Matthew Johnson, Director of Education for MediaSmarts

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Welcome to a very special episode of AI, a podcast about artificial intelligence in the Canadian education system. I am your host, Ryan Oliver, the chief executive officer of Empire, and I am not joined today by my co-host Melissa Sariffodeen, as she is away on assignment. We need to take this episode out though right away. So I'm recording this episode today by myself, and I have a great guest today and a really interesting conversation.

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My guest today is Matthew Johnson from the Canadian organization Media Smarts. You can see them at Media Smarts. We talk in depth about misinformation, and our teachers can help students build critical thinking skills to recognize deepfakes, fake information, and keep themselves safe in a digital world. We are going to jump right into that. But for our first and most favorite segment, one real, one artificial, I did want to touch on old Canadian advertising campaign, but media smarts.

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I found out through this interview has taken over. They relaunched it and brought it back into the classroom in 2019. And so I just want to touch base on it. It is a very effective campaign, and it is one that we, that we talk quite a bit about and is still pretty useful today. So for Canadians of a certain age, the House hippo may be a familiar term or an old ad, you may remember.

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This is the original ad campaign from May of 1999. It's nighttime in a kitchen just like yours. All is quiet. Or is it? The North American house? Hippo is found throughout Canada and the eastern United States. The house hippos are very timid creatures and are rarely seen. But they will defend their territory from the boat. They come out at night to search for food and water and materials for their nests.

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The favorite foods of the house hippo are chips, raisins, and the crumbs from peanut butter on toast. They build their nests in bedroom closets using lost pins, dryer lint, and bits of string. Nests have to be very soft and warm. Hippos sleep alone 16 hours a day. That looked really real. But you knew it couldn't be true, didn't you?

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That's why it's good to think about what you're watching on TV and ask questions. Kind of like you just did. A message from concerned children's advertisers. So originally developed by the concerned children's advertisers, the House Hippo ad was taken over and, the house hippo with the concept, the mascot you could even call it was taken over and reintroduced by Media Smarts, our guest organization, in 2019 as a part of a campaign called Beat the Fake.

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You can still find that, resource online. It is as much a lesson plan as it is just a general tool for both, teachers and just the general public alike. All the all of these things, both the, media smarts promotional campaign as well as the concerned children's advertisers original ad in 1999, they were all happening before the mass introduction of large language models and deep fakes as we know and understand them today.

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When I think of deepfakes, I always go back to the original deepfake that got me, that image as as kind of ChatGPT it was just really started to take off in the public consciousness. There's that image of Pope Francis and a Balenciaga jacket. It was, it was an incredible image. If you haven't seen it, just search.

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Just search that. It's an easy one to find. Because I sound like, much like the house hippo, it was an image that I just really wanted to be real. This really cool pope having this walk in this jacket. In this interview, Matthew and I touched on the house hippo idea, so I wanted to start the episode with an introduction to those that may be unfamiliar with the elusive North American mammal.

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And as a reminder, for all of us, that many of the issues that we are dealing with today have been around for a very long time. There are different, often better tools to create deepfakes, but often the skills needed to recognize them remain exactly the same. The introduction of AI. It doesn't necessarily need a wholesale rethinking of how we teach children critical thinking and logical thinking.

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The scientific method. These are all just really important tools, to continue to learn, to continue to work the muscles of, both in recognizing AI, but in everything we do. But in terms of recognizing AI, they're they're just as important to interacting with it, in a healthy way as they are in, in keeping yourself safe around it.

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So with that in mind, let's get to the interview.

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Matthew, thanks so much for joining. I want to just to start, you mind introducing us to to media smarts. The organization you work with. Yeah. So media smarts. We're actually celebrating our 30th anniversary, this year in 2026. And for that time, we've been Canada's Center for digital media literacy, with a mission to ensure that all Canadians, but with a particular focus on young Canadians and the people who support them in their lives, like parents and teachers, have the critical thinking skills and the ethical decision making skills they need to understand and actively engage with media of all kinds.

