Recently I was asked to talk about computers and artificial intelligence to year 5 and 6 primary school kids (i.e. ages 9-11). I’ve spent a lot of time explaining AI and ML to a range of different people, but never to such a young audience! I couldn’t find much inspiration online so came up with my own material. Here’s the outline of my lesson plan which had me spending 30 minutes with each class.

1. Introduction
My day job involves voice recognition, so I start by introducing myself and asking the class how many of them had ever talked to a computer or a device before to get something done – normally I get the majority of the class putting their hand up.

For some context, I include a bit of history. Primary school children have grown up around smartphones and voice computing and often don’t know how fast technology moves. At the time of writing, the Y5 class was born in 2008/2009. For comparison, the iPhone was launched in 2008 and Siri was released on it in 2011.

2. Computer Programming
The first discussion topic is how computers are programmed to do things by writing rules (or programs). It’s possible to write very complicated and seemingly intelligent computer programs this way. By Y5 and 6, the children in this school have had lessons programming using scratch. They understand how you make computer programs from instructions, and how it’s easy to get those instructions wrong so the computer doesn’t do what you meant it to.

3. Rules to identify cats
People like to share photos on the internet, and they share a lot of photos of cats! One thing that might make a computer artificially intelligent is being able to say whether a photo is of a cat or not. I brainstorm with the class for some rules to write on the board that we could use for identifying a cat in a picture. Some of the rules we’ve come up with in previous sessions are:

• Has a tail

• Is furry

• Is cute, makes people go ‘awww’

• Has whiskers

• Has eyes

• Is an animal

These aren’t rules that we can directly implement in a computer, but they get the idea across.

Next we go through a slide deck of pictures playing ‘cat or not’. My slides have a range of pictures – some are easy to identify as cats or not, some are cats which are obscured or in funny poses, and some are other animals which have some of the same features as cats. They get the children thinking about how to define the task (do big cats count as cats or not?), edge cases (what about the drawing of a cat?) and the kind of rule you really need (how exactly do you distinguish a red panda from a cat?).

4. Intelligent computers
After this, I ask if the kids thought the rules we had were good or not. Most acknowledge that our rules don’t cover all the pictures and so could have been better.

Some tasks, like seeing and hearing, are impossible to write rules for that a computer can follow. We need a different method. Instead of writing rules, we have a computer learn how to do the task from data. To do this we take a lot of data (images, audio, video etc.) and have people label it. For images the people might label each image what object is depicted. From this database of ‘labelled data’, we can train a machine to learn the patterns of what makes a picture of a cat or not. Once the computer has learnt from this training data, we can take the model that the computer builds and use it to identify cats in pictures it’s never seen before.

Identifying cats or other objects in pictures might seem frivolous, but there are lots of ways you can use this technology in the real world. One example which a lot of people are working on is to identify what is in front of you in a self-driving car. Another is helping to save endangered wildlife by identifying animals and counting them in the wild.

5. Discussion and Questions
I finish with a discussion about what kind of smart robots the class would build in the future. Where I know anything about their suggestions, I’ll talk about what’s being already built in that area.

Examples of ideas I’ve heard include:

• Computers that help blind people: examples include Microsoft’s Seeing AI or text-to-speech technology which can read text aloud

• Space travel: we have sent men to the moon and rovers to Mars already, but AI can help us explore further e.g. rover navigation or identifying objects in space,

• Looking after people in hospital: there are many ways computers can help in hospitalsfrom surgery to diagnosis to doing admin and so freeing up the time of doctors and nurses to spend with patients.

• A robot that can cook: the sort of robotics needed to handle ingredients is tough to build, but there are examples

• A computer that does homework. I don’t normally point out that voice assistants like Alexa can already answer a lot of questions

When I ask the class teacher, they usually just want an intelligent computer to help them with marking homework!

There are a few other discussion points I add into the discussion:

• Computers aren’t always right. When computers learn from data, we always know they’ll make some mistakes.

• Some things are not possible for computers to do, e.g. tell if someone is lying. In general if it’s hard for a person to do, it’s also hard for a machine to learn.

• There are bad uses of technology as well as good ones. Sometimes people in the class come up with ideas that others find creepy, which helps illustrate the point.

Extra background
For those who are interested to know more, image recognition has a long history and had been well researched over recent years. One database of images, called ImageNet, has been the basis of much academic research on object recognition. This database has several million images in more than 20,000 categories.

In 2012, it took 16000 computers to learn how to identify a cat. In recent years, researchers have also looked at harder tasks like distinguishing between 5000 species of animal, identifying and tracking objects in video or automatically creating in-depth descriptions of what is happening in a photo.

For some practical exercises in Scratch, you can visit Dale Lane’s https://machinelearningforkids.co.uk.