December 10, 2025 • 27 mins
Students are motivated to learn when they have autonomy and see the purpose in what they are learning. In this episode, Tara Chklovski joins us to discuss a curriculum in which students use AI tools to solve challenging problems in their communities. Tara is the founder and CEO of Technovation, a nonprofit developer of a curriculum used in over 160 countries and reaching over 400,000 students, to prepare young women for careers in technology.
A transcript of this episode and show notes may be found at http://teaforteaching.com.
Mark as Played
Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
(00:00):
Students are motivated to learn when they have autonomy and see the purpose in what
they are learning. In this episode, we examine a curriculum in which students use AI tools to solve
challenging problems in their communities. Thanks for joining us for Tea for Teaching,
(00:22):
an informal discussion of innovative and effective practices in teaching and learning.
This podcast series is hosted by John Kane, an economist...
...and Rebecca Mushtare, a graphic designer......and features guests doing important research
and advocacy work to make higher education more inclusive and supportive of all learners.
(00:50):
Our guest today is Tara Chklovski, the founder and CEO of Technovation,
a nonprofit developer of a curriculum used in over 160 countries and reaching over 400,000 students,
to prepare young women for careers in technology. The current focus of Technovation is on teaching
students to use AI to solve real-world problems in their communities. Welcome, Tara.
(01:11):
Thank you, Rebecca, thank you for having me. Our teas today are... Tara, are you
drinking tea? Yes, I am.
What kind of tea are you drinking?It's Costco’s green tea. I love it.
Very good. Excellent. I have a Twinings English breakfast
that I actually got when I was in London.I have Twinings English breakfast that I got
(01:36):
delivered to my house by Amazon. Actually, I made a whole pot this time,
John, like it's the good stuff. So we've invited you here today to discuss Technovation. But before
we start with that, can you tell us a little bit about your journey to this position.
Yeah, I grew up in India, and I always wanted to be an aerospace engineer, and I came to the U.S.
(01:59):
to do my Masters, and then my PhD. And it was just interesting to me that I did an internship
in India at Hindustan Aeronautics Limited, and I was one of the only women on the research and
development team, and then when I came to the US, and I was doing an internship at a drone company,
I was also one of the only women on the research and development team. And it was just very
(02:21):
surprising to me that the most powerful country in the world had a similar kind of talent makeup
and distribution as a very low-income country. India was much lower income than it is now,
and it made me kind of think about it, and it was just surprising to me to run into people
in the U.S. where, especially women, thought it was okay to say, “I'm just so bad at math,”
(02:46):
and that is almost like such a shameful thing to say in India, because it's kind of saying like,
“Oh, I'm not intelligent or I'm not a good person.” And it was just kind of interesting
to me to see the culture of even people in a wealthy country just assuming that certain
paths are not open to certain people based on their gender or socio-economic status,
(03:10):
and in the richest, most innovative country in the world, that's also the most entrepreneurial,
that was just such a shock to me that that is okay for us to say. And so I stepped out of my
PhD program and actually started a nonprofit 20 years ago, and the goal was to bring cutting-edge
technologies and an innovator's mindset to groups that are not typically thought of as innovators,
(03:34):
and that was the sort of path. And we were funded by the U.S. Navy in the early years, and we were
very, very data driven, trying to figure out what type of model makes the most impact on
students and their mindset as a innovator. And one model really rose to the front that had a durable
impact on students' identity as a problem solver, and that was a three-month long experience where
(03:58):
you work in a team, find a problem in your community, and actually build a technology
solution and present it to your community. And that experience is unforgettable. And 10 years
after that experience, students would choose STEM careers because of that very, very formative,
collaborative learning experience. And when we saw that, it was like, “Okay, this is it,
(04:21):
and we need to scale this up.” And we brought it to 120 countries, and it has run primarily as an
after-school program, and now we have adapted a new version of the same curriculum, but making it
easier for educators to use in the classroom. And that's the AI in Action curriculum.
Can you tell us about this program?Yeah, as I was sort of mapping out the journey,
(04:41):
it is really our Technovation curriculum and our Technovation model of supporting students to go
out into their community, talk to nonprofit organizations, actually any organization,
find out what are some big problems that are impacting people, and then developing
a technology solution and testing it with those users. So we started doing AI nine years ago,
(05:01):
before anybody was talking about AI. Nvidia and Google and the Patrick J McGowan foundation were
the three sort of leaders who recognized what was coming and wanted to make sure that there was a
lot of education support built in when AI really became mainstream. And guess what? It took about
nine years for it to become what it is today. And so we are entering the space with a lot of
(05:26):
evidence-based curriculum, a lot of incredible stories of students actually using and building
AI solutions for good. And so, as I had mentioned, this curriculum has run primarily in after school,
and so we adapted it to be a shorter version that educators can adapt for in school,
and you go through the same sequence of how do you find a problem that's a meaningful problem,
(05:49):
impacts a lot of people, and you need to have no prior technical background. How do you actually
build an AI prototype? How do you build your own data set? How do you train a model? How
do you make sure that it is not going to hurt anyone? And then actually test it with users,
iterate, and then present it to the broader community on kind of like a demo day.
You mentioned that it was after school, now you've shortened it so it can be
(06:12):
embedded into curriculum at schools. How do educators come about the program and
actually bring it to their classrooms?Yeah, so it's completely free. Just go to
technovation.org, and you can go onto the curriculum. And so there are two tracks.
