How Should we Educate Kids About Artificial Intelligence?

This Women in AI Podcast episode is with Juliet Waters, Chief Knowledge Officer at Kids Code Jeunesse, a Canadian charity with a mission to give every Canadian child access to digital skills education, with a focus on girls and underserved communities. KCJ teaches kids and their educators about topics including algorithm literacy and artificial intelligence, and how these integrate with the UN’s Sustainable Development Goals to give kids the confidence and creative tools they need to build a better future. Read more blogs like this and hear more from AI experts here.

Topics explored include:

  • An Introduction to KCJ
  • The #kid2030 Challenge, and the Response So Far
  • How the Algorithm Literacy Project Came About and It’s Goals for the Initiative
  • Kids Interest in Pursuing a Career in AI
  • The Positive Impact of COVID-19 on KCJ
  • Challenges Faced by Women AI Practitioners in the AI World
  • Role Models and the Importance of Them

🎧 Listen to the podcast here.

Nikita RE•WORK [0:46]

Hi, Juliet. Thank you so much for joining us for the Woman in AI Podcast today. You’re currently Chief Knowledge Officer at Kids Code Jeunesse so I wanted to, first of all, for any of our listeners that are not maybe familiar with KCJ, ask if you could share a brief overview.

Juliet [1:06]

Sure, so we started a Canadian charity in around 2013, working alongside teachers in classrooms, trying to help develop some viable lesson plans that would help to bring computer programming into the classroom. So we started this, probably around the same time that the UK was mandating coding into their curriculum. And we worked with organizations like Raspberry Pi, we have a really strong partnership with Code Club. So we manage Code Club Canada. And so I would say after three, four years of really working alongside teachers with lesson plans around traditional programming, we started to become interested in how we could help to conceptualize AI algorithms to teachers so that kids and teachers could start working together to reflect on some of the ways that AI was having an impact in their world. And in some of the ethical issues that were being raised. As well, we started to try to use all of this energy in this community that we built towards creating more lesson plans that allied directly with the UN Sustainable Development Goals. So we created a campaign called #kids2030, that would present certain challenges and make available certain challenges to kids around some of those goals. So to raise awareness around that. So that’s where we are, we’ve worked with hundreds of 1000s of kids and 10s of 1000s of teachers across the country, and also alongside international partners, like UNESCO and Raspberry Pi.

Nikita RE•WORK [3:00]

I wanted to just ask you a bit more about that #kid2030 challenge that you just mentioned. This year, it’s to encourage kids to use data science to address plastic pollution. What’s the response been to that challenge so far?

Juliet [3:17]

It has been really unexpectedly great. I mean, we only launched it a couple of weeks ago and we’ve had a few 1000 views. We have had quite a number of submissions across the country in a really short amount of time. And then today, everyone’s really excited because we had our first global submission. So we had somebody submit a challenge from India, a kid, he wanted to find a way to turn plastic into electricity. So we’re really happy about that. And really happy about all of the positive feedback that we’ve had from educators and partners in the industry and in the SDGs. And it’s just so great to enter this decade of action with something fun like this.

Nikita RE•WORK [4:12]

That’s great. It’s been such a positive response. Another initiative that I wanted to explore a bit further is The Algorithm Literacy Project. It’s an absolutely fantastic idea, and some of the reasons behind it are relevant for the whole of society, not just for kids. I was doing a bit more about what you term as the big ideas, things such as the AI is not magic, that it can be wrong, that training data matters, that the use of AI creates ethical issues around bias and transparency, accountability explainability. So all of those topics, we touch on it at every single event that we do. Could tell us a bit more about how that project came about and also what are your goals for that initiative?

Juliet [5:02]

So, the project came about through a partnership with the Canadian Division of UNESCO, they approached us about wanting to create a public service awareness campaign contextualizing algorithm in the context of media literacy because there are so many teachers right now who are teaching media literacy. And media has been shaped so much by AI algorithms, we wanted to create some awareness around that and some materials around that. But at a more, I would say, really crucial level. I have been thinking so much in the last couple of years about this generation of kids that have grown up with smartphones and knowing that they never get to know a world that’s not mediated by AI algorithms. And you see the impact of that now in research that’s coming out that shows that least, you know, there are three-time YouTube videos that feature kids are three times more popular than any other video on YouTube. And, inevitably, that has been seized on and we see this rise of what we call kid-fluences’. These are kids that are making YouTube videos every day, obviously, in collaboration with their parents, making 10s of millions of dollars reaching a preschool and early school kid audience who don’t know, and whose parents don’t know that their viewing habits are being tracked. That their whole media landscape is being shaped by these algorithms. So we really wanted to create something that would just start a conversation around that and empower teachers and students and parents to just start thinking about the presence of AI in their media environment.

