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August 7, 2025 63 mins

When civics teacher Zach Kennelly first encountered ChatGPT and DALL-E, he immediately recognized their transformative potential for education. As one of the first AI Trailblazers in aiEDU's fellowship program, Zach has reimagined what's possible in the classroom by positioning AI not as a replacement for human thinking, but as a collaborative tool that empowers students to tackle challenges they care about.

Throughout our conversation, Zach shared how his diverse background in political science, sociology, math, and science provided the perfect foundation for integrating AI into his teaching at the Denver School of Science and Technology Public Schools (DSST) network. Despite initial roadblocks after the school blocked AI tools due to privacy concerns, Zach persisted in his belief that providing students with AI literacy was fundamental – students without AI literacy would soon be competing against peers who were becoming fluent in these technologies.

The results speak for themselves: Zach's civics students created VoteWise Colorado, a voter engagement app that caught the attention of the Colorado Secretary of State. Rather than traditional assignments where teachers dictate knowledge for students to absorb, this project centered students as experts in their own community's needs. And the lessons learned went beyond academics; one student confidently declared "I could run a tech company," while another reflected how "I care a lot more about things than I knew."

Are you ready to explore how AI might transform your classroom? Zach recommends starting in areas where you have expertise, focusing on low-stakes experimentation and remembering that the goal isn't to replace traditional skills but to elevate them. As we navigate this pivotal moment in education, teachers who thoughtfully adopt these tools aren't just preparing students for an AI-driven future – they're addressing fundamental questions about what it means to learn in the 21st century. 

Learn more about Zach Kennelly and DSST Public Schools:



aiEDU: The AI Education Project

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Episode Transcript

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Alex Kotran (aiEDU) (00:05):
so we're here at another early recording
of ai edu studios, with someonethat I've been really looking
forward to interviewing uh, zachcannelli, one of the first ai
trailblazers, which is a cohortof innovative teacher leaders
that we brought in as part of asix-month fellowship, and Zach

(00:30):
was someone who you know.
Very early on, we realized, youknow, this is exactly what we,
when we closed our eyes andenvisioned like, what could the
impact of creating this sort ofexperience for teachers be?
It's not just, you know,training and impact, but really
like creating champions who candrive this work for themselves,

(00:53):
and so I want to dive into that.
But, Zach, can you so welcome,Can you give us just like a?
You know it doesn't have to beyour whole story, but you know
how did you get into educationand then you can just tell us
about you know what you teach,where you teach, what your
school is like, to sort of helpus paint a picture of what your
day to day is.

(01:13):
I know that you actually have acareer shift within your system
that you can talk about as well, but maybe just sort of like
sharing up until that pointbefore you get to the sort of
like what you're going to bedoing next.

Zach Kennelly (01:24):
Yeah, thanks for asking First.
So excited to be here.
Really appreciate you asking meto be on, alex.
Yeah, what a journey.
So I do think a big part of thisstory is that my undergrad was
in political science andsociology at CU Boulder, and
then I went through TFA and didmath and science.

(01:48):
I got my master's in math andscience, and so I think that
broad training was reallyimportant to my passion for AI
because it allowed me to likeapply different understandings
of content and pedagogy withdexterity, and so that was
really important in that I hadtaught in middle school and high

(02:09):
school and math and science andsocial studies and civics, and
so really early on in thegenerative AI boom, I saw it and
knew that this really, reallymattered.
I had always been tech forward,but I hadn't been incredibly
focused on AI, and so thatprocess of seeing this really

(02:34):
matters for society, for youngpeople and for our system, and
especially what this means in acivic context, really ignited my
imagination.
And then I just started to playright, getting connected with
different communities.
Aiedu was a key community.
The Trailblazers cohort reallyallowed for me to connect with

(02:59):
people across the countrybecause originally it was
blocked.
Almost all AI use was blockedat DSST and I really understand
where that came from.
It came from a purpose-drivenplace, and so the opportunity to
push that was really powerful.
So I just mentioned DSST alittle bit about that.
Denver School of Science andTech we're a charter network in

(03:21):
Denver and focused on urban andsuburban, serving predominantly
low-income students of color andSTEM career fields had some
really great data come outrecently that our graduates in
the STEM field are earningsignificantly more than peers in
other fields, which is reallyexciting, and so we see building

(03:46):
AI competencies as a veryimportant part of ensuring that
the young people of Denver andbeyond are future ready.

