Coby Reynolds explores why we should teach AI and Machine Learning and provides a list of practical examples for use in the classroom.

What is AI and Machine Learning?

For many of us, Artificial Intelligence (AI) and Machine Learning (ML) provide some nostalgia back to the Skynet taking over human civilization or the rise of self-aware robots that look like Will Smith. And for many years, Hollywood has dramatized AI and painted a scary perception of the possibilities of what this type of technology can become – but luckily for us this is still somewhat a pipe dream.

That being said, this does not mean that AI isn’t already all around us. To put it simply, Artificial Intelligence is a sequence of algorithms (code) that run repeatedly aiming to predict and complete complex tasks in the matter of seconds. Additionally, Machine Learning is the data set(s) and information being collected which allows a large majority of AI technology to function. For example, personally curated playlists on Spotify, global trending tweets on Twitter, or even stock market transactions are all extremely complex tasks that would be merely impossible for humans to do, let alone in a timely manner, hence the increased reliance on AI and ML.

All of this data is collated by using a range of sequenced algorithms that learn from one’s online interaction. Take those ‘I’m not a Robot’ tests – where it asks you to ‘Click all the traffic lights’. While some people either find these fun or super annoying, is a prime example of humans providing ML data to AI technology; the more data, the more precise it can be. Some other examples are ‘Recommended Videos on YouTube, Popup Ads, Chat Bots on websites or simply agreeing to the ‘Terms and Conditions’ when registering for accounts – all things our students do on a daily basis.

What does this mean for students?

To place this into a more relatable context, educators are beginning to see the educational cognitive affordance that coding has on student learning. I am not saying that all students need to be able to code an AI algorithm, but understanding the basics of how it works and its impact on society right now is extremely important. More and more our students are spending countless hours online and using technology devices connected to the internet (IoT devices). All of these online interactions are feeding huge data sets of ML at incredible speeds. What they watch on YouTube, search on Google, permissions they allow when registering for popular social media sites are all examples of how ML collates uses data.

More recently the impact of the General Data Protection Regulation (G.D.P.R.) has seen many companies rethink the types and amount of data being collected and what they actually do with it. This places data protection and the ethics of the collection regarding AI into the spotlight for us as educators. So how do we ensure our students are aware of this type of technology and how to protect their personal data and information?

Where do I start?

For many adults, this concept is difficult to grasp. So teaching it to students as young as 7 or 8 years old is seemingly impossible without some relatability and context. Below I have curated a shortlist of basic tools and resources to support teachers in better unpacking a not-so-easy topic for students and teachers alike.

Hello Ruby ‘Love Letters to Computers’ – https://www.helloruby.com/loveletters

A fantastic ‘child-friendly’ resource for teachers to use and/or print. The Hello Ruby book series is also a great resource for teaching all digital technology resources. Some of my favorites are the ‘reCAPTCHA Code’ and ‘Build your own Robot’ activities from the Activity Journal.

Google Quick Draw – quickdraw.withgoogle.com

A fun and exciting AI game created by Google to predict your doodles based on previous data. You can also view hundreds of thousands of other drawings to see how the AI program successfully guessed your somewhat interesting drawing or a ‘flower’.

Machine Learning for Kids – https://machinelearningforkids.co.uk/

If you’ve been using Scratch with your students this is a great resource to expand their knowledge of AI and coding. This tool allows you to create your own AI project to recognize ‘text, images, numbers, or sounds’ through machine learning.

AI4K12 – https://github.com/touretzkyds/ai4k12/wiki

A plethora of online learning materials for teachers to better understand AI as well as ways to use these with students. They have a great mailing list of upcoming webinars and resources.

Moral Machine from MIT – https://www.moralmachine.net/

A tool created by MIT to collate human data based on situational dilemmas that are based on human morals. This famously relates to their study around ethics and AI technology concerning self-driving cars.

Wreck-it Ralph 2 – Ralph Breaks the Internet

Yes, a Disney Film teaching about AI… well not exactly, but there are some great areas of conversation that can be brought up by watching this film.

Still confused?

If, like me, you are a visual learner, here are some great videos to help explain AI and Machine Learning, these are great for the kids too!

Hello Ruby – Episode 09 – AI and Machine Learning

How I am Fighting Bias Algorithms – Joy Buolamwini

How Machines Learn – CPG Grey (YouTube)

Should I be worried about AI taking my job?

Well, not just yet, AI for all its amazing capabilities is still not very good at very basic human tasks. AI is very ‘robotic’ in the way it operates, therefore it is up to humans to provide the right data for it to work its magic. As educators, preparing our students to become better online digital citizens is paramount, which is why AI and ML should be taught as a part of your digital citizenship curriculum. This will equip them with the necessary knowledge and understanding to tackle the complex online world which has become a cornerstone of the 21st Century.