Explore a Topic: Generative AI Introduction

Welcome to Explore a Topic: Generative AI! In this lesson, you will learn by exploring on your own, then by teaching your classmates and even your teacher! This "Explore a Topic" lesson is about artificial intelligence.

"Artificial intelligence," or AI for short, is a type of computer system that identifies patterns in data to make predictions, take actions, or create content.

AI can do lots of different things, such as recommending movies you might enjoy to helping robots recognize objects and pick them up.

You are probably already using AI every day! For example, a type of AI called "generative AI" can create content such as images or text, which can help you with tasks like suggesting words to finish a sentence you're typing on your computer.

Until recently, AI existed only in our imagination and science fiction stories.

However, its origins go back hundreds of years.

In 1842, Ada Lovelace— considered to be the first computer programmer— stated that a computer "can do whatever we know how to order it to perform." In other words, she predicted that computers would one day be able to follow complex instructions provided by humans, which is a core concept in AI.

Beginning in the 1950s, AI started to become a reality thanks to the work of mathematicians and computer scientists like Alan Turing and John McCarthy.

Since then, our technology and computer science knowledge has grown, enabling the development of the AI systems we have today.

AI has become much more common, and it is used in many aspects of our daily lives.

Examples include recommendation systems in entertainment streaming platforms, virtual assistants, facial recognition software, and navigation apps.

AI is able to do things like make predictions and generate content.

"Generative AI," for example, is a type of AI used to create new content, like text, images, music, audio, and videos.

A unique quality of generative AI is that you don't need to be a computer scientist or know any special programming languages to use it— you can use generative AI with natural language.

Natural language refers to the way people talk or write when communicating with one another.

Here's how AI works: First, developers train an AI model on lots of data, or information.

This data provides examples that the model can identify patterns in.

Once the AI model has been trained, the developers incorporate that model into an AI tool for people to use.

People enter input—such as text, speech, images, or video files—into the AI tool, and the tool processes that input.

Finally, the AI tool generates a response— or output—based on the patterns it identified in its training data.

This output might be text, images, audio, or video.

Generative AI tools are easy for anyone to use, and they can help you do lots of things.

For example, generative AI tools can help you complete tasks, answer your questions, and brainstorm ideas with you.

However, while generative AI can help you perform a variety of tasks, it also has some limitations.

For example, generative AI models can't learn on their own.

They need people to regularly retrain them using new data.

Generative AI can also reflect biases.

A "bias" is a prejudice in favor of or against one thing, person, or group compared with another, usually in a way considered to be unfair.

Biases in training data can lead generative AI tools to produce skewed responses that sometimes have unfair impacts on people.

And, since generative AI tools are built by humans and trained on data that sometimes contains mistakes, the tools can make mistakes, too.

People, organizations, and governments are thinking about ways to address these challenges and ensure AI is developed and used responsibly.

As you research your topic, consider how AI tools can be developed and used in ways that are unbiased, safe, and good for society.

Coming up, you'll learn how to choose and explore your topic, organize the information you discover, and present it to your class.

Click "Next" to move on to the next video.