Basically, one is a competition track, and that is primarily for girls, and so that
(06:34):
has typically been what we've been running after school. And then we have the AI in Action track,
which is for educators, for use in the classroom, again, completely free, and you can access it from
our website. You can also sign up for our educator guide that will provide you. Again, you know,
you need no prior AI background, and the exciting thing is, we want you to become part of our global
(06:56):
educator community and get connected to other communities of practice, learn from one another,
and especially for students, its super inspiring to see what other students around the world are
using and building to improve the world.Can you talk a little bit about the
competition track, why the focus has been historically on young women?
(07:16):
Yeah, we don't have, like, I started like, the problem statement. I think every one of
the 190 countries legally discriminates against women. They have a very big ladder to climb. And
I just think that a country really loses out on innovation when you just have one type of person
that is in the leadership role or in the sort of innovator's seat. And, I think, if a country is
(07:43):
really to make progress, you want everybody to have these kind of future-ready skills and these
future-ready mindsets. And so I don't see this as from an equity lens, I really see it as this
is what a country needs to innovate and to stay thriving. So that, especially in the age of AI,
where so many of your traditional white-collar prestigious jobs are being automated, there's a
(08:07):
real question of like, what are the big problems that are left for humans to solve? And these are
these very complex human-related problems where so many people don't have access to healthcare,
education, there's hunger across the US. And so who's solving these problems? These are very,
very difficult problems, and we are not empowering students to tackle these very
complex problems. And so I think that this kind of future-ready skilling and mindset
(08:31):
is really important to bring, especially to groups that have not been part of that.
Can you tell us a little bit more about the competition track? How is it structured?
Yeah, absolutely. So there's just so much evidence to show that having a deadline motivates humans to
try doing big things in a short amount of time. And so, yeah, it is a challenge and the challenge
(08:54):
is find a problem in your community with a team. And so we invite girls to form teams sometime
around now, anyone can go onto our website and register and start basically going through all
the steps. As an educator, you can think about if you want to invite or do a club, or an after
school club, or bring some students together, and then have the students self select into teams…
(09:18):
anywhere between one to five… and then the most exciting part is for them to find a problem that
they all care about, that they want to solve. And this is the highest learning opportunity,
because they have to sort of think about their own value systems, who they are as people, what do
they care about, and then they have to compromise as a team. And so the collaboration that happens
(09:39):
there is very, very deep, and the conflicts that happen and the negotiation that happens. Once you
register on the Technovation platform, we try to connect every team with mentors from industry,
depending on your zip code or whether you're virtual, and so educators are always connected
to more help, so that the teams are not on their own. And then the team of girls and mentors walk
(10:02):
through the 12-week curriculum. There are three subtracts divided by age. So beginners, eight to
12, junior is 13 to 15, senior is 16 to 18. And now we have an advanced accelerator track for
19 to 24. And so the curriculum is appropriately scaffolded for these age groups. And then, yeah,
you spend 12 weeks actually prototyping, testing your product with users, and then doing that final
(10:26):
demo day. And depending on how effective your solution is and how big your problem is, you may
make it to the different rankings, so quarter final, final, and then we have the big world
summit, where we apply the finalists from around the world. Last year we had it at Nvidia, and
that experience is absolutely life changing for these girls, because they make friends with other
(10:47):
innovators from around the world, and they stay in touch with them, and that's their cohort of fellow
inventors. So yeah, that's the whole journey. This past year, we had about 33,000 girls compete.
That's wonderful. I'm thinking, as an educator, it sounds really enticing and really exciting,
but also maybe a little overwhelming to like, take a group of students on a journey like this.
(11:08):
You mentioned that maybe the educators don't necessarily have to have a background in AI,
but what are some things that they would need to be prepared to do to lead a project?
And is there training for the educators?Absolutely, there's a training for educators,
and you can sign up, and now is the time, and you get connected with my incredible
team of colleagues who absolutely love to support educators on this professional development journey
(11:32):
and this journey of sort of bringing a sense of purpose to their students. It's so, so fulfilling,
because it's not like your average class project, because you're actually going out into the
community. You have students listen to people and hear about their problems and then frame a
solution. And students are very self motivated, because when you sort of promise somebody else
(11:55):
that I'm going to make a solution for you, the students have an increased sense of accountability
and responsibility, which grades can never do. And so you really unlock this deep sense of purpose
and a problem solver’s identity in students, and that's very fulfilling for educators. So Rebecca,
you're absolutely right. It feels overwhelming, but I think the thing to remember is like, there's
(12:16):
no right or wrong, because even a very lightweight experience for students is very powerful, and like
with FIRST Robotics or any kind of competition framework that lasts for a long period of time,
every year you do it, you get more students, you understand things a bit better, things become
familiar, and you just get better at facilitating. But you're not alone, and I think if you keep in
(12:38):
mind that you don't need to be the expert, but you can basically use AI to solve so many of these
questions that you may have, it's not going to be that overwhelming, because if there's something
that you don't know, you just say, “I don't know, let's go find out.” And that part is just fun.
I find that it's so exhilarating to work with young people, because they're so unafraid, like
(13:00):
I'm afraid to try new things and break things, they just go bang at the keys, break things,
and nothing happens. And it's very inspiring to me, and that kind of reverse mentoring is
something I'm like, “Yeah, I'm a facilitator, but I'm learning so much here too.”