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And of course, over those 30 years, the kinds of media that we've engaged with, the ways that people use media have changed tremendously. The ways that we've provided that support have changed. But we're really probably best known for our many lesson plans that are part of our digital media literacy framework from K to 12. And also the, the workshops and other materials that we deliver to parents and teachers to help support them and help them.

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Provide kids with the support they need. That's right. So 30 years you've gone from from teaching and providing guidance. From, I would assume, television all the way now to like, this age of AI. What's, what does that evolution look like as we get into this moment? Yeah, it's had a number of really big, changes, I guess.

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Three, really. And one was just a few years after the organization was founded with, the the widespread adoption of the internet. Now, some people may be old enough to remember the school net program, which was, in a federal program that got every school in the country connected to the internet. I believe most public libraries as well.

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We were actually involved in that because there was a recognition at the time, that, at the same when you were providing kids with access to a technology, you need to help them use it critically. And ethically. And so that was when we started getting involved in digital literacy as well as media literacy. And then about ten years later, there was the second, big change, which, of course, was the advent of social media, where those ethical issues, and the privacy issues really started coming to the fore, because now people were using media as a tool as much as they were consuming it.

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And where our media was coming from change tremendously. We saw the shift began to happen from having a small number of broadcasters, whether those were TV broadcasters or movie studios or book publishers. The power shifted away from them towards the social networks as network gatekeepers. And our newest change, of course, has been AI, and it's a little bit early to say whether it will turn out to be as big a change as the internet and social media were, but we're certainly seeing that it is already having an impact on everything that we do, from verifying information to privacy to, ethics and consent, to really the fundamentals of learning

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and critical thinking. Yeah, we we started this podcast because we're hearing from teachers so much that they're they don't know how to approach this next era. They don't know what AI is going to do to the classroom. I'm curious, from the conversations you're having, from the way you are directing your lesson plans, what are you hearing and seeing as the biggest ethical issues around artificial intelligence?

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I think the things that teachers are most concerned about are, kind of symptoms in a way of those broader changes that we are seeing, in terms of how AI as an impact on learning, obviously from a teachers perspective, and I say this as someone who is in the classroom when the those first two changes happen, and so you suddenly did have this flood of copy and pasted, essays coming in, so from a teachers perspective, there's no question that the fact that I can automate things that weren't previously possible to automate, is huge.

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It has really, I think, led a lot of teachers to, to feel they have to reevaluate how they assess students. But I think that really is going to turn out to be just the first thing we have to consider, because I think it is pushing us to reconsider for how we learn, and to reconsider how we teach, that we have to go beyond just thinking how we how we assess, but also how can we make effective use of these tools.

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I think there's frequently a mistake, and we've seen it, in the past with technology generally in some cases, with some specific things like Wikipedia, where there's a resistance that lasts much longer than really is justified, you know, to the at this point, when we look at verification, when we look at authenticating information, the people who are professionals, the people who are scholars in this field, all looked at Wikipedia as one of the most essential tools, and I still find myself, trying to convince teachers, to teach students how to use it effectively.

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And I think we may be in a similar moment with AI. Where our initial reaction to it is, preventing us from grappling with how we actually can use it effectively. And I do want to say there are some really legitimate reasons to be skeptical about AI as an industry and the AI tools that we're currently being offered.

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There's no question. You know, I, I've never seen such a concerted push with so much money behind it to get a technology into schools. So that absolutely, I think merits a lot of skepticism. We're already seeing as well the that the, the basic versions of the tools are being degraded so and so that the companies that make them can get us to pay for the paid versions, for the subscription versions.

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So, you know, even if you are new out in front of things and teaching kids how to use and AI effectively, what you taught them six months ago may not be as effective today because, the tool just doesn't work as well unless you're paying for it. So, you know, I don't want to suggest that teachers are wrong to be skeptical about AI, and I certainly am not pushing for, you know, uncritical, adoption of it.

