Understand AI. Use it wisely. Shape the future.

Computers sense the world with cameras, microphones and other sensors, then make sense of the signals.

Computers store knowledge in organized data and reason with it to work out new facts.

Machine learning finds patterns in data and uses them to make predictions.

AI that talks with people needs language, context and an understanding of how people communicate.

AI can help or harm. People decide how it is designed and used.

Computer systems doing tasks that usually need human intelligence, like recognizing, predicting, deciding or writing.

Today’s AI is very good at specific tasks but has no general understanding of the world like a person.

If you can’t tell a machine’s answers from a person’s, does it think? A famous test, but passing it doesn’t prove understanding.

A step-by-step set of instructions that a computer follows exactly.

AI has no wishes or feelings. People build it, choose how to use it and are responsible for it.

Facts, numbers, pictures, sounds or text collected for a purpose. AI learns from it.

If training data is wrong, messy or one-sided, the AI’s answers will be too.

In supervised learning, people tag examples with the right answer so the computer can learn from them.

The measurable details a model looks at, like size, color, shape or word counts.

AI spots patterns in past data to make a best guess about something new.

Computers learn from examples instead of being told every rule.

Learn from labeled examples, then label new ones.

Find groups and patterns in data that has no labels.

Learn by trying actions and getting rewards or penalties, like a game score.

Test a model on examples it has never seen to find out if it really learned.

A model that memorizes its training examples fails on new ones, like memorizing answers without understanding.

Layers of simple math ‘neurons’ that adjust their connections as they learn.

A picture is a grid of numbers called pixels. Models learn which pixel patterns mean ‘cat’ or ‘stop sign’.

Sound waves are turned into numbers, then matched to sounds and words.

Cameras, microphones, GPS, radar, lidar and touch sensors give machines their ‘senses’.

AI gives its best guess with a probability. A high score can still be wrong.

Explore possible steps to find a path to a goal, like solving a maze or planning a route.

Smart rules of thumb that make searching much faster.

Break a big problem into smaller problems you can solve one at a time.

A chain of yes-or-no questions that leads to a decision.

Programs that search moves and learn from play beat world champions at chess (1997) and Go (2016).

Models trained on huge amounts of text to predict the next piece of text, which lets them write and answer.

Text is split into small pieces called tokens. A language model predicts one token at a time.

A chatbot can make up facts, quotes or sources that sound real but are not.

People tend to believe a chatbot understands them, even when it is only matching patterns.

Models that create new text, images, audio or video from patterns in their training data.

Realistic but fake AI-made videos, pictures or voices of real people.

Say when and how you used AI, and respect the work of artists and writers.

Before you trust or share something, find out who made it and where it came from.

Give the goal, the context, the format you want and any limits. Then improve and ask again.

Check AI answers against reliable sources, especially facts, numbers, quotes and advice.

Ask AI to explain, quiz you or give feedback, not to do your work for you. Follow your school’s rules.

Never share personal details, passwords or private photos with an AI tool.

When training data or design leaves people out, AI can treat some groups unfairly.

Check how well an AI works for different groups of people before anyone relies on it.

People affected by an AI decision deserve to know how it was made and how to question it.

For important decisions, a responsible person reviews what the AI suggests.

Build and test AI so it does what people intend, without causing harm.

AI changes tasks inside jobs. Creativity, care, judgment and teamwork become even more valuable.

AI can speed up science and help people, such as predicting protein shapes or floods.

A robot senses, decides and acts in the physical world. Not every robot uses AI.

AI tools change fast. Curiosity, math, reading and learning skills last a lifetime.