You mentioned that the AI in Action curriculum was free. Who bears the costs of
this? I know you're a nonprofit organization. Yeah, that's a great question, John. So technology
(13:25):
companies and our corporate partners who are really interested in building a talent pipeline,
a talent network, because if we are to increase resilience in the United States, there is a real
question of, where are the people coming from? And so the industry is very, very interested in
addressing the skilling problem. AI skilling is a very important part of the full AI supply chain,
(13:49):
and that's what they have been supporting, the development the build out of the curriculum,
as well as engaging their employees as mentors.I want to pick up on something you were just
talking about, which is there's a lot of opportunity for educators to learn from
students about lack of fear. A lot of college students, for example, are more comfortable
with AI than maybe some of the faculty. Is this also true in elementary and secondary education,
(14:15):
and if we're going to venture into an AI space that we might be unfamiliar with,
what are some basic things to get started?I honestly think the Technovation curriculum
and experience is a very powerful one, because it actually unlocks and opens up the black box of how
a large language model works. I'll give you one example of what a student builds, because it'll
(14:36):
help you immediately understand what it means to build a dedicated AI solution for a problem. So a
girl was looking to clean a local lake. This was in India, and bringing volunteers together, and
she wanted to sort of give some data back to the volunteers about how the lake was getting better,
and she didn't have access to a water sensor and her idea was she would train an AI model to
(15:00):
detect the sounds of birds, and more birds would come as the water became cleaner. And so when she
was looking online for an AI model that would automatically detect bird song, she only came
across North American models. And so she built her own data set of Indian birds so that it could
actually recognize the Indian bird songs. And these are examples of students around the world
(15:24):
building new data sets that don't exist currently for problems that are not being addressed by the
AI models and solutions out there. And so educators can really be on the forefront of
that if they were to partner with young people and students. And that's where the innovation lies,
(15:45):
and the only thing holding us back is fear. And I think we're all super busy, and so the other
thing holding us back is that we probably feel too overwhelmed and uncomfortable to make time and to
prioritize this. But here's the thing like, this is unlike previous technologies. This is unlike
the internet. This is unlike mobile. This is unlike a lot of the other kind of technology
(16:10):
waves, because it's never threatened what humans did so closely. And the kinds of conversations
we are having today are very different from what we used to have before, because sort of what it
means to be human is being questioned when an AI, sort of chatbot responds sympathetically to you,
and what if you didn't know it was an AI chatbot, like, what if your friend was not a true friend
(16:32):
and responded in a similar sort of robotic way? It still makes us feel the same way,
right? And so that is a very scary piece, because that means that I don't know what it means to be
uniquely human. And so I think that over the next five years, people, especially our age, adults,
if we are not fully grasping our hands around this crazy, scary thing, we'll just get more
(16:56):
and more buried by our own fears. And so the most we can do is to really embrace it and experiment
and young people do it the best. So I think the Technovation model of adults co-learning with
young people is such a powerful and a fun way. Otherwise, online learning is so boring.
One thing that you're highlighting is having a goal, or like a problem that
(17:18):
you're interested in and connected to and that you want to solve. And I think that's always a
motivating way to pick up some new skills.Absolutely, and I think grounding it in your
community, whatever your community would be, it could be physical, geographical, online.
Now, I know at the college level, students are often racing a bit ahead of their professors in
terms of adopting AI tools, and in terms of that willingness, as you said, students are much more
(17:42):
willing to try things and not be too worried about the risks of things breaking, but I know a lot of
college professors are a little reluctant to try it. Are you seeing the same sort of things in K-12
education? The response of many school districts initially was to try to ban the use of any AI,
but that broke down pretty quickly, but are you still seeing that same sort of resistance
(18:04):
to introducing AI tools in K-12 education?Absolutely, you can see it everywhere. It's
the same kind of percentage of adoption, fear, hesitation, almost in every workplace,
and especially so in the education space, because it takes so many years to build curriculum,
build evaluation methodologies, set those systems in place, align teacher… like all the incentives
(18:27):
and performance around that. And so I think we're going to have this period of intense chaos where
the evaluation methods have not caught up with the tools that students are using. And so I think the
place is really to have open conversations with your students, because this is such an interesting
time. You can bury your head in the sand and say, “This is above my pay grade,” or “This is not my
(18:53):
job,” or you can really engage your students in some fascinating questions about how they are
using AI tools to do their homework at home, and how do they see their brains changing as
they are using AI for a lot of their assignments. And I think that will be very, very interesting.
I don't know if schools can quickly adapt and ask these questions, of like, what are the skills that
(19:17):
are important to teach? Because I think we're all grappling with that question. I think when
people talk about empathy, being uniquely human, I was just kind of saying, I don't know what that
means when a chatbot can mimic empathy much better than even a human could. So I think
that this is a time for parents and educators to really open their minds and actually ask young
(19:41):
people and their children, no matter how young, because guess what? They're all using AI. What do
you think is happening in your brain? I have two daughters, and my older one was saying that she
can feel her brain going soft in some places, but being exercised in different ways. And so that's
very interesting. Like, I totally feel my brain going soft in some ways and stretching in other
(20:03):
ways. And so, yeah, what is happening here?People who already have become experts or have
developed some expertise in an area are able to critically evaluate the output of AI systems.
But there's a lot of concerns that beginners might do some cognitive offloading and not
develop those critical thinking skills needed to critically evaluate the output. And we know
(20:26):
those hallucinations do occur because of the nature of these models. What can teachers do,
at all levels, to help develop the critical thinking skills needed to
be able to critically evaluate the output?I think that's such a great question, John. And
I'll come back to really encouraging students to tackle the big problems, because complex systems
(20:47):
thinking is not a linear problem, like where you follow a bunch of steps. I'll give you an example.