Nikita RE•WORK [7:11]

It’s such an important issue, and as you said, kind of never more so than now. And what has the response been from adults and parents and teachers? Has it been primarily positive, and have there been any challenges?

Juliet [7:27]

Certainly, one of the challenges for us was that we were all set to launch this in Paris, like at a big UNESCO conference, in the first week of March. It got canceled, it was one of the first big conferences that got canceled. So we had to pursue all of these other ways of launching and relaunching this to the point where I actually attended conferences in my Animal Crossing persona, at a research conference organised for AI researchers on Animal Crossing platform, and just finding fun and engaging ways to promote this video on the places that people were going to. So I mean, it’s been quite good, we have a pretty steady stream of, I would say, probably close to 2000, monthly videos, views and visitors in English and French, because it’s also fully bilingual. We get to have a lot of enthusiastic feedback about how important this is, and how glad people are that we are making these issues visible. But because we never were able to have that big, big international launch that we wanted to have, it’s great the more people engage with this and pass it along, the better.

Nikita RE•WORK [9:05]

And how can any of our interested listeners get involved?

Juliet [9:10]

Well, number one, they can visit it at algorithmliteracy.org. There are a huge number of resources there, there is a video that we created that helps to spark some interest from kids in how AI algorithms work. But there’s also a number of resources there. There’s a Canadian Premier on computational thinking and code, for those who still want to look at traditional algorithms and also look at like how you spark the kind of thinking that we want to see kids and adults doing around algorithms. There’s a whole suite of other offerings around things like preference bubbles and being aware of those. And also, there’s some really interesting resources in there alerting people to bias and gender bias and some interesting resources right now around these issues that are really fun to look at, fun to think about, and obviously quite essential going forward for anybody that is going to be thinking about AI or going into careers in AI.

Nikita RE•WORK [10:32]

And do kids often show more interest in pursuing a career in AI after being involved in some of the work that you do?

“In the UK, ever since they introduced programming into the school system, there’s I think about an 11% rise in girls that are taking on CS”

Juliet [10:42]

That’s a really good question. I wouldn’t say often, because it’s not something that we push in our AI classes at the elementary school level. The reason for that I’m going to say is that we started early on sort of pursuing the traditional, like, let’s bring in like an expert and show the kids like all the fantastic careers that will be open to them, where they can learn to program. What I found is that 10-year-old girls are very conservative. Show them all of the amazing women, cool young women in that, and they’re like, yeah, I don’t know. And then also, what would happen is that the teachers love to take these opportunities when the expert comes in to go and grade some papers, right, because they’re not going into careers in AI, right?

We really change that to make sure that the focus was on having an experience that was really fun and playful and engaging, and that involved the teachers and sort of hope that that was a broader pathway towards interest. And certainly, we’re seeing the statistics, let’s say in the UK, ever since they introduced programming into the school system, there’s I think about an 11% rise in girls that are taking on CS. And that’s even without really giving a lot of support to teachers. So I think that number is going to rise even more as that goes on. So that has tended to be our pathway, we’re going to be working more with teens.

So I think as we get into developing resources for teens will probably bring in a little bit more about, what would you want to learn if you want to be a data analyst or a data scientist, or a data engineer? Like what are the different kinds of things that these people do? And do you like to guess things a lot? Like, you’re probably going to want to be a data scientist. Do you like to explore patterns, then maybe a data analyst? Do you like to build things, then think about engineering, like those kinds of broad ways? And I wouldn’t be surprised if we can reach girls through that. Because I think we’re in a much more society and culture that’s supporting that now than we were when we started.

Nikita RE•WORK [13:12]

Definitely, which is a great thing. And what about this year, in particular, so COVID-19, and all of the different ways that that has impacted every part of society, but how is it specifically impacted KCJ in the work that you’ve been doing?

Juliet [13:33]

By and large, it’s had quite a positive impact for us. In that I mean, we were fortunate in that we’d already been doing a lot of online stuff because Canada is such a huge and massive country, that if we’re going to reach our mandate to reach regional schools, we have to do a lot of stuff online. So we were able to take that expertise online pretty fast. So we were able to move all of our code clubs. I mean, the schools started to shut down on March 13 and three days later we were able to move our code clubs over onto online workshops and had them all on by the end of the month. So really, we reached over 5000 children within a couple of months and about 2000 educators, and the need for that support, obviously has not gone away in Canada. So in that way, I think we as an organisation, have felt that we’ve been able to have a positive impact.