Alex Kotran (aiEDU) (03:57):
And so you teach social studies.
That's right, my heritagepsychology and senior civics and
senior civics, not socialstudies broadly, but actually
civics, which is reallyimportant.
And when you say, like thisgenerative AI moment, what was
it like?
What was your first interactionwith generative AI?

(04:19):
Was it ChatGPT?
It was.

Zach Kennelly (04:22):
It was ChatGPT and Dali chat gpt, like when it
first came out, it was chat gptand dolly.
So I was on a fishing trip withmy father and jamming out to
some economist uh articles youknow audio version, and they
talked about this emergentcapability.
I had, you know, been listeningto a bit of what's happening in

(04:45):
generative AI.
This could matter, but as soonas the emergent capabilities
came out, that's where I wasexcited and curious enough to go
spend several hours trying tofigure this out and play.
And so right away I built animage on Dolly.
I remember running upstairs itwas like this beautiful hawk

(05:07):
over Longs Peak, which is areally famous peak here in the
Colorado Front Range and runningupstairs and showing it to my
wife and being like, oh my gosh,this is incredible.
The hawk had three heads.
So it was also very interestingin where it was precise and
accurate and where it was reallywrong and where it was messing

(05:29):
up.
Then also started to play withchat GPT and building out
different use cases in educationin my life I love to write, but
I also kind of struggle withsyntax and spelling.
I've always struggled with thatsince I was a little kid, but I
also love to write.

(05:50):
I scored in like 98thpercentile on analytical writing
in the GRE, but they don'tscore spelling and they don't
score grammar, whereas if theydid, I would have scored much
lower, and that was a hugemoment in my life because I had
always struggled as a writer.
I got like my best grade was aC in high school and so yeah,

(06:12):
that is a really important partof my life.

Alex Kotran (aiEDU) (06:14):
You don't expect me as someone I kind of I
would have assumed you were,like the straight A student.
That's right, yeah.

Zach Kennelly (06:18):
So no, I was a.
I was a football blockhead.
I only did enough school sothat they would let me put on a
helmet and go smash my head, andso actually that's an important
part of my story is like didthat and then went back to
college later and reallyembraced my passion for writing
and analytical writing,especially in political science,
and so what I really lovedinstantly about interacting with

(06:44):
chat GPT was being able to takethe incredible number of
thoughts in my brain and likeget them out quickly and help
them refine quickly using AI.
I was never super excited aboutlike AI doing things for me.

Alex Kotran (aiEDU) (07:00):
It was not ever really a big efficiency
play no-transcript part ofunderstanding sort of how we got

(07:29):
to this zeitgeist moment.
It's like it's jarring when yousee this technology thing
create language.
You know, when you ask it tosort of like, write an essay and
it produces an essay and you'rejust like it, it.
It manifested in a really sortof visceral way something that

(07:50):
was previously really arcane.
Right, like you know, machinelearning was around, like it was
touching our lives.
It was recommending the contentthat we consume, um, you know
google maps, machine vision, youknow it was in our phones, in
our computers, but it was mostlyinvisible, and I think also the
chat interface.
It made it something becauseit's like interactive and you
could almost have a conversation.
You can have a conversationwith it.

(08:13):
It opened the door to peoplethat weren't technical and, as
someone who also, you know, likeI, was a history nerd, in high
school, social studies, apEuropean history was my favorite
subject.
I love reading history and soyou know I'm a humanities kid
and you know language modelsbecause they are, you know,

(08:33):
working with language.
It was a.
It created for me a veryaccessible way to interact with.
You know this technology, um,so so you joined, you, you
joined.
How did you hear about the AItrailblazers.
Like did you just apply?

Zach Kennelly (08:48):
great question.
First, it's so great to hearabout your humanities background
, right?
I?
I kind of thought maybe the CSbackground, um, so I really I I
love seeing, uh, the way thishas grown for you, right?
I'd love to also at some pointhear how you saw the need for

(09:08):
AIEDU.
That said your question.
How did I hear about AIEDU?
I actually got on a podcastwith.
It was with Christian Pinedo,patty Quijones of Colorado
Education Initiative and AdilKhan and they invited me to.

(09:33):
Hey, I heard Zach's doing a lotwith this Hop on the webinar
and then saw Christian Pinedoand then I can't remember
exactly how that came about, butgot referred to AIEDU and
jumped in and applied and sograteful that that relationship

(09:56):
has blossomed and we've had theopportunity to work together.

