June 30, 2025

AI, Machine Learning & Algorithms—What’s the Difference?

When people talk about artificial intelligence, they throw around a lot of techie terms—but what do they actually mean? Here’s a quick, easy guide to AI, machine learning and algorithms.

AI, algorithms, machine learning—these words get thrown around a lot, especially when it comes to tech our kids are using. But what do they actually mean?

Here’s the quick breakdown parents need to understand how these tools work, and how they’re shaping our kids’ digital lives.

So… what is an algorithm, anyway?

At its simplest, an algorithm is just a set of rules or instructions a computer follows to solve a problem or make a decision. Kind of like a recipe.

You put in ingredients (data), follow steps (the rules), and get a result (like “show this video next” or “sort these photos by date”).

Algorithms are everywhere. They’re what decide:

Which videos pop up on your child’s YouTube homepage
Which filters are available on their photo apps
Which ads show up on your screen (even if you swear you only thought about that product)

They don’t always involve artificial intelligence. Sometimes they’re super simple—just rules someone programmed in manually.

AI: the big umbrella

Artificial intelligence, or AI, is the broadest term here. It covers any kind of technology that mimics human thinking, whether it’s following rules, recognizing patterns or generating new stuff entirely.

So yes, machine learning falls under AI. And so do algorithms that help tech make decisions. But AI also includes more complex tools, like:

Chatbots that hold full conversations
Image generators that turn prompts into pictures
Virtual assistants that plan your day or suggest what to cook for dinner

Machine learning: how AI gets smarter

Machine learning is what helps AI improve over time—without needing a human to constantly reprogram it.

Instead of following fixed rules, machine learning systems learn from the data they see. The more they process, the better they get at spotting patterns, making predictions or adjusting their behavior.

So if an app notices your child always skips certain types of questions, it might stop showing them. If it sees they’re breezing through a math level, it might offer harder problems next time. That’s machine learning in action.

It’s not magic—it’s just data, patterns and (hopefully) smart design. But it does mean these systems can change in ways that feel personalized… and sometimes unpredictable.

In short:

Algorithms = the instructions it follows to get things done

AI = the brain

Machine learning = how it gets smarter over time

Why this matters for families

You don’t need to memorize the definitions, but knowing the difference helps you spot how these tools are working in your kid’s life.

That endless scroll of perfectly tailored videos? That’s the algorithm at work.
That math game that gets harder as your child improves? Machine learning.
That chatbot that tells bedtime stories? AI.

Each layer brings new opportunities and new things to watch out for, like how data is being used, what kinds of content are being recommended or whether your child understands that a chatbot isn’t actually their new best friend.

AI, machine learning and algorithms aren’t just techie terms, they’re shaping the digital spaces our kids are growing up in. The more we understand how they work (and where they sometimes go wrong), the more confident we’ll feel guiding our families through them.

‍