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Intelligence, but the Artificial Kind (Grade 6)

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Intelligence, but the Artificial Kind
by Archika Dogra

“Alexa, what’s the weather today?”

No, this isn’t your average weather small talk. This is a question that many of us will ask in our lifetimes, and not just to another person, but to a device.

Whether you’re saying “Hey!” to Alexa, Google, or Siri, the names are all facades for the one term that binds them all together: artificial intelligence, or AI.

AI is a field within computer science, using computers to solve complex problems by modeling the same way humans and animals learn. Whether it’s asking your phone a question, when Google auto-completes your search, or when your car alerts you that you’re awfully close to an object, these are all examples of AI making decisions based on how it understands humans and the world.

So, what is the difference between computer science and artificial intelligence? How do we train AI the same way we train our own brains?

Computer science began with algorithms, which are just a step-by-step list of directions written in English and converted to a language that computers can understand (0s and 1s, or numbers). For example, when you use a recipe to cook pasta, that is an algorithm. However, what happens if the recipe you’re using says that the proportions it uses is intended to feed four people, but you need to feed eight? Well, most of us would just think “Easy! We’ll just make double of everything the recipe asks for.” Give a computer this same task and they wouldn’t be able to make that inference.

That’s where artificial intelligence kicks in. AI is when computers take in a lot of data and learn to make rules for itself, rather than you telling it a lot of rigid rules. In this way, the computer learns by adapting.

Let’s compare training AI to training your dog. In this example, you are trying to train your dog to “stay.” In the same way, let’s say you’re trying to train your AI to say “Hello!” back to you when you greet it.

To train your dog, you’d first teach it “stay” somewhere in your house with little distractions. Every time your dog doesn’t move, you give her a treat. You can’t just have her stay once and assume that she understands, you have to do it over and over again, rewarding her for the right response. Then you take her on a busy street with people walking around and say “stay.” She doesn’t. It’s a new environment with more distractions and unfamiliar smells. So, you have to incorporate distractions into your training at home - different noises, movements, and smells - so that she is more confident in listening to you outside.

AI works in the same way, by feeding it data. The AI can’t just be trained on you saying “Hello!” once. It has to be trained on different tones, types of greetings (hello, hey, hi), and with background noise (the dishwasher, music, other people talking). Just like how you need to train a dog many, many times for them to master how to “stay,” they same goes for AI. Once it learns this, it will start to adapt its listening to include more ways that you could be greeting it. It’s always observing and learning.

As people, how can AI positively affect the world? AI can help in almost every field. On Twitter, AI robots monitor when people are saying misleading or offensive things. In your car system, AI learns to detect what objects close by look like to warn you from crashing into them. Even when you’re shopping, AI can recommend new things to purchase based on the data it has collected about your preferences.

However, we need to be very careful how we use AI. The misguided training of AI can lead to racial bias, inappropriate responses, or safety concerns. The quality of AI is based on the quality of the data we feed it. If in the right hands, the opportunities are boundless.
1. 
How is AI different from other conventional forms of computer science?
  1. AI uses algorithms while other forms of computer science don't.
  2. AI can complete household tasks like baking a cake while other forms of computer science can't.
  3. AI can adapt the rules while other forms of computer science follow rigid rules.
  4. AI and conventional forms of computer science are the same.
2. 
AI needs to be trained on                            of                            for effective outputs.
  1. lots, algorithms
  2. a small amount, algorithms
  3. lots, data
  4. a small amount, data
3. 
AI is responsible for constantly improving which machine's performance?
  1. the wheels on your car
  2. an oven in your kitchen
  3. the lights in your home
  4. a voice recognition device
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