Alex Kotran (aiEDU) (10:01):
Yeah, excellent.
So what was it like?
I mean, you had you had you hadan opportunity to sort of like
spend time with other educatorsprior to that, you know, in sort
of like a space whereeverybody's sort of like working
on AI together.
Is that like an opportunitythat you had in DSST?

Zach Kennelly (10:18):
Not at all.

Alex Kotran (aiEDU) (10:19):
What does DSST stand for?

Zach Kennelly (10:21):
Yeah, denver School of Science and Tech.
We also now have Aurora Scienceand Tech, a neighboring city,
and so, and this is a charter.

Alex Kotran (aiEDU) (10:31):
Is it a charter system or a charter
school?
Within a charter system, that'spart of the public school
district.

Zach Kennelly (10:37):
Yeah, you nailed it.
We are a charter network withina public school system, so DPS
is the umbrella.
We operate in DPS, we have DPSfacilities, dps transportation
and then we're a charter networkwithin.
There are also several othercharter networks.
So Denver has Choice, which isa really important part of our

(11:00):
story is the ability for youngpeople to choose where they go,
and we are a public charter, sototally publicly funded.
Anyone can get in.
We do have wait lists and ourSTEM mission has been a really
important part of that processand so, really on, even though I
teach civics and AP psychologyright away, I saw a natural

(11:23):
relationship, of course, withthe humanities, but also with
STEM and AI.
So I didn't have theopportunity to talk with a lot
of other teachers becauseactually it was blocked.
At DSST there were significantprivacy concerns.
There was a lot of questionsabout like how do students sign
in?
How is that data being used?

(11:44):
What are the risks, and I thinkall of that was right.
In the initial Trailblazerscohort, not only did we explore,
you know, ways to help youngpeople understand this content,
but also thought partnership andlike how, what are the risks?
How are other districtsapproaching this?

(12:04):
What are the ways that we cantalk with our district and help
them understand the way that I'mseeing this, and the way that
I'm seeing this is very much anequity issue.
We have to get young people theability to use this not
necessarily, you know, requirethem to use it, but build the
skills to use it so that theycan understand what they're
working with and the idea thatthese are very much going to be

(12:28):
the challenges the challenges ofthe age of AI are going to be
the challenges of the youngpeople that were in front of me
right then and I was teachingall seniors and I was looking at
them, I was playing with AI, Iwas understanding the potential
and I knew so many of them weregoing off to college next year
and were going to be competingagainst other people who were

(12:51):
learning about this and we'relearning how to leverage it and
we're learning how to use it andwe're learning about the
pitfalls and the opportunities,and so I felt really compelled
to get after it, incollaboration with this group,
and help DSST like really orientto the power and peril of
leveraging AI, so that we canput young people in a position

(13:12):
of power.

Alex Kotran (aiEDU) (13:14):
Yeah, and so you know, this is something
that we had spent a lot of timetalking about, and it was
abstract, right, Like the ideaof like, okay, what does it look
like to actually give studentsor create learning experiences
for students that allow them toboth engage with the technology
while also building skills, thedurable skills that we know are
going to be critical?
I guess it's a pun, becausecritical thinking is one of them

(13:36):
.
Yeah, what does that give?
Can you give an example of howyou brought that to life,
especially as a civics teacher?
Right, so you, you know.
I think most people assume thatyou know the place where you
teach students about AI is atechnology class or a computer
science class, and I don't knowthat they would necessarily
think of civics as a place whereyou do that.

(13:58):
And yet you figured out a.
Really you know like more thanone, but you know one really
powerful student project thatended up getting national
attention.
Yeah, can you share more about,sort of like, how you brought
this to your kids?

Zach Kennelly (14:12):
Absolutely.
So really early on.
Okay, so I've always had sortof this problem with the way
education approached both theinternet and social media.
Uh, I went to Columbine highschool down here in in Littleton
Colorado.
Um right, challenging andincredible experience.
So many people, uh, filled withdeep care, incredible educators

(14:36):
at the same time coming of agewith the internet.
So many people were like, don'tuse it same thing with social
media, we're not exploring it,just stay off of it.
Right, it's not, it's, it's notgoing to be helpful.
I really wish that I had hadmore educators in my life and in

(14:56):
all of our lives.
Invite us into a conversation,right, hey, this internet thing,
this social media thing, mightbe a big deal.
Let's think about theimplications.
And so, really early on, I feltcompelled to be that for young
people and I think AIEDUTrailblazers especially helped

