AI Jargon Buster: 20 Terms Explained in Plain English

AI comes with a lot of jargon. Terms get thrown around on the news and in conversation as if everyone knows what they mean. Most people don't, and that's completely fine.

Here are 20 AI terms explained in plain English. No technical background needed. Just straightforward definitions you can actually use.

1. Algorithm

A set of instructions that tells a computer what to do. Think of it like a recipe. A recipe tells you to chop onions, heat oil, fry the onions. An algorithm tells a computer to take data, process it in a certain way, and give you a result. Every piece of software runs on algorithms. They're not mysterious, they're just instructions.

2. Artificial Intelligence (AI)

The broad term for computer systems that can do things which normally require human intelligence. Things like understanding speech, recognising faces, making decisions, and learning from experience. It's a wide category. Your email spam filter is AI. So is ChatGPT. So is the system that recommends films on Netflix.

3. Machine Learning

A type of AI where the computer learns from examples rather than being told exactly what to do. Instead of programming "if the email contains 'Nigerian prince,' mark it as spam," you show the computer thousands of spam emails and let it figure out the patterns itself. The more examples it sees, the better it gets.

4. Neural Network

A type of machine learning inspired by how the human brain works. Not literally brain-like (it's still just maths), but it's structured in layers that process information step by step. Neural networks are what power most modern AI, from image recognition to language translation.

5. Deep Learning

Machine learning using neural networks with many layers. The "deep" just means there are lots of layers stacked on top of each other. More layers generally means the system can learn more complex patterns. Deep learning is behind most of the impressive AI you see today.

6. Large Language Model (LLM)

The technology behind tools like ChatGPT. An LLM is trained on billions of words from books, websites, and articles. It learns patterns in how language works, and then it can generate new text that reads naturally. It doesn't "understand" language the way you do. It predicts what word should come next based on everything it's learned.

7. Generative AI

AI that creates new content. Text, images, music, video. ChatGPT generates text. DALL-E generates images. These tools don't copy existing content directly. They create something new based on patterns learned from training data. Whether what they create is genuinely "creative" is a debate people are still having.

8. Prompt

The question or instruction you give to an AI tool. When you type "Write me a poem about autumn" into ChatGPT, that's a prompt. The better your prompt (more specific, more detailed), the better the output tends to be. "Write a funny limerick about a cat who hates Mondays" will get you a better result than "write a poem."

9. Chatbot

A programme that has text conversations with you. Some chatbots are simple and follow scripts (like the one on your bank's website). Others use AI to have more flexible conversations (like ChatGPT). They range from helpful to frustrating, depending on how well they're built.

10. Hallucination

When an AI confidently says something that's completely wrong. ChatGPT might tell you that a book exists when it doesn't, or give you a historical "fact" it's made up. It's called a hallucination because the AI isn't lying on purpose. It's generating text that sounds plausible but happens to be wrong. Always check important facts independently.

11. Training Data

The information used to teach an AI system. For ChatGPT, the training data was enormous amounts of text from the internet: books, articles, websites, forums. The quality and breadth of training data affects how good the AI is. Rubbish in, rubbish out, as the saying goes.

12. Deepfake

A photo, video, or audio clip that's been created or altered by AI to look or sound like a real person. The technology can make it look like someone said or did something they never did. Used for entertainment sometimes, but also for scams and misinformation. We've written a whole article on how to spot deepfakes if you want to know more.

13. Natural Language Processing (NLP)

The branch of AI that deals with understanding and generating human language. When you ask Siri a question and she understands it, that's NLP. When Google translates a website from French to English, that's NLP too. It's what makes it possible for you to talk to computers in normal sentences instead of code.

14. Bias

When an AI system produces unfair or skewed results because of problems in its training data. If an AI learned from data that mostly featured one type of person, it might not work as well for others. For example, facial recognition systems have historically been less accurate at identifying people with darker skin tones. Fixing bias is one of the biggest challenges in AI development.

15. Automation

Using technology to do tasks without human involvement. A dishwasher automates washing up. A thermostat automates temperature control. In the AI context, automation usually means using AI to handle repetitive tasks like sorting emails, processing forms, or managing schedules.

16. Bot

Short for robot, but in the digital sense. A bot is a programme that does automated tasks online. Some bots are helpful (search engine bots that index websites). Others are annoying (spam bots that post rubbish on social media). A chatbot is a specific type of bot designed for conversation.

17. Cloud Computing

Storing and processing data on remote servers (someone else's computers) rather than on your own device. When you use ChatGPT, the processing happens on OpenAI's servers, not on your phone or laptop. "The cloud" is just a friendly term for "other people's computers connected via the internet."

18. Data Privacy

Your right to control what information about you is collected, stored, and used. In the UK, this is protected by laws like GDPR and the Data Protection Act 2018. When you use AI tools, your data (what you type, how you use the tool) may be collected. Understanding privacy policies and settings helps you stay in control.

19. Open Source

Software whose code is publicly available for anyone to use, modify, and share. Some AI systems are open source, meaning anyone can examine how they work and build upon them. Others are proprietary (owned by a company and kept secret). Open source AI tends to be more transparent, which some people prefer.

20. AGI (Artificial General Intelligence)

A hypothetical future AI that could do any intellectual task a human can do. Current AI is "narrow," meaning it's good at specific things but can't generalise. ChatGPT can write essays but can't drive a car. AGI would be able to do both, and everything else. It doesn't exist yet, and there's serious debate about whether and when it will. You'll hear it mentioned a lot in news stories about AI's future.

Still Confused?

Don't worry. You don't need to memorise all of these to use AI. Just bookmark this page and come back when you encounter a term you don't recognise. Language evolves, and new terms pop up regularly, but these 20 cover most of what you'll come across in everyday reading and conversation.

For a deeper look at any of these topics, explore our full glossary page or start with our plain English guide to what AI actually is.