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But I think we know enough about the tools at this point to know that they are tremendously power when they're used effectively. Yeah. It's interesting. I had forgotten about the controversy around Wikipedia. I remember I think Stephen Colbert really helped, push it right with that. He did something with elephants at Wikipedia, and I cannot remember the specifics more.

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I don't know if you do it. You know, it's like. But you're right, Wikipedia is now what was at the time this, this idea of this laughable website because anyone could write anything they wanted in it and we would all believe it now has such a vigorous, vetting system around around referencing that Wikipedia is a is is one of the last sources of truth in a lot of ways, as it's saying.

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Right. And one of the last sources of transparency, and in that way, it's a real contrast to AI, because one of the big challenges with AI is that it is. So, it is so obscure and it's decision making, even if you ask it to explain how it did something, it's not actually explaining to you how it did it.

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It's providing you with its best imitation of someone explaining how something, how they came to a decision. But it's not actually giving you any insight into its workings. But yeah, at the same time, one of the things that has improved Wikipedia tremendously is AI, because there are extremely effective bots that have been trained to recognize what are likely malicious errors, and they correct them almost immediately.

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You know, one of the things that we're known for is the house hippo, the, the North American house hippo. And there is a house hippo. Wikipedia page. And every now and then someone will come and, change it to say that, house hippos are real. And because it's Wikipedia, you can actually look at the edit history.

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It's really one of the only places, anywhere where you can see every single change that has ever been made. It make you can see every single editorial decision that went into it. And what you'll see is that those changes almost never last more than five minutes, because the bots are so effective at recognizing a malicious ad it and they refer to it, and there isn't even the need for, those, those communities of editors that, that you mentioned and those are still tremendously valuable and you're still much more likely to get good information.

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If it's a subject where there is, a good community of editors. So the misinformation on Wikipedia tends to linger in places where there isn't an active community. But once you have a decent quality article, the bots do a really good job of reverting any malicious edits. Now, it's really interesting, the kind of cyclical, ecosystem that that supports both Wikipedia and AI, because I had not heard the side that that there are about supporting Wikipedia.

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The the angle I hear more frequently is that without Wikipedia, AI's brain would be about 20% of what it is right now, right? Or even less like just in that it is. It understands that Wikipedia is such a source of truth. Anyway, it's very interesting. I guess we can jump into and jump over rather to, some of the work that media smarts is done.

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You mentioned there's a whole piece, there's a report you put out or the organization put out called Motives and Methods Building Resilience to Online Misinformation. I wonder if you can walk us through a little bit of that, because I think at the core of what we've been speaking to with artificial intelligence, it is such an issue with social media as we know.

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Is is this idea of like, what's the motivation behind what this is telling me? Right? And, you know, what is what is media smarts is research shown. What's what's that, done to the direction you guys are moving in terms of the way you're talking about these tools? Yeah. So a big part of the the reason behind that, study was to look at our approach to verifying information, which we, presented mostly in our break the fake program.

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And to see whether essentially whether it worked in an AI environment and how well and also we did a little bit of, a closer look than we have in the past at how effective it was with different audiences, different age groups and, the reasoning. So it did have a big qualitative component, where we weren't just giving people verification tasks and testing to see how good they were at them, although we did do that as well.

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But we really wanted to know the, the thinking, process that went into it. And also, of course, what was key was understanding the situations in which they would verify, because it's one thing, to be in a, you know, in a lab or in a classroom, verifying something because that's what you're supposed to be doing. And it's quite another to actually be carrying this out in the real world, in our daily environment.

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So, you know, a number of the findings were really, positive for us, where we did find that even quite a short, intervention, that is to say, a short video in this case that was teaching some of the basics of verifying information. Teaching the approach that is, is sometimes sometimes called lateral reading, which we generally call companion reading, where we're trying to steer people away from focusing on the specific text or the specific claim, and rather turn to other resources that they know are reliable, for instance, Wikipedia, reliable news sources, things like that.

