Req 1 — Key AI Terms

This requirement is your vocabulary boot camp. Before you can build, discuss, or critique AI, you need to speak the language. These 16 terms are the building blocks you will use throughout the rest of this merit badge. Think of them like trail markers — once you know what each one means, you will never feel lost in a conversation about artificial intelligence.

Do not just memorize definitions. Try to think of a real-world example for each term. When you meet with your counselor, connecting a definition to something concrete shows that you truly understand it.

The Core Terms

Artificial Intelligence (AI)

Artificial intelligence is the broad field of computer science focused on building systems that can perform tasks that normally require human intelligence. This includes things like recognizing speech, making decisions, translating languages, and identifying objects in photos. AI does not mean a robot that thinks like a person — it means software that can handle complex tasks by finding patterns in data.

Artificial Intelligence Agents

An AI agent is a system that can perceive its environment, make decisions, and take actions to achieve a goal — often without being told exactly what to do at each step. Think of a self-driving car: it senses the road, decides when to brake or turn, and acts on those decisions in real time. AI agents range from simple (a thermostat that adjusts temperature) to complex (a system that manages an entire warehouse).

Automation

Automation is the use of technology to perform tasks with minimal human involvement. It is important to understand that not all automation is AI. A simple timer that turns your porch light on at sunset is automation — it follows a fixed rule. AI-powered automation can adapt and learn. We will explore this distinction much more in Requirement 3.

Basic Programming

Programming is writing instructions that a computer can follow. These instructions are written in a “programming language” like Python, JavaScript, or Scratch. Basic programming means understanding concepts like giving a computer step-by-step commands, using loops (repeating actions), and making decisions with “if-then” logic. You do not need to be an expert coder for this badge, but understanding the idea that AI systems are ultimately built on code is essential.

Bots

A bot is a software program that runs automated tasks. Chatbots are the most common example — when you visit a website and a chat window pops up asking “How can I help you?”, that is usually a bot. Bots can be simple (following a script of pre-written answers) or AI-powered (understanding your question and generating a unique response). Social media bots can automatically post, like, or share content.

Data

Data is information — numbers, text, images, sounds, measurements, or any other facts that can be collected and stored. Data is the fuel that powers AI. Without data, AI systems have nothing to learn from. When you take a photo, type a message, or click a link, you are creating data.

Databases

A database is an organized collection of data stored electronically. Think of it like a giant, searchable filing cabinet. Your school’s student records are in a database. A streaming service’s library of movies is a database. AI systems query (ask questions of) databases to find the information they need.

Digital Workers

A digital worker is an AI-powered software program that can handle entire business processes — not just a single task. While a bot might answer one question, a digital worker can process an insurance claim from start to finish: reading the form, checking the policy, calculating the amount, and sending the payment. They are sometimes called “virtual employees.”

General AI

General AI (also called Artificial General Intelligence or AGI) is a theoretical type of AI that could understand, learn, and apply intelligence across any task — just like a human. A general AI could write a poem, diagnose an illness, fix a car, and play chess, all with the same system. General AI does not exist yet. Every AI system in use today is narrow AI.

Machine Learning (ML)

Machine learning is a subset of AI where systems improve through experience instead of being explicitly programmed. Instead of writing rules like “if the email contains ‘free money,’ mark it as spam,” you feed the system thousands of examples of spam and non-spam emails, and it figures out the patterns on its own. The more data it processes, the better it gets.

Narrow AI

Narrow AI (also called “weak AI”) is AI designed to do one specific task very well. Your voice assistant, your email spam filter, the facial recognition on your phone — these are all narrow AI. They are extremely capable at their specific job but cannot do anything outside that job. A chess AI cannot drive a car, and a translation AI cannot diagnose a disease.

Superintelligent AI

Superintelligent AI is a hypothetical future AI that would surpass human intelligence in every domain — science, creativity, social skills, and everything else. This concept exists mostly in science fiction and philosophical debate. Superintelligent AI does not exist, and many researchers question whether it is even possible. However, thinking about it helps us discuss important questions about safety and control.

Tasks

In the context of AI, a task is a specific action or job that a system is designed to perform. Examples include: classify an image, translate a sentence, recommend a video, detect fraud, or generate a paragraph of text. Most AI systems are built around completing one or a few closely related tasks.

Triggers

A trigger is an event or condition that starts an automated action. When you say “Hey Siri,” that phrase is a trigger — it activates the voice assistant. In workflow automation, a trigger might be “when a new email arrives” or “when a form is submitted.” Triggers are the “starting gun” for automated processes.

Workflows

A workflow is a sequence of steps that accomplish a task from start to finish. In AI and automation, workflows connect triggers, tasks, and decisions into a chain. For example: a customer submits a support request (trigger) → the system reads the request (task) → it routes the request to the right department (decision) → a response is sent (task). Tools like Zapier and Microsoft Power Automate let people build workflows without writing code.

Variables

A variable is a piece of information that can change. In programming, a variable is like a labeled container that holds data — the label stays the same, but the contents can be updated. For example, a variable called temperature might hold the value 72 right now but change to 68 later. AI systems use variables to track inputs, store results, and make decisions.

Putting It All Together

These 16 terms are deeply connected. Data feeds into machine learning systems that power artificial intelligence. An AI agent might use variables and triggers to execute tasks within a workflow. Bots and digital workers are practical applications built on these concepts. And the distinction between narrow AI, general AI, and superintelligent AI helps us understand where the technology is today versus where it might go in the future.