Nikita RE•WORK [14:44]

That’s great. And it’s great to be in that position, especially in a year like this when everybody’s had to quickly pivot to move online. So that’s great, and I’m sure that will be really important over the next few months. What about exploring more on the topic of women in AI, which obviously, is the name of this podcast series. But what are your thoughts on the challenges faced by women as AI practitioners? I know that we touched on getting more women involved, and especially girls involved in working in computer science, but from your own experience, have you faced challenges? And what do you think are some of the main challenges faced by women now as AI practitioners?

Juliet [15:33]

I think one of the biggest challenges for women as AI practitioners is that, like it or not, they are the custodians of making sure that the training data is used in the construction of AI and being used in the tools that they’re using, is diverse and fair. And that’s a tough job to have in any company that you’re working in to be the squeaky wheel that goes like, are we sure that the training data is diverse and represents stuff. Other things that as a woman, you end up with a custodial job in is in making sure that AI because it’s not right now as explainable as we would like it to be, is being used alongside human intelligence and intuition still.

So for instance, as a woman, you might be the person that’s going to have to question whether or not we really want to be using AI as the only tool in job performance or job recruitment, or things like that, where often it cannot be explained how the AI algorithms are coming to those things. So I think that that’s challenging. But as always, I think that if you’re going into a career in AI, or even technology anywhere, as a woman, you need to also make sure that you are strengthening and developing your socio-emotional skills alongside your hard skills because those are the skills that they’re going to see you through all of the different parts of your careers.

And those are the skills that are going to have an impact on all of the people in your company. So I think that staying strong, having a good support network, knowing how to be supportive without losing your strength, those are all skills that you still have to do to make sure you are strong, alongside your hard skills.

Nikita RE•WORK [17:50]

And what about role models in the fields in the sector of AI in particular, how influential have they been for you? And how important do you think that they will be in the next few years to come?

Juliet [18:05]

I think they’ll be incredibly important. I love seeing some of the women on your podcast, like Paige Dickie. Working at KCJ, I am so in awe of the many young women that I’ve worked with at KCJ, and that I see in the industry, and those women who are going out right now and raising questions about bias. I’m impressed by researchers like Joy Buolamwini. I think Joy has done so much in raising issues around this. But also, my role models are those women who are going into AI who maybe don’t have huge backgrounds in AI who haven’t been coding since they were 12 years old, who have confidence in themselves as lifelong learners, that they’re going to learn what they need to learn to use these tools. And what they have to learn to be part of AI teams. I think that I see so many women like that, and those are the ones that I’m so inspired by.

Nikita RE•WORK [19:45]

Definitely. I think, well we certainly at RE•WORK, we’re in a great position where we get to see really inspiring women in AI and be in contact with them every day. So we’re in a very fortunate position there. But I think over the past few years that we’ve been hosting events in AI, we’ve certainly seen an increase in the number of women that are even on podcasts or speaking at events or writing blogs about their research. So it’s great to see that increase. And certainly initiatives like the work that you’re doing will definitely help that as well. And so what would be the best way for any of our listeners that would like to get in touch with you to reach out to you. Would it be on Twitter or LinkedIn? Or what would be the best way for them to do that?

Juliet [20:38]

Certainly, they can reach out to me on Twitter at @Julietwaters. They can reach out to me on LinkedIn, they can reach out to me at kids coaching us if they want, juliet@kidscodejeunesse.org. I love hearing from people about our initiatives, and how they’ve been involved in them.

Nikita RE•WORK [21:09]

Thank you so much for that, we’ll share some of those links in their podcast notes, or share your Twitter or LinkedIn, and the website links as well. And also the couple of the videos that you mentioned, so that people can see a bit more about some of those projects that you’re working on, including the algorithm literacy one if anybody’s interested in getting in touch about that. But thank you, again, it’s so interesting to hear about the work that you’re doing and it’s great to hear that the influence and the reach that you’re having is global now, which is fantastic. So I look forward to hearing more about it. And make sure you keep us up to date with KCJ and where it hits in the future as well.

Juliet [21:54]

Thank you so much, Nikita, thanks for having me on. It’s been a pleasure.

Nikita RE•WORK [21:58]

No problem. Thank you.

If you’re keen to learn more about KCJ and The Algorithm Literacy Project, then please do check out the website in the links. If you would like to get involved in any of our Women in AI initiatives, then please do get in touch at hello@re-work.co.

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