what all this means in practice, here’s an example: imagine there’s a medical AI whose job is to predict how many of its patients may suffer from heart problems in the future. It creates this prediction by first looking up patient data such as age, weight, height, blood pressure, and heart rate variability. The AI then combines this data with information from previous patients who have suffered from heart attacks. It then processes this data, pushes all the data through a model, then predicts whether a patient is at risk of suffering from a heart attack or not.
Unsupervised learning is all about finding hidden patterns in data and drawing inferences from data sets without labeled responses. We can do this with the help of a technique known as clustering. Clustering is the most common unsupervised learning technique. It’s a way to group data into different clusters that have the same data points. We use clustering for market research, gene sequence analysis, and facial recognition.
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Here is an example of clustering: picture a cell phone company that wants to build signal towers to reach all its customers. The cell phone company uses machine learning to estimate the number of people who depend on their towers. Based on this information, the company builds the towers exactly where they are needed. Companies rely on algorithms to make the best decisions on where to place their towers. Without AI, companies would not be able to optimize the signal receptions for their customers.
Examples of Machine Learning in Everyday Life
Where can you find machine learning put into practice? What are some businesses and industries that put machine learning into action? To explain the benefit of machine learning for kids, you can provide them with these concrete examples of real-life applications:
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1. The Medical Sector
Machine learning can be used to diagnose and predict health problems. Many physicians already use chat-bots to help them diagnose patients. These same machines can even use speech recognition to deduce patterns and symptoms in patients.
Machine learning isn’t just used for diagnosis; it is used for robot-assisted surgeries as well. Some machines can even take a snapshot of a patient’s face and spot phenotypes linked with genetic diseases.
2. Speech Recognition
It’s no secret that there has recently been a boom in modern technology. These innovations can be seen everywhere. From technology that can listen to your speech and convert it seamlessly into text to smart home devices that help you with your shopping, machine learning is used in life every day. Even if you may not realize it, machine learning is also used when you use cell phones for voice searches and voice dialing.
3. Image Recognition
One of the most commonly known instances of machine learning in everyday life is the use of CAPTCHAs to identify traffic lights, cars, and other vehicles in traffic. Machines are trained to be able to determine what they see on the road; one day, they may safely drive among us.
We also use machine learning to identify people in photos, like when you tag photos on social media. Machine learning is used to recognize text from handwriting as well. This is called optical character recognition.
Another well-known example of image recognition is facial technology. Facial recognition uses biometrics to map facial features from a large database of people’s photos and videos. This technology can use its database to match the images with people seen on the street. Because of this feature, facial technology is becoming increasingly popular among law enforcement officials worldwide.
Machine learning is all about data science, statistics, mathematics, and programming.
The field of machine learning has become progressively popular. One of the aspects that makes a career in this field so in demand is the salary: starting salaries range from $100,00-$150,000 a year. Most entry-level careers do not have salaries of this magnitude, making a career in machine learning very profitable from the beginning.
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Getting your child started with machine learning from a young age makes it much easier for them to become experts in the field more quickly than if they began practicing later in life. Math, data science, statistics, and programming are quite difficult fields. It’s worth your time to invest in additional courses and coaching so that your children can successfully learn the fundamentals of these subjects.
The demand for both machine learning and programming jobs is so high that many schools have started teaching programming languages such as Python in grades as early as middle school.
This is so kids can familiarize themselves with programming techniques such as writing semicolons, ellipses, and dashes as soon as possible. All of these aspects make machine learning for children a popular topic among educators right now.
AI for kids can be a tricky topic to introduce to your children. To make it easier for them to understand, slowly present them with specially made programming languages such as Blockly and Scratch. These languages are simple enough, colorful enough, and engaging enough to capture the minds of young ones. They also do a great job of teaching them how to think logically and creatively in a step-by-step manner.
Motivate your children to learn more about AI and machine learning by exposing them to television shows like Robot Wars and Battlebots. If they like video games, try encouraging them to make their own video game for fun! Help them learn and create in all aspects of their life. Provide your child with plenty of positive feedback and praise when they accomplish something, even if the feat is small.
Machine learning and artificial intelligence for kids go hand-in-hand. This is an incredibly rewarding field that is both challenging and stimulating. With most careers in this field offering solid salaries, machine learning ensures your child will have a bright future.
Math, science, statistics, and programming are all fields in which your child should get involved if they are interested in a future in machine learning and AI.
Since this is a popular field, there are numerous amounts of free resources available online. If you’re looking to enroll your child in classes about machine learning and artificial intelligence, be sure to look for reputable classes with credible teachers.
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