A very common problem that students try to tackle is hunger, especially in the United States. And
the problem is so complex, because many people in the middle class families see the amount of food
being wasted in restaurants, at your home, and so you immediately think, “Oh, what if it was a
(21:11):
better food distribution method that would bring this food that's being wasted to the people that
are hungry?” And many people will just stop at that solution, and that is not a solution.
The hard part is, really, this is perishable, these are perishable items. They're dependent
on preferences. It's dependent on where you are, and the cost of logistics and transportations are
(21:32):
enormous. And how would you do that at scale? Everything can be done for one little thing,
but you'll break down when you do it at scale. And so that's a complex system, and that kind of
mental mapping and problem solving is completely different from the little project that you would
outline to a student. And so those are the kinds of skills that are really the ones that are
(21:54):
what we need. And I think teachers have… there is time in the classroom. And if you align a lot of,
I think, reading, literacy, math standards, into a rich project like this, I think you are preparing
students very well for the future. And then they're completely understanding they're using
AI at every step of the game, at every step of that way, and they're seeing exactly what you were
(22:17):
mentioning because they're so invested in the end outcome that they're checking and they're like,
“Wait, that doesn't line up.” And so they're motivated, they're invested in their learning
journey. I see students short cutting when they don't care. We've traditionally sidestepped that
question when students ask, “why should I care about this? Why does this matter to me?” And we
(22:37):
typically say, "This is important for your brain, this is important for your future.” And I think
we can't hide behind that for much longer.You've mentioned that the competition track at
least is 12 weeks and I know the one for the AI in Action is a little bit shorter,
but there's a structure to it, because it goes week by week. Can you talk a little
bit about what that structure looks like?Yeah, absolutely. And so the very first part
(22:58):
is problem identification, kind of like what we were talking about, and not very broadly,
like, “Oh, I'm going to solve hunger,” but really narrow it down into what exactly is the problem,
and then how can AI technologies actually address it? And so if you were to go back to
our hunger example, it could literally be, how do we use AI to predict supply and demand? And
(23:20):
how could we make the distribution of unused food as efficient as possible with minimal use of gas
and energy and things like that? And so that problem identification, a meaningful problem,
takes a few weeks, and we provide a lot of exercises, worksheets, for students to be able
to do this, and for educators to facilitate that. The next phase would be prototyping,
(23:42):
where you actually prototype on paper, and then you go out into the community and get
feedback from actual people on would this actually help you? Where are you getting stuck? And then
kind of building out the user interface for that. Third stage would be to actually start to code it,
and this is where they're learning whether they're going to build it as a mobile app, or have it as a
(24:03):
website or whatever. And then you start to think about, once it's actually working, you test it
again with people, and then you actually think about, how can you bring it to a lot of people?
And so there's a marketing element to it. There's a business element to it. You look at competitors,
you look at how much money is needed to actually scale it. And so that's where that entrepreneurial
learning happens a lot. And then the last phase is again, after iterating your solution a bunch
(24:26):
of times, you actually develop a pitch video or a pitch where you tell your story and you practice
explaining your solution to a larger audience so that more people adopt it and give you feedback.
So that's the full spectrum, and it's a spectrum of starting a startup. I think for educators,
and Rebecca, you were talking about like it's a very real thing, like when you're busy on your
(24:49):
day to day, it feels overwhelming to try something new, to learn something new, and to restructure
your life to make room for that. And I think that, as I was saying, that this is a very unusual time,
and you may think that, “Oh, I'll be fine,” but the option is, there's a very real risk of jobs
(25:10):
being completely eradicated. I think educators are not going anywhere, because we learn best from
humans, but you can really be a superstar if you learn how to leverage these tools to support you,
rather than have that be pushed down on you when you're not ready. And so I think taking
ownership of your own learning journey and your career and your professional development,
(25:33):
I think it's a very exciting sort of juncture for adults today where you can choose to really be a
world class superstar because you have the world class superstar tools at your disposal, and the
only thing holding you back is your mindset.So we always wrap up by asking, what's next?
Yeah, I think for us, it's really about trying to support and get educators to help their students
(25:56):
get ready to solve these big problems. Because I sort of see an extreme case where corporations are
making so much money with AI automation, maybe, like, I don't know whether universal basic income
is a real thing, but what if it is? Then the big problems that corporations will not be solving
are the ones that still cause human suffering, healthcare for all, high quality education for
(26:19):
all, no hunger, and those are not incentivized by industry. And so whose job is it to solve those?
It's our job. And I think that really encouraging students to have that sense of empathy and
empathize with another human’s suffering and to try to do something about it. I think that's the
core of what makes us human. And so that's why we want to bring this and work with educators
(26:40):
to bring this to many, many more students.So if people would like to find out more about
the program, we'll include links to your website so that people can learn about the AI in Action
Program and the other programs that you run. And thank you for all of your work on this.
Absolutely. Thank you for having me.Yeah, thank you for sharing this exciting work.
(27:01):
And it's even better that it's free. Yes, absolutely!
If you've enjoyed this podcast, please subscribe and leave a review on Apple
Podcasts or your favorite podcast service. To continue the conversation, join us on
our Tea for Teaching Facebook page. You can find show notes, transcripts and
(27:25):
other materials on teaforteaching.com. Music by Michael Gary Brewer.
Students are motivated to learn when they have autonomy and see the purpose in what
they are learning. In this episode, we examine a curriculum in which students use AI tools to solve
challenging problems in their communities. Thanks for joining us for Tea for Teaching,
(00:22):
an informal discussion of innovative and effective practices in teaching and learning.