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To look for evidence, of whether or not something is reliable, even quite a short intervention, just, a video about a minute long, had really positive results. We did find that it was not as effective with some audiences. Others, so we did find it actually worked better with older adults, than with young people.

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Which is possible that there was already something, some of a ceiling effect there, that they had had instruction possibly that the older adults hadn't had. But it's also something we're looking at because, of course, we want to make sure that what we do works well with every age group. There were some really other really interesting nuggets we found, for instance, that of the deepfake images, the one that people were most likely to believe was correct was an image of Henry Ford.

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And it seems as though looking at the qualitative data, it seems as though it was just that they were familiar with who he was. And so they were less skeptical. So to a certain extent, when there wasn't anything to trigger those habits of skepticism, they were more likely to accept, deepfake. And of course, we know, today, deepfakes have reached a level of believability, where it's almost always impossible to tell just by looking at them.

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So that does come back to that basic question of motivation, of getting people to be in the habit of verifying something. Part of motivation is trying to make these skills as quick and easy as possible so they can be reflexive. And one of the things that we've found with young people that we've also found in some of our other research is that, they respond really well to being to seeing themselves and being encouraged to see themselves as resources for friends and family.

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We found, for instance, that the young people who felt that friends and family relied on them as a source of information, or sometimes relied on them to verify information, were much more likely to verify it and much more likely to take, effective steps to do that. That's really interesting. We, we have always run a program called Connected Elders where we have youth.

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We've trained that, then go and train their grandparents, essentially. And that's a really that's neat to see. The research backs that up because, it feels like the right thing to do like that, you know, who's who, who's going to listen to more than your own family. Right. That's, Yeah. And I really think that the, the, the pro-social, qualities of teenagers, the desire to contribute positively is something that we really don't, we don't take advantage of enough, either in, within school or within communities that, you know, teenagers really are looking to provide value.

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They're looking to find a place, they're looking to feel good about themselves. And so we have a program, for instance, called the Teen Fact-Checking network, where we actually do have teens, who make terrific, hilarious videos where they investigate things and fact check them. And, you know, we make sure that it's not always, something that turns out to be fake.

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A lot of it are things that maybe seem too good to be true, but actually are real. But what's really important is that they're showing the process and that these are things that show up in their own feeds. And so they're, they are contributing to the discourse. They're contributing to a better internet. Yeah. That's, that's great.

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I, to go back to another thing you said. I'm obsessed with this idea of lateral thinking. I love that term, and I'm going to use that from now on. I think it's it even goes back to, I think in a lot of ways what the the role out of Wikipedia ultimately led to is that, you know, through what Colbert did with it and then ultimately, like where it got to now, it's like this idea that like two checks, I mean, even before that, it goes back to the way to write a good essay, but is just to just to have that lateral thinking process of like, oh, there's there's a footnote to this,

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I can, I can, I can check the sources on this. It's a really great skill to have if I am a teacher, wanting to engage with this with my students, you have the break the fake campaign. What you know, is that something through teachers be googling that. Is that something they can reach out to you? What's that process look like?

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If they want to use any of these resources, there's a bunch of different ways of getting it or resources. It would break the fake. It's a it's a general audience campaign. But we do have lesson plans that use that material. And actually start all the way at kindergarten, where we're really just introducing kids to the idea that, what you see in media, whether the online or other media, isn't necessarily real.

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And, we goes all the way up to high school where they're actually making their own fact checking videos, and they learn those skills in between. But those, those lessons, as well as all the other lessons on that subject and lessons on a whole bunch of other topics that connect in various ways are all part of our digital media literacy framework, which is on our At the Teacher section of our website, Media Smart SQA.

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And of course our sister site had media points here. So that's where we have all of our lessons. In four grade bands. So K to three, 4 to 6, 7 to 8 and 9 to 12 across nine topics that we've identified as the essential subject matter of digital media literacy. And those range from, things like reading media, which is just essential, really understanding how different media communicate and the the tools that media makers have at their disposal.

