What You Need to Know About AI Tools Like ChatGPT
Ever wonder how ChatGPT works, whether it’s telling you the truth, or how it decides what to say? This page will walk you through the basics of how AI text generators work, their limits, and how to use them responsibly in school and beyond.
What Is AI, Really?
What You Need to Know
Artificial Intelligence (AI) is when a computer system is designed to do tasks that normally require human intelligence. These can include things like:
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Recognizing faces in photos
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Understanding and translating languages
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Recommending your next song on Spotify
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Generating writing or summaries
But AI doesn’t mean one big robot brain that knows everything. There are different types of AI, and most of what we use today is actually pretty focused.
Two Types of AI You Should Know
Narrow AI
This is what powers most AI tools today. It’s designed to do one specific task really well — like transcribing speech or filtering spam emails. Tools like Grammarly, Google Maps, and Siri are all examples of Narrow AI.
General AI
This kind of AI would be more like a human brain — able to think, reason, and learn across many different areas. We’re not there yet. General AI is still mostly science fiction (think C-3PO or Iron Man’s JARVIS).
Other Terms You’ll Hear A Lot
| Term | What It Means |
|---|---|
| Machine Learning | A method where computers learn from data to make predictions or decisions without being explicitly programmed for every step. |
| Large Language Model (LLM) | A kind of AI trained on huge amounts of text from the internet to generate human-like writing. ChatGPT is an example of this. |
| Predictive Text | When your phone or AI suggests the next word you might type — based on past data or patterns. |
Match the Term to Its Definition
Can You Always Trust What AI Says?
Sometimes, tools like ChatGPT generate responses that sound confident and convincing — but are actually wrong. These errors are called AI hallucinations.
Other times, the AI may reflect biases from the data it was trained on, such as outdated gender roles, cultural stereotypes, or Western-centered perspectives. It doesn’t mean the AI is “trying” to be biased — it just mirrors patterns in the data it has seen.
Examples:
1. Hallucinated Citation
“According to a 2017 study published in the Journal of Cognitive Learning, students who used AI tutors improved their grades by 35%.”
What’s wrong?
There is no such journal or study. This citation sounds academic and legitimate, but it’s completely made up by the AI.
2. False Fact (Historical Inaccuracy)
“Steve Jobs invented the internet in 1989 while working at Apple.”
False.
The internet was developed over decades by researchers, and the World Wide Web was created by Tim Berners-Lee in 1989. Steve Jobs had no direct involvement in inventing the internet.
3. Biased Statement
“Nurses are naturally nurturing and empathetic, which is why women are better suited for the job.”
Biased.
This reflects gender stereotypes and ignores the growing number of men and nonbinary people in the nursing field. It assumes certain traits belong only to one gender — which is inaccurate and harmful.