(15:20):
me find a lot of that languageand approach.
And being a civics teacher, youknow I've taught civics and ap
psychology goes reallyinterestingly hand in hand.
So I've taught a lot about theinternet, social media, how
social media is so good at ourthe reward system in our brain
and so good at nudging us tomore extreme content, because

(15:42):
that's what's highly engaging,and that's how social media
companies tend to make money,and that there's some great
things about that, but there'salso some real perils about that
.
And so, right away withgenerative AI, we saw it as an
opportunity to invite our youngpeople into critical

(16:02):
conversations about theimplications for this technology
, way beyond the tech sector andin their lives, focused on
power and empowerment, and whatI mean by that is a gap that we
think is in CS education andengineering.

(16:27):
Education in general is like adeeper focus on the human impact
of these technologies, and sowe saw it as an opportunity, in
this STEM community, to help ouryoung people really think about
, you know, what are theimplications for the future of
civic society and the future ofhumanity when we're thinking

(16:49):
about this new technology thatcan generate, right now,
language, but it may be able togenerate a lot more as the
technology advances.
And so I wanted to positionyoung people as experts in their
lives, experts in the problemsof the community, and then be
able to work on those.
And I think what's reallyimportant about this you talked

(17:09):
about our big project is that weauthentically centered young
people.
What I mean by that is westarted out with okay, what is
power?
Then we helped them look at thetechnology, and this is where
we used a lot of AIEDU materials.

(17:30):
One of the best examples is the29 AIs of Washington DC

(18:05):
no-transcript plays out overtime.
And then we looked at you know,what are the implications for
human relationships?
We've worked with the RhythmProject for that and then we had
students build bots on PlayLaband these bots were actually
focused on their story, theirexpertise, and that came back to

(18:27):
when we were looking at power.
And then we put students intogroups.
We said okay, a bunch of youbuilt bots on voter engagement.
Do you want to build a voterengagement app for Colorado?
And students felt reallyexcited about this.
The thing that we're seeinghere is that so often we're
telling students what to focuson problems that matter to them,

(18:48):
and that's what happened withVote Wise, colorado.

(19:10):
Young people were focused onbuilding a voter empowerment,
voter engagement app.
We put them in collaborativeteams and they blew us away.
We thought it would maybe be afailure and it wasn't.
They built something incredible.

Alex Kotran (aiEDU) (19:24):
Yeah, I was just talking to this venture
capitalist who he had thisreally interesting idea, which
is, you know, the key topreparing students for the age
of AI is all about equippingstudents to basically be their
own CIO, and you know, what achief information officer does
in an organization is likethey're making decisions about

(19:45):
what technology the organizationuses.
And so his point was we need togive students the ability and
the skills to evaluate differenttools and um identify which
tools are the right fit for thegoals that they have.
Um and it sounds like you're inPlayLab for our audience is a

(20:06):
platform.
It's a nonprofit organizationthat allows teachers and
students to create.
If you've built like a customGPT, it's sort of like that, but
it's, you know, like a modelagnostic.
So was this an idea thatstudents had that you brought to

(20:27):
students?
Is this something that thestudents had sort of?
Was it their idea that theycame to you with?
How did you get from having thestudents just explore to this
very clear idea of what youwanted to help your students
build?

Zach Kennelly (20:41):
It's a great question.
Okay, so what we used to do?
We always used to do somethingcalled story of self us and now.
So our big thesis for a longtime was that the greatest way
to empower students was to teachthem how to tell their story,
or a story in a way that impactsothers, that can drive another

(21:02):
to action.
So we use Marshall Gans storyof self us and now and really
like drive that.
We thought that AI teachingstudents how to leverage AI was
a better way to help them tellpowerful stories, and so we knew
we wanted to do a projectinstead of our story of self, us

(21:22):
and now project, which we haddone for years.
We wanted to do an AI,human-centered AI leverage
project and students chose voterengagement.
So we had tons of things thatstudents proposed and built bots
around.
Students were really interestedin empowering immigrants with
information about how tonavigate our extremely complex

(21:46):
immigration system.
Students were really interestedin financial literacy
empowering folks with financialliteracy bots.
Housing is incredibly important.
Young people wanted to helppeople with housing and
identifying resources foraffordable housing, but the most
popular was voter empowerment,and so many kids were talking