This podcast series is hosted by John Kane, an economist...
...and Rebecca Mushtare, a graphic designer......and features guests doing important research
and advocacy work to make higher education more inclusive and supportive of all learners.
(00:50):
Our guest today is Tara Chklovski, the founder and CEO of Technovation,
a nonprofit developer of a curriculum used in over 160 countries and reaching over 400,000 students,
to prepare young women for careers in technology. The current focus of Technovation is on teaching
students to use AI to solve real-world problems in their communities. Welcome, Tara.
(01:11):
Thank you, Rebecca, thank you for having me. Our teas today are... Tara, are you
drinking tea? Yes, I am.
What kind of tea are you drinking?It's Costco’s green tea. I love it.
Very good. Excellent. I have a Twinings English breakfast
that I actually got when I was in London.I have Twinings English breakfast that I got
(01:36):
delivered to my house by Amazon. Actually, I made a whole pot this time,
John, like it's the good stuff. So we've invited you here today to discuss Technovation. But before
we start with that, can you tell us a little bit about your journey to this position.
Yeah, I grew up in India, and I always wanted to be an aerospace engineer, and I came to the U.S.
(01:59):
to do my Masters, and then my PhD. And it was just interesting to me that I did an internship
in India at Hindustan Aeronautics Limited, and I was one of the only women on the research and
development team, and then when I came to the US, and I was doing an internship at a drone company,
I was also one of the only women on the research and development team. And it was just very
(02:21):
surprising to me that the most powerful country in the world had a similar kind of talent makeup
and distribution as a very low-income country. India was much lower income than it is now,
and it made me kind of think about it, and it was just surprising to me to run into people
in the U.S. where, especially women, thought it was okay to say, “I'm just so bad at math,”
(02:46):
and that is almost like such a shameful thing to say in India, because it's kind of saying like,
“Oh, I'm not intelligent or I'm not a good person.” And it was just kind of interesting
to me to see the culture of even people in a wealthy country just assuming that certain
paths are not open to certain people based on their gender or socio-economic status,
(03:10):
and in the richest, most innovative country in the world, that's also the most entrepreneurial,
that was just such a shock to me that that is okay for us to say. And so I stepped out of my
PhD program and actually started a nonprofit 20 years ago, and the goal was to bring cutting-edge
technologies and an innovator's mindset to groups that are not typically thought of as innovators,
(03:34):
and that was the sort of path. And we were funded by the U.S. Navy in the early years, and we were
very, very data driven, trying to figure out what type of model makes the most impact on
students and their mindset as a innovator. And one model really rose to the front that had a durable
impact on students' identity as a problem solver, and that was a three-month long experience where
(03:58):
you work in a team, find a problem in your community, and actually build a technology
solution and present it to your community. And that experience is unforgettable. And 10 years
after that experience, students would choose STEM careers because of that very, very formative,
collaborative learning experience. And when we saw that, it was like, “Okay, this is it,
(04:21):
and we need to scale this up.” And we brought it to 120 countries, and it has run primarily as an
after-school program, and now we have adapted a new version of the same curriculum, but making it
easier for educators to use in the classroom. And that's the AI in Action curriculum.
Can you tell us about this program?Yeah, as I was sort of mapping out the journey,
(04:41):
it is really our Technovation curriculum and our Technovation model of supporting students to go
out into their community, talk to nonprofit organizations, actually any organization,
find out what are some big problems that are impacting people, and then developing
a technology solution and testing it with those users. So we started doing AI nine years ago,
(05:01):
before anybody was talking about AI. Nvidia and Google and the Patrick J McGowan foundation were
the three sort of leaders who recognized what was coming and wanted to make sure that there was a
lot of education support built in when AI really became mainstream. And guess what? It took about
nine years for it to become what it is today. And so we are entering the space with a lot of
(05:26):
evidence-based curriculum, a lot of incredible stories of students actually using and building
AI solutions for good. And so, as I had mentioned, this curriculum has run primarily in after school,
and so we adapted it to be a shorter version that educators can adapt for in school,
and you go through the same sequence of how do you find a problem that's a meaningful problem,
(05:49):
impacts a lot of people, and you need to have no prior technical background. How do you actually
build an AI prototype? How do you build your own data set? How do you train a model? How
do you make sure that it is not going to hurt anyone? And then actually test it with users,
iterate, and then present it to the broader community on kind of like a demo day.
You mentioned that it was after school, now you've shortened it so it can be
(06:12):
embedded into curriculum at schools. How do educators come about the program and
actually bring it to their classrooms?Yeah, so it's completely free. Just go to
technovation.org, and you can go onto the curriculum. And so there are two tracks.
Basically, one is a competition track, and that is primarily for girls, and so that
(06:34):
has typically been what we've been running after school. And then we have the AI in Action track,
which is for educators, for use in the classroom, again, completely free, and you can access it from
our website. You can also sign up for our educator guide that will provide you. Again, you know,
you need no prior AI background, and the exciting thing is, we want you to become part of our global
(06:56):
educator community and get connected to other communities of practice, learn from one another,
and especially for students, its super inspiring to see what other students around the world are
using and building to improve the world.Can you talk a little bit about the
competition track, why the focus has been historically on young women?