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There are some things that are really associated with, traditional media literacy, like media representation, which of course is as important now as it ever was. Things like consumer awareness, understanding the business model, all of these different media and how that influences, how they work and then things that are really associated primarily with digital media, things like ethics and empathy, things like privacy and security and making and remixing about actually teaching kids to make, media themselves.

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That's really an that's really, really cool. I, I feel, you know, I feel kind of just very lucky to have an organization like yours to, to do this type of stuff for, for youth. I think it's such a, you know, it's like a it's a blank spot for a lot of parents, and I, it's really useful to have this resource.

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One of things I want to talk to you about is, you know, we've had a lot of guests on this, and often the conversation is especially at a high school level. But high school, college level, because the conversation around AI is, did they really write that essay? It comes down to trust. It comes down to like to those pieces, right?

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That where when you're at that level that's, you know, you are trying to, show you understand the show, you understand. And often that has been done through writing. We've talked a bit about how that probably needs to change moving forward. But what we haven't had a lot of is conversations around the, kind of K to six event.

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And one of the lessons that you wrote is called introducing I. It's a lesson plan for grades 1 to 3. I think this is a neat opportunity to share with elementary school teachers that may otherwise not think this is a conversation that, needs to be have a kids until grade eight or grade nine. What does introducing AI to kids in grade one, two, and three mean?

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What? What kind of stuff should they be taken from it? So really it is about getting across the idea that AI does not think in the way that people do. Because we know that actually kids at that age do interact with a lot of AI tools. They're just not necessarily aware that they're doing it. So there are increasingly physical toys that have AI built into them.

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But also a lot of the apps for young kids today have AI, essentially AI chat bots built in, because it's a lot easier than, you know, programing, a conversation tree or having, you know, a full database of response as, like a Furby would have had, because now you can just get, you can train a chat bot relatively cheaply.

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You can build it into an app. But it is really important that they understand that these things are as much as they may seem almost alive, that they aren't that they think differently. We know that with AI in general, demystification of the process, understanding even just the very basics of how it works is really essential. More so than any other media topic, that we've seen all the way up to adults, that those who have some basic knowledge of how it works, they don't see it as magic, they don't see it as, unopened.

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A black box are likely to use it more critically, but also likely to use it more effectively. And so, first of all, we introduce the idea that, an AI is not conscious, that it is not actually making decisions, that it is essentially kind of like a cartoon character, who's whose words have been written by someone else.

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But then we do look in, in a very concrete way at the idea of how AI makes its decisions by looking for patterns, and that because of that, it can make mistakes that no human would make, and it can make mistakes in ways that aren't obviously mistakes. And what we do with that is initially by looking at, different kinds of balls, like rubber balls, soccer balls, basketballs, looking at how an AI, if you then show that, you know, a volleyball, it would correctly guess that after all those first three kinds of balls bounced the volleyball would bounce.

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But that if you then show that an orange, the AI might guess that incorrectly, that the orange would bounce. And going through that, looking at will, why would it make this decision correctly? But that decision incorrectly helps get at the idea that it made the right decision. In the first case, because it found a pattern that was that doesn't actually mean anything in the real world, which is that they were all round.

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And so when it when you gave it something else that was round that didn't bounce, it guessed incorrectly. But the first time, because it did happen to be round and it did bounce, it guessed incorrectly, but you wouldn't necessarily know it. And we go from that to a really tactile project where kids, find similar patterns. It's a they challenge each other to try to guess what the fourth thing and, pattern is, and then they get to design, a robot called a trash bot where they try to think of how they could train by providing examples and providing feedback.

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A robot that would pick up trash in the classroom but only pick up trash. And it really is a fun, creative experience. Of course they get to do other things, they get to draw it, and they get to do some other things that, to make it a more tactile, physical, kinesthetic experience. But it really is a good basic, very practical introduction to how eyes work and how fundamentally how they work in ways that people don't, which can let them do things that are difficult for people but easy for eyes, but also sometimes may lead them to make mistakes that no human would ever make.