(22:06):
about.
I have family members who areeligible to vote, who want to
vote, but the process feelsdaunting, and so they started to
build bots around it and weformed a hypothesis that we
could build an app that wasincredibly powerful that could
drive results.
We did have a secret ingredient, essentially, which is

(22:27):
something called Boxcar.
We had a local AI expertreached out to us wanting to
work with us, and he is trulymission aligned founder of Tin
man Kinetics here in Denver, andwhy this matters is we used
PlayLab.
We used Claude to build out ourprototype of the app Students,

(22:48):
genuinely, you know a room fullof kids just building out the
app in roles.
And then Boxcar was used tocode the back end, which is a
big challenge right now, whichis why we were able to launch a
enterprise grade web app from ahigh school classroom.
It's incredible, wow.

Alex Kotran (aiEDU) (23:11):
It was truly student driven.
So what's your vision for youknow what comes next.
I mean, you have one amazingyou know app that or a project
that students have really leanedinto.
But I think you have you talkedwith me, you know, when we were
at the ACO GSB Summit togetherearlier this week.
You have a lot of other ideasin terms of like how to continue

(23:32):
, sort of like leaning into thisway.
Yeah, what's your vision?

Zach Kennelly (23:36):
Yeah, it's a great question, OK, so two we
just wrapped up our second roundof this and students built.
We were focused on empathyfatigue.
So the problem that we startedto focus on is, because of
social media, so many peoplestruggle to empathize really
with folks, and we have a largepopulation of young people who

(24:00):
come from immigrant backgrounds,have immigrant family members,
and so many of these youngpeople are just like, oh my gosh
, my family is like suffering,my parents you know, they're
incredible people.
They've come here, they've gonethrough this, a lot of people
with housing insecurity, firstgen college student.
And so what they did is theyworked in teams to create

(24:22):
artifacts mostly on Claude thattell stories, to create
artifacts, mostly on Claude thattell stories.
So the idea is it's easy tojudge someone.
It's really hard to judge themif you see through their eyes
the choices they have to makeevery day, and that's associated
with sensory details to triggerempathy in the brain, and so

(24:43):
that's what students did andthat one didn't get as much
press.
It's not an enterprise gradeapp, but there's a lot to be
taken from it and studentsreally love telling their story,
and so what we're reallystarting to think is how do we
put this together in a way thatallows people to do this at

(25:05):
scale, because what we've doneright is it's challenging to
replicate.
You know, I've been doing thisfor a long time.
I have a broad set ofexperiences.
I had an incredible teachingpartner in Gianna Giraffo, who's
just like was in software salesbefore being a teacher, left,
you know, a much more lucrativecareer to come do this, and so a

(25:31):
lot of things came together forus to do this.
But we do believe that we cansort of lay a foundation and
collaborate with incredibleorganizations like AIEDU to help
other people do things likethis and ensure that people are
seeing that it's not aboutefficiency, it's not about doing
you know things faster or anold model faster, but it's about

(25:51):
empowering young people so thatthey have the motivation, the
desire, the imagination andcreativity and agency to solve
problems in their world anddrive impact.
And when that happens, we seethat it solves all these
problems around, like it reallyaddresses attendance problems,
interest problems, and sostudents can do great things and

(26:14):
they get excited about it.

Alex Kotran (aiEDU) (26:18):
Do you?
It's interesting that youmentioned solving attendance
problems.
That's not intuitive, but, youknow, absenteeism is a really
big challenge in districtsacross the country I think there
was one of the big districtsyou were talking to is like 40%
of the kids are not showing upto school, and this is like a
multidimensional challenge.

(26:40):
There's lots of things thatfeed into that, but one of the
consistent things that we thatyou see from surveys and the
research is that kids just don'tfeel like education is relevant
.
They just don't understand andmaybe even rightfully, are
seeing that, you know, the stuffthat they are being forced to
learn is just not connected withtheir day to day experience.

(27:02):
Experience.
But, yeah, what's behind the?
This phenomena of students,like you know, AI, actually sort
of like drawing students intoeducation?
Is it just that connection tosort of like what they are
actually experiencing?
As you know, digital natives?