(07:16):
Yeah, we don't have, like, I started like, the problem statement. I think every one of
the 190 countries legally discriminates against women. They have a very big ladder to climb. And
I just think that a country really loses out on innovation when you just have one type of person
that is in the leadership role or in the sort of innovator's seat. And, I think, if a country is
(07:43):
really to make progress, you want everybody to have these kind of future-ready skills and these
future-ready mindsets. And so I don't see this as from an equity lens, I really see it as this
is what a country needs to innovate and to stay thriving. So that, especially in the age of AI,
where so many of your traditional white-collar prestigious jobs are being automated, there's a
(08:07):
real question of like, what are the big problems that are left for humans to solve? And these are
these very complex human-related problems where so many people don't have access to healthcare,
education, there's hunger across the US. And so who's solving these problems? These are very,
very difficult problems, and we are not empowering students to tackle these very
complex problems. And so I think that this kind of future-ready skilling and mindset
(08:31):
is really important to bring, especially to groups that have not been part of that.
Can you tell us a little bit more about the competition track? How is it structured?
Yeah, absolutely. So there's just so much evidence to show that having a deadline motivates humans to
try doing big things in a short amount of time. And so, yeah, it is a challenge and the challenge
(08:54):
is find a problem in your community with a team. And so we invite girls to form teams sometime
around now, anyone can go onto our website and register and start basically going through all
the steps. As an educator, you can think about if you want to invite or do a club, or an after
school club, or bring some students together, and then have the students self select into teams…
(09:18):
anywhere between one to five… and then the most exciting part is for them to find a problem that
they all care about, that they want to solve. And this is the highest learning opportunity,
because they have to sort of think about their own value systems, who they are as people, what do
they care about, and then they have to compromise as a team. And so the collaboration that happens
(09:39):
there is very, very deep, and the conflicts that happen and the negotiation that happens. Once you
register on the Technovation platform, we try to connect every team with mentors from industry,
depending on your zip code or whether you're virtual, and so educators are always connected
to more help, so that the teams are not on their own. And then the team of girls and mentors walk
(10:02):
through the 12-week curriculum. There are three subtracts divided by age. So beginners, eight to
12, junior is 13 to 15, senior is 16 to 18. And now we have an advanced accelerator track for
19 to 24. And so the curriculum is appropriately scaffolded for these age groups. And then, yeah,
you spend 12 weeks actually prototyping, testing your product with users, and then doing that final
(10:26):
demo day. And depending on how effective your solution is and how big your problem is, you may
make it to the different rankings, so quarter final, final, and then we have the big world
summit, where we apply the finalists from around the world. Last year we had it at Nvidia, and
that experience is absolutely life changing for these girls, because they make friends with other
(10:47):
innovators from around the world, and they stay in touch with them, and that's their cohort of fellow
inventors. So yeah, that's the whole journey. This past year, we had about 33,000 girls compete.
That's wonderful. I'm thinking, as an educator, it sounds really enticing and really exciting,
but also maybe a little overwhelming to like, take a group of students on a journey like this.
(11:08):
You mentioned that maybe the educators don't necessarily have to have a background in AI,
but what are some things that they would need to be prepared to do to lead a project?
And is there training for the educators?Absolutely, there's a training for educators,
and you can sign up, and now is the time, and you get connected with my incredible
team of colleagues who absolutely love to support educators on this professional development journey
(11:32):
and this journey of sort of bringing a sense of purpose to their students. It's so, so fulfilling,
because it's not like your average class project, because you're actually going out into the
community. You have students listen to people and hear about their problems and then frame a
solution. And students are very self motivated, because when you sort of promise somebody else
(11:55):
that I'm going to make a solution for you, the students have an increased sense of accountability
and responsibility, which grades can never do. And so you really unlock this deep sense of purpose
and a problem solver’s identity in students, and that's very fulfilling for educators. So Rebecca,
you're absolutely right. It feels overwhelming, but I think the thing to remember is like, there's
(12:16):
no right or wrong, because even a very lightweight experience for students is very powerful, and like
with FIRST Robotics or any kind of competition framework that lasts for a long period of time,
every year you do it, you get more students, you understand things a bit better, things become
familiar, and you just get better at facilitating. But you're not alone, and I think if you keep in
(12:38):
mind that you don't need to be the expert, but you can basically use AI to solve so many of these
questions that you may have, it's not going to be that overwhelming, because if there's something
that you don't know, you just say, “I don't know, let's go find out.” And that part is just fun.
I find that it's so exhilarating to work with young people, because they're so unafraid, like
(13:00):
I'm afraid to try new things and break things, they just go bang at the keys, break things,
and nothing happens. And it's very inspiring to me, and that kind of reverse mentoring is
something I'm like, “Yeah, I'm a facilitator, but I'm learning so much here too.”