00;31;12;26 - 00;31;38;11
That's very neat. That's that's fantastic. So yeah, there's there are decent amount of lesson plans on media smarts. How many do you know like briefly on this topic. It's, well over 200. I don't have the count in front of me. I mean, and we're always on we're always on an audit and update cycle. And it's one of the reasons I don't know that offhand, because, we will go back and look and sometimes will retire or lesson more often will update it.

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And so one of the other things that we've been doing over the last few years, besides creating new lessons that focus on AI, is integrating AI into subjects where it needs to be addressed. So we have, for instance, one a couple of lessons that look at the idea of consent in the digital context. One of them is for younger students, and it does it in kind of a, nonspecific way.

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Just talking more generally about, you know, sharing, making sure you get consent before sharing a photo that might be embarrassing or something like that. And then we have another lesson, for older students that looks specifically at, sexting, and addresses, the moral disengagement techniques, or mechanisms, the excuses people give for sharing a sext without permission.

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And in both of these, we've integrated intimate deepfakes. So in the one for younger students, we may get just an embarrassing deepfake and the one for older students, we do identify it as an intimate deepfake, but recognize it in both cases. It's the exact same thing. The fact that it is an AI image rather than a real image, doesn't make it any less harmful, and it doesn't remove the need to get consent from someone before you post a photo or video that they're in, even if they never posed for it.

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Yeah, that's a sort of neat. I, I love all all of the work you guys are doing, like I said. And, one last question I am curious about because I think, for a lot of people, this is an industry. I in particular. But even like social media, the tidal wave has already swept us away in a lot of ways.

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I think it feels like for a lot of people. But, how do you personally, you're the director of education? For media smarts. How do you stay on top of this? What is, you know, in a, in a industry where we are hearing every other day that, you know, we're on the verge of AGI, everything, we're about to lose all our jobs, but also all our jobs are really a matter what is how do you shift through it?

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What what kind of things do you do to stay on top of this, but also stay realistic about what you're saying? I mean, a lot of it is just what I do generally to try to stay on top of all of the topics that we cover. You know, obviously, I'm aware that AI is is one of the, the hot button issues.

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And there's a lot of work coming out all the time right now. I am very I follow a lot of people on blue Sky who are doing work on AI, particularly as it relates to education or as it relates to learning. And, you know, I, I make a point of following people, but I don't necessarily agree with, a lot of the people that I follow, for instance, are a lot more critical and skeptical about AI.

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But I think that's, you know, that's really important. I agree, I think it's such an important part of having a full social media and. Yeah, to make sure that you're getting things that are challenging you so long and stay there based in evidence, you know, they're they're doing real scholarship. And one of the things that I do every day, is, like, we have a news digest, where every day we send out five links to news stories relating to media.

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And honestly, it's a challenge. I kind of have a personal rule. I keep it down to two AI stories per day. Maximum. I'm always looking for stories about other, other media topics because it is it's just happening so, so often that even even if I don't run one of those things in our news digest, it's always save to our reference library.

00;35;26;04 - 00;35;52;06
And, it's one of the things that factor in our decision making when about doing a project. So if we get an offer to do a research project, or if we get an offer, to partner on something when it is connected to AI, it's definitely a point in, in the favor of doing that project. Because, you know, we're aware this is something where we have to build and maintain capacity because it is changing so rapidly.

00;35;52;09 - 00;36;17;04
And because it is such hot issue, particular and I think in the education system. Yeah. I really appreciate it. Like I said, I think Canada is very lucky to have your organization. It's media smart sky. It's, it's has such great resources. And thank you so much for for joining us. Well, thanks for letting me.

00;36;17;06 - 00;36;38;27
I is a podcast from Ampere and Canada Learning Code, brought to you by the Pinnguaq Foundation, hosted by Ryan Oliver and also for Melissa Sariffodeen. The show is produced by Zach Miller and edited by Zach Miller and Kyle Gordon. If you want to support AI, please check out the Pinnguaq Foundation on Canada Helps and consider a donation. Thanks for listening.