All About AI

Senior Division Curriculum All About AI
  • Learn the basics of how artificial intelligence works

These are the activities for this lesson:

HOW DOES AI WORK?

Earlier, you learned how artificial intelligence is being used in different areas to make an extraordinary impact on our daily lives. Let’s go a little deeper into what it is and how it works.

True artificial intelligence is not quite here yet. There doesn’t yet exist a system that completely thinks and acts like a human. When we think of AI in our everyday lives, we are really thinking about machine learning. 

When we talk about AI in this curriculum, we’ll really be talking about two subsets of Artificial Intelligence, Machine Learning and Generative AI.

What are they?

face recognition

Machine Learning

is a subset of AI where a machine (computer) "learns" to identify patterns so it can make predictions.

That's how Youtube can predict the next video you might like to watch, or Facebook can identify your face in an image.

generated girl with robot

Generative AI

can generate text, images, and sounds. It uses Large Language Models to be able to create content based on lots and lots of existing data. 

ChatGPT and DALL-E are current popular examples of generative AI.

Let’s dive deeper into Machine Learning.

MACHINE LEARNING HAS THREE MAIN PARTS

DATASET

FINDS PATTERNS WITH LEARNING ALGORITHM


PREDICTION!

Source: “Learning about Artificial Intelligence: A hub of MIT resources for K-12 students”, MIT Media Lab

DATASETS

  • AI needs a LOT of data to learn from.  AI uses a dataset, which is just a very large set of data! In today’s world, computers can access more data than ever before. That’s one reason AI has made such huge advances in the past few years.

AI:

  1. learns from the data
  2. and eventually can find patterns on its own
  3. when it takes in new data
    • it can make a prediction
    • based on the patterns.

STOP AND DISCUSS

Where does AI get its data? Well, it gets a lot from you and me.

In your household, what sorts of data do you create every day through technology?

See some ideas
Did you think of any of these?
  • Every Google search
  • Words you type into emails
  • Every question you ask Alexa/Siri/OK Google
  • Connected devices - each time you turn on lights, turn on air conditioning or heat
  • Taps you make on your cell phone
  • Anything you purchase online
  • Who you are connected to on social media
  • Songs you listen to
  • Steps you take
girls discussing

AN EXAMPLE

Let’s step through how Google Maps uses AI to give you directions to where you want to go. Hover over each box to reveal how Google Maps addresses each part.

DATASET

DATASET

Google Maps takes the following inputs to make a prediction.
  • current location
  • destination
  • mode (walk, car, public transport)
  • traffic

FINDS PATTERNS

FINDS PATTERNS

Google Maps is constantly learning from people who use Google Maps. That data are fed into the learning algorithm so that Google Maps can continue to improve upon its predictions

MAKES PREDICTION

MAKES PREDICTION

Based on its current knowledge, Google Maps predicts the best route for you to take to your destination. It might give you different options. When you choose one, it continues to learn from your choice

STOP AND DISCUSS

Now you try it!

Step through the process with Youtube.

  1. What is the dataset?
  2. How does Youtube learn?
  3. What does it predict?

 

ACTIVITY: AI IN ACTION

Estimated time: 15 minutes

Explore some of the websites below to get a taste of what AI can do.

As you explore, consider:
  • Could you take the concept in front of you and apply it in a different context?
  • What sort of data do you think is needed to make these applications work?
Instrument Playground - based on an image, AI generates what it believes you would hear if you were actually there.
AutoDraw - takes your doodling and predicts what it is you’re trying to draw, very quickly!
X Degrees of separation - takes two art pieces and shows us a bridge of similar artworks that connects the two together.

REFLECTION

Now that you have a glimpse of what it takes to create artificial intelligence, you might want to think about the problem you are solving, and how AI might be useful.

Sunset and reflection over lake
Can you think about your problem and possible solution in terms of the three parts of AI - data, pattern, prediction?
How would you address all three parts in your solution?

REVIEW OF KEY TERMS

  • Artificial Intelligence (AI) – machines/programming that can do tasks normally thought to be done only by humans
  • Machine Learning – the subset of AI where a technology is trained with data and “learns” to recognize patterns in order to make predictions
  • Generative AI – technology that has the ability to create content like text, images, and and sound
  • Large Language Model – an AI model that predicts and generates text, trained using enormous amounts of data
  • Datasets – information that is used to teach AI to recognize patterns and predict something
  •  

ADDITIONAL RESOURCES

Want to explore some more cool AI?

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