Zach Kennelly (27:21):
This is such a great question, alex, because,
okay, so I'm observing now oneof my AP psychology.
One of them is first period andfirst period, like you know,
can be really challenging to getto all of those things, but my
attendance in my civics classesis stronger than AP psychology
and, like AP, psychology isincredibly interesting.
You know, we have greatattendance in those classes

(27:43):
overall.
But even at that scale right,this AP course versus this
highly creative course and we dosome of that in AP, but it's an
AP curriculum, right, I'mreally focused on the curriculum
, and so what I think we'reseeing is when we position young
people to work on things thatthey choose as relevant, while

(28:05):
also building the criticalthinking agency, creativity,
imagination and technical skillsto create it solves the
challenge, just like you said,of relevance.
We've known, right, for I don'tknow a really long time, that
relevance matters.
I was just teaching Piaget andyou know, context In context,

(28:28):
learning matters, and so, when Ithink about this, I think the
biggest thing that we've beendoing, and with good intention,
is lying to young people andtelling them that the process to
success is doing what you'retold.
Do what you're told.

(28:49):
I'm going to tell you how well,you did it.
I'm going to give you a gradeand then if you do what I told
you to do, you're successful.
And kids are saying I don'tbelieve you and they're starting
to see like actual, realsuccess is our ability to see
challenges in the world andaddress them relentlessly,

(29:12):
iteratively, and collaboratingwith people and AI.
And so where I see AI cominginto this and I've heard some
people who are critical aboutlike the lower friction I don't
want to lower friction oflearning, but I do want to lower
the friction to collaborateLike to be a great teacher in a
problem-based setting isincredibly time intensive.

(29:37):
Right To set all the things up,to do all the grading, to give
all the feedback On our projects.
We gave zero grades, not one.
Students graded each other andit turns out they grade each
other harder than we grade andthe authenticity is deep and
rich.
And so what I think is thethesis here is we position young

(30:02):
people to work on things thatmatter, we equip them to
collaborate between each otherand on with AI, and then they
are accountable to one another.
But, most importantly, thatauthentic audience right, it got
really real for them when I'mlike, hey, the secretary of
state just called and they'vegot some feedback.

(30:22):
Those types of moments are sopowerful.
Hey, the CEO just reached outof DSST Public Schools, nella
Garcia-Urban.
She used our app to vote.
She'd love to celebrate y'alland tell you about her
experience.
Those things fueled our youngpeople in a way that I haven't
seen in my 14 years of education.

(30:43):
We've done a lot of reallygreat things, and so that's one
of the things that keeps me onfire about this work is the
opportunity to position ouryoung people to be creators, to
work on things that matter themost to them, and to get away
from so much of the narrative oflike what's wrong with the
young people to let's create asystem that empowers them to do

(31:06):
things that they love and careabout yeah, this was um, like
victor lee at stanford did someresearch and one of the things
that really caught people'sattention is they found that
this assumption that chat gbt iscausing students to cheat more
is is flawed.

Alex Kotran (aiEDU) (31:26):
It's actually that you know students
are using chat GPT to work ontheir homework and you know, at
least for me, I think it'simportant not to write off, like
when teachers are statingconcerns about that they're like
we should trust their instinctsand the answer isn't just like

(31:47):
oh, you know, you just have toallow students to use chat gpt
and be okay with it.
Um, you know, I think there'sthat's a conversation I want to
have with you about.
Like, what is, what doesguidance look like to educators
who are trying to think aboutthat?
Um, but victor's researchreally suggests that the rate of
cheating is about is still thesame as it was before.
In fact, historically it reallyhasn't changed that much as

(32:09):
different technologies come inand even, like I think with
Chegg, they had I forget exactlywhat it's called, but you can
go to the back of you can getanswers to a lot of, like the
homework assignments.
Do you know what I'm talkingabout?
This is like oh, I know exactlywhat you're talking about.

Zach Kennelly (32:24):
That's exactly right.

Alex Kotran (aiEDU) (32:30):
But ultimately, the root cause of
cheating is that students don'tfeel like what they're learning
is relevant um, they feel likethey're just being given busy
work and um, and so that's.
That's encouraging, insofar asit shows a path to how we
address this.
It's it's not that we need toentirely ban AI or, you know,
completely change the way weteach, but it does mean that

(32:53):
there's an opportunity to evolve, maybe how we teach, and you
just described maybe one reallycogent and sort of vivid example
of what that could look like.
But I think the cool thingabout this technology is that
any teacher, no matter theirsubject, um, as long as they
know how to use the tools, theywill be able to.

(33:14):
They can both design, you know,assessments and and projects
that, uh, the the tