Digital Citizenship: Ethics and privacy

In the digital world, we can lose control of the information we share. It’s important to respect other people’s privacy and take control of your own.

Privacy Pursuit: The Value of Privacy

In this lesson, students learn how their personal information is key to how most of the “free” apps and platforms they use make money. They learn practical strategies and tools for managing their privacy and plan how these can be used to limit what audiences have access to their personal information.

Managing your privacy when using smart devices

Whether it’s a video doorbell, a speaker with a built-in voice assistant, or even “smart socks” for your baby, these things all have one thing in common: they collect information about you and your family.

How much information they collect, though, is at least partially up to you. Here are some steps you can take to manage your privacy when using smart devices.

Media Literacy Week: Protecting and empowering students in the digital age

Guest blog by Patricia Kosseim, Information and Privacy Commissioner of Ontario  

Privacy impacts of advertising and marketing

One of the oldest adages in marketing is “Half the money I spend on advertising is wasted, but I don’t know which half.” It’s as important for advertisers to reach the right people as it is to make an appealing ad, so they have developed many different ways of targeting ads effectively. Online advertising lets marketers match different ads with individual users. This section looks at how that’s done and how it affects kids’ privacy.

How to Train Your Algorithm

In this lesson, students will learn about algorithms and how they function, particularly recommendation algorithms utilized by popular apps like YouTube, TikTok, Instagram, and Netflix. Students explore the role of optimization goals such as watch time, engagement, and daily active use in shaping the content algorithms prioritize. Through activities like “red teaming,” students will critically analyze the potential downsides and biases of these optimization goals. Students will also discover how to train algorithms by providing both explicit inputs through actions like liking and sharing, and understand the implications of implicit inputs gathered from their online activity. Finally, students design their own algorithm for an app of their choice, identifying which goals it should be optimized for and how they should be weighted as well as what inputs it should use.