You mentioned that the AI in Action curriculum was free. Who bears the costs of
this? I know you're a nonprofit organization. Yeah, that's a great question, John. So technology
(13:25):
companies and our corporate partners who are really interested in building a talent pipeline,
a talent network, because if we are to increase resilience in the United States, there is a real
question of, where are the people coming from? And so the industry is very, very interested in
addressing the skilling problem. AI skilling is a very important part of the full AI supply chain,
(13:49):
and that's what they have been supporting, the development the build out of the curriculum,
as well as engaging their employees as mentors.I want to pick up on something you were just
talking about, which is there's a lot of opportunity for educators to learn from
students about lack of fear. A lot of college students, for example, are more comfortable
with AI than maybe some of the faculty. Is this also true in elementary and secondary education,
(14:15):
and if we're going to venture into an AI space that we might be unfamiliar with,
what are some basic things to get started?I honestly think the Technovation curriculum
and experience is a very powerful one, because it actually unlocks and opens up the black box of how
a large language model works. I'll give you one example of what a student builds, because it'll
(14:36):
help you immediately understand what it means to build a dedicated AI solution for a problem. So a
girl was looking to clean a local lake. This was in India, and bringing volunteers together, and
she wanted to sort of give some data back to the volunteers about how the lake was getting better,
and she didn't have access to a water sensor and her idea was she would train an AI model to
(15:00):
detect the sounds of birds, and more birds would come as the water became cleaner. And so when she
was looking online for an AI model that would automatically detect bird song, she only came
across North American models. And so she built her own data set of Indian birds so that it could
actually recognize the Indian bird songs. And these are examples of students around the world
(15:24):
building new data sets that don't exist currently for problems that are not being addressed by the
AI models and solutions out there. And so educators can really be on the forefront of
that if they were to partner with young people and students. And that's where the innovation lies,
(15:45):
and the only thing holding us back is fear. And I think we're all super busy, and so the other
thing holding us back is that we probably feel too overwhelmed and uncomfortable to make time and to
prioritize this. But here's the thing like, this is unlike previous technologies. This is unlike
the internet. This is unlike mobile. This is unlike a lot of the other kind of technology
(16:10):
waves, because it's never threatened what humans did so closely. And the kinds of conversations
we are having today are very different from what we used to have before, because sort of what it
means to be human is being questioned when an AI, sort of chatbot responds sympathetically to you,
and what if you didn't know it was an AI chatbot, like, what if your friend was not a true friend
(16:32):
and responded in a similar sort of robotic way? It still makes us feel the same way,
right? And so that is a very scary piece, because that means that I don't know what it means to be
uniquely human. And so I think that over the next five years, people, especially our age, adults,
if we are not fully grasping our hands around this crazy, scary thing, we'll just get more
(16:56):
and more buried by our own fears. And so the most we can do is to really embrace it and experiment
and young people do it the best. So I think the Technovation model of adults co-learning with
young people is such a powerful and a fun way. Otherwise, online learning is so boring.
One thing that you're highlighting is having a goal, or like a problem that
(17:18):
you're interested in and connected to and that you want to solve. And I think that's always a
motivating way to pick up some new skills.Absolutely, and I think grounding it in your
community, whatever your community would be, it could be physical, geographical, online.
Now, I know at the college level, students are often racing a bit ahead of their professors in
terms of adopting AI tools, and in terms of that willingness, as you said, students are much more
(17:42):
willing to try things and not be too worried about the risks of things breaking, but I know a lot of
college professors are a little reluctant to try it. Are you seeing the same sort of things in K-12
education? The response of many school districts initially was to try to ban the use of any AI,
but that broke down pretty quickly, but are you still seeing that same sort of resistance
(18:04):
to introducing AI tools in K-12 education?Absolutely, you can see it everywhere. It's
the same kind of percentage of adoption, fear, hesitation, almost in every workplace,
and especially so in the education space, because it takes so many years to build curriculum,
build evaluation methodologies, set those systems in place, align teacher… like all the incentives
(18:27):
and performance around that. And so I think we're going to have this period of intense chaos where
the evaluation methods have not caught up with the tools that students are using. And so I think the
place is really to have open conversations with your students, because this is such an interesting
time. You can bury your head in the sand and say, “This is above my pay grade,” or “This is not my
(18:53):
job,” or you can really engage your students in some fascinating questions about how they are
using AI tools to do their homework at home, and how do they see their brains changing as
they are using AI for a lot of their assignments. And I think that will be very, very interesting.
I don't know if schools can quickly adapt and ask these questions, of like, what are the skills that
(19:17):
are important to teach? Because I think we're all grappling with that question. I think when
people talk about empathy, being uniquely human, I was just kind of saying, I don't know what that
means when a chatbot can mimic empathy much better than even a human could. So I think
that this is a time for parents and educators to really open their minds and actually ask young
(19:41):
people and their children, no matter how young, because guess what? They're all using AI. What do
you think is happening in your brain? I have two daughters, and my older one was saying that she
can feel her brain going soft in some places, but being exercised in different ways. And so that's
very interesting. Like, I totally feel my brain going soft in some ways and stretching in other
(20:03):
ways. And so, yeah, what is happening here?People who already have become experts or have
developed some expertise in an area are able to critically evaluate the output of AI systems.
But there's a lot of concerns that beginners might do some cognitive offloading and not
develop those critical thinking skills needed to critically evaluate the output. And we know
(20:26):
those hallucinations do occur because of the nature of these models. What can teachers do,
at all levels, to help develop the critical thinking skills needed to
be able to critically evaluate the output?I think that's such a great question, John. And
I'll come back to really encouraging students to tackle the big problems, because complex systems
(20:47):
thinking is not a linear problem, like where you follow a bunch of steps. I'll give you an example.
A very common problem that students try to tackle is hunger, especially in the United States. And
the problem is so complex, because many people in the middle class families see the amount of food
being wasted in restaurants, at your home, and so you immediately think, “Oh, what if it was a
(21:11):
better food distribution method that would bring this food that's being wasted to the people that
are hungry?” And many people will just stop at that solution, and that is not a solution.
