MY OPINION ON AI AND HOW I THINK IT SHOULD BE USED. IT IS A WONDERFUL TOOL IF USED CORRECTLY.

MY OPINION ON AI AND HOW I THINK IT SHOULD BE USED. IT IS A WONDERFUL TOOL IF USED CORRECTLY.

AI has come a long way since the modern idea of it began in 1950, when Alan Turing published “Computing Machinery and Intelligence.” In that paper, he introduced what we now call the Turing Test — a way to evaluate whether a machine can show intelligence that looks human.

From there, the timeline continued to grow. In 1952, Arthur Samuel began developing a checkers program on the IBM 701, and it later became one of the earliest examples of a computer system that could learn from experience. In 1956, AI officially became its own field of study through the Dartmouth Summer Research Project on Artificial Intelligence, often considered the founding event of AI as a discipline. Organizers and participants included major names like John McCarthy, Marvin Minsky, Claude Shannon, and others — people who believed machines could eventually simulate aspects of human intelligence.

During the 1950s and 1960s, early AI heavily focused on logic and rules — systems designed to reason step-by-step, almost like formal math. One famous milestone was the Logic Theorist, created by Allen Newell, Herbert Simon, and Cliff Shaw, which proved mathematical theorems using symbolic reasoning.

Before we jump into opinions about whether AI is “good” or “bad,” it helps to understand what AI actually is and what it’s designed to do. A lot of the fear and confusion around AI comes from people assuming it works like a human brain — or worse, believing it’s some kind of all-knowing truth machine. The reality is much simpler: AI is a tool built to process information and generate outputs based on patterns. Once you understand how it works, it becomes easier to use it wisely instead of blindly trusting it.

What makes AI especially interesting is how many ways it can be used. Most people today have seen both the good and the bad… but honestly, it often feels like the bad gets the spotlight more than the good.

But like any tool, AI depends on how you use it.

Personally, I use it to help me break down topics I don’t understand — especially when Google searches throw a hundred categories at me and still don’t clearly answer my question. With Google, it helps a LOT if you already know exactly what you’re looking for… because if you don’t, you can get lost fast.

Now, yes — AI can give false information. And if you don’t word a question clearly, it can misunderstand what you mean. But AI was built by humans, and humans don’t always think of the thousand different ways to ask a question.

For example: • “What is a crane?” → Are we talking about the bird or the construction machine? • “What is a condor?” → Are we talking about the bird or the jet plane?

So how you phrase your question or request is one of the biggest keys to getting the answer you’re actually looking for.

So there are two main ways AI works today. One is communicative (like ChatGPT), and the other is more research-driven (like Google’s Gemini, Facebook’s Meta, and Microsoft’s Copilot). So what makes them different?

ChatGPT (Conversational AI) — The most popular one by far.

ChatGPT is what’s called a language model. It doesn’t “think” like a human thinks, and it usually doesn’t search the internet in real time (unless it’s using a browsing feature).

Instead, it does something that sounds simple but is insanely powerful:

It predicts language.

The Simplest Explanation

ChatGPT works like a super-autocomplete.

When you type a question, it looks at your words and predicts: “What is the most likely helpful response someone would say next?”

It generates a reply word-by-word, kind of like how your phone guesses the next word… except ChatGPT can do it with: • Paragraphs • Explanations • Step-by-step teaching • Conversations • Storytelling

Why does it sound like a real person then?

Because it was trained on massive amounts of human writing: • Conversations • Books • Articles • Tutorials • Explanations • Arguments • Essays

So it learned the patterns of how humans talk. Not emotions. Not real understanding. But it learned the shape of communication REALLY well.

The Important Warning

Since ChatGPT predicts what “sounds right,” it can sometimes give: • Outdated info • Incorrect details • Made-up answers that sound confident

That’s called hallucination, and it’s why phrasing matters so much.

