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2. Choose a Category and Search for Images

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In this video, you will pretend that you are training a computer to recognize a certain category of items.

Computers learn based on the data they receive.

That’s why it’s so important that the information machines train with is fair and inclusive.

The first step in creating your machine training data is to select a category.

Then, you will select images to teach a computer to recognize it.

To do this, it’s important to select images that represent “everything” in the category.

You could choose: Birds, Clocks, String instruments, Houses, Shoes, Spoons, Or telephones.

Then, open a new browser window, and go to Google Drive.

Open your machine learning journal, if you have one, or create a new document.

Add a heading that says Fairness in Machine Learning Reflection.

Add a subhead with the name of the type of item you selected.

Now, brainstorm five images that will represent “everything” in your category.

When you have an idea of the first image you’d like to include, insert it into your document.

Use the option to “search the web.”

Then, type a description of the image you want.

When you find one you like, insert it.

Make sure you have the right to use the image.

Adjust the size if you like.

To keep the image proportional, hold down the shift key while you drag one of the corner handles.

Continue searching the web for images in your category until you have added five to your document.

Great job!

Now, it’s your turn: Select a category of items from the list.

Search the web for five images of things that represent everything in your category And insert them into your document.


  1. Select a category of items from the list.
  2. Search the web for five images of things that represent everything in your category.
  3. Insert them into your document.