The hard part is, really, this is perishable, these are perishable items. They're dependent
on preferences. It's dependent on where you are, and the cost of logistics and transportations are
(21:32):
enormous. And how would you do that at scale? Everything can be done for one little thing,
but you'll break down when you do it at scale. And so that's a complex system, and that kind of
mental mapping and problem solving is completely different from the little project that you would
outline to a student. And so those are the kinds of skills that are really the ones that are
(21:54):
what we need. And I think teachers have… there is time in the classroom. And if you align a lot of,
I think, reading, literacy, math standards, into a rich project like this, I think you are preparing
students very well for the future. And then they're completely understanding they're using
AI at every step of the game, at every step of that way, and they're seeing exactly what you were
(22:17):
mentioning because they're so invested in the end outcome that they're checking and they're like,
“Wait, that doesn't line up.” And so they're motivated, they're invested in their learning
journey. I see students short cutting when they don't care. We've traditionally sidestepped that
question when students ask, “why should I care about this? Why does this matter to me?” And we
(22:37):
typically say, "This is important for your brain, this is important for your future.” And I think
we can't hide behind that for much longer.You've mentioned that the competition track at
least is 12 weeks and I know the one for the AI in Action is a little bit shorter,
but there's a structure to it, because it goes week by week. Can you talk a little
bit about what that structure looks like?Yeah, absolutely. And so the very first part
(22:58):
is problem identification, kind of like what we were talking about, and not very broadly,
like, “Oh, I'm going to solve hunger,” but really narrow it down into what exactly is the problem,
and then how can AI technologies actually address it? And so if you were to go back to
our hunger example, it could literally be, how do we use AI to predict supply and demand? And
(23:20):
how could we make the distribution of unused food as efficient as possible with minimal use of gas
and energy and things like that? And so that problem identification, a meaningful problem,
takes a few weeks, and we provide a lot of exercises, worksheets, for students to be able
to do this, and for educators to facilitate that. The next phase would be prototyping,
(23:42):
where you actually prototype on paper, and then you go out into the community and get
feedback from actual people on would this actually help you? Where are you getting stuck? And then
kind of building out the user interface for that. Third stage would be to actually start to code it,
and this is where they're learning whether they're going to build it as a mobile app, or have it as a
(24:03):
website or whatever. And then you start to think about, once it's actually working, you test it
again with people, and then you actually think about, how can you bring it to a lot of people?
And so there's a marketing element to it. There's a business element to it. You look at competitors,
you look at how much money is needed to actually scale it. And so that's where that entrepreneurial
learning happens a lot. And then the last phase is again, after iterating your solution a bunch
(24:26):
of times, you actually develop a pitch video or a pitch where you tell your story and you practice
explaining your solution to a larger audience so that more people adopt it and give you feedback.
So that's the full spectrum, and it's a spectrum of starting a startup. I think for educators,
and Rebecca, you were talking about like it's a very real thing, like when you're busy on your
(24:49):
day to day, it feels overwhelming to try something new, to learn something new, and to restructure
your life to make room for that. And I think that, as I was saying, that this is a very unusual time,
and you may think that, “Oh, I'll be fine,” but the option is, there's a very real risk of jobs
(25:10):
being completely eradicated. I think educators are not going anywhere, because we learn best from
humans, but you can really be a superstar if you learn how to leverage these tools to support you,
rather than have that be pushed down on you when you're not ready. And so I think taking
ownership of your own learning journey and your career and your professional development,
(25:33):
I think it's a very exciting sort of juncture for adults today where you can choose to really be a
world class superstar because you have the world class superstar tools at your disposal, and the
only thing holding you back is your mindset.So we always wrap up by asking, what's next?
Yeah, I think for us, it's really about trying to support and get educators to help their students
(25:56):
get ready to solve these big problems. Because I sort of see an extreme case where corporations are
making so much money with AI automation, maybe, like, I don't know whether universal basic income
is a real thing, but what if it is? Then the big problems that corporations will not be solving
are the ones that still cause human suffering, healthcare for all, high quality education for
(26:19):
all, no hunger, and those are not incentivized by industry. And so whose job is it to solve those?
It's our job. And I think that really encouraging students to have that sense of empathy and
empathize with another human’s suffering and to try to do something about it. I think that's the
core of what makes us human. And so that's why we want to bring this and work with educators
(26:40):
to bring this to many, many more students.So if people would like to find out more about
the program, we'll include links to your website so that people can learn about the AI in Action
Program and the other programs that you run. And thank you for all of your work on this.
Absolutely. Thank you for having me.Yeah, thank you for sharing this exciting work.
(27:01):
And it's even better that it's free. Yes, absolutely!
If you've enjoyed this podcast, please subscribe and leave a review on Apple
Podcasts or your favorite podcast service. To continue the conversation, join us on
our Tea for Teaching Facebook page. You can find show notes, transcripts and
(27:25):
other materials on teaforteaching.com. Music by Michael Gary Brewer.
Popular Podcasts
On Purpose with Jay Shetty
I’m Jay Shetty host of On Purpose the worlds #1 Mental Health podcast and I’m so grateful you found us. I started this podcast 5 years ago to invite you into conversations and workshops that are designed to help make you happier, healthier and more healed. I believe that when you (yes you) feel seen, heard and understood you’re able to deal with relationship struggles, work challenges and life’s ups and downs with more ease and grace. I interview experts, celebrities, thought leaders and athletes so that we can grow our mindset, build better habits and uncover a side of them we’ve never seen before. New episodes every Monday and Friday. Your support means the world to me and I don’t take it for granted — click the follow button and leave a review to help us spread the love with On Purpose. I can’t wait for you to listen to your first or 500th episode!
Stuff You Should Know
If you've ever wanted to know about champagne, satanism, the Stonewall Uprising, chaos theory, LSD, El Nino, true crime and Rosa Parks, then look no further. Josh and Chuck have you covered.
The Joe Rogan Experience
The official podcast of comedian Joe Rogan.