Researcher AIs — Google Gemini, Facebook Meta, and Microsoft Copilot

Now this is the part where people get messed up between the two AIs.

Some AIs don’t just “predict text.” They also do something called:

Retrieval — searching or pulling sources.

So they’re mostly a hybrid:

Searcher AI = Chatbot brain + Search Engine

Searcher AI does two jobs:

1. It talks like ChatGPT
2. It searches the web (or pulls from its connected data sources)

So when you ask something, it can: • Pull info from live websites • Quote sources • Show links • Summarize fresh information

This makes it better for: • Current events • Breaking news • “What’s the latest?” • Prices, availability, recent updates • Stuff that changes all the time

What it’s really doing

Instead of guessing purely from training, it does:

1. Search — collects results
2. Extracts the most relevant info
3. Then writes an answer based on those sources

So it’s closer to: “Let me look that up, then explain it to you.”

But search AI has weaknesses too

Even if it uses web searching, it can still: • Misread a source • Pull from a bad source • Summarize wrong • Combine two sources incorrectly • Or confidently misunderstand what it found

So it’s not “perfect truth,” just better at being up-to-date.

The Best Way to Explain It

If ChatGPT-style AI is like: A genius student who read millions of books already…

Then searcher AI is like: That genius student… but with a phone in their hand Googling things live while answering you.

Both can be smart and wrong, but they’re smart in different ways.

So now that we know how it works, the next question is: how is it “smart”?

The simple truth:

AI is “smart” because it is excellent at recognizing patterns.

Not because it has: • Common sense • Life experience • Real understanding • Emotions • Intuition

It doesn’t know things like a person knows things. It learns patterns from huge amounts of examples.

In other words, the AI reads your input in a fraction of a second and rearranges the puzzle pieces in different ways to see what fits best in this conversation.

Or you can think of it like this:

If you read 10 books, you’ll notice patterns in how the stories work. But if you read 10,000 books, you’ll notice deep patterns like: • How people argue • How explanations are usually written • How jokes are structured • How certain questions are answered • What words usually go together

Now imagine reading millions of books, conversations, and articles. That’s what AI training is like.

The three ingredients that make AI “seem” smart

1. Training data

AI is trained on massive amounts of text. That’s where it learns: • Grammar • Sentence structure • Tone • Facts (some true, some outdated) • Common ways humans explain things

So it becomes very good at talking like a human.

2. Pattern learning (the secret)

During training, it learns: • What words usually appear together • Which ideas are usually connected • What a “good answer” tends to look like • How different topics are explained

So later, when you type something, it can continue the pattern.

It’s like: “I’ve seen millions of examples like this, so I know what usually comes next.”

3. Prediction (how it generates answers)

When you ask a question, AI is basically doing this: “Given these words… what words are most likely to be correct or helpful next?”

It chooses the next word based on probability. That’s why AI can: • Write essays • Summarize • Teach • Brainstorm • Translate • Hold conversations

All by predicting language.

Why it can still be wrong

AI doesn’t “check reality.” It checks what sounds likely.

So if it doesn’t know… it might still generate something that sounds correct. And that’s why hallucinations happen.

AI is like a human who’s done a million practice tests. They may not understand the topic deeply like a professor… but they’ve seen so many examples that they can usually guess the right answer.

Most of the time they’re right, but sometimes they’re confidently wrong.

Conclusion

AI is a great tool if used correctly.

The reason people need to stop using AI so horribly is because some people can’t tell what’s real and what’s not — and it can hurt others.

Use AI to understand the article you’re reading better. Use it to “help” write a school paper.

But don’t sit there and let it write everything for you. That’s pure laziness — and I can understand why teachers think it’s a horrible tool.

Use AI to grow your learning, not damage it. If you aren’t understanding the assignment (no matter what it is), then rethink it. Let AI “guide” you, but learn the material.

Thanks for reading. I hope you have a wonderful day, and please respect all tools no matter what they are. Tools are made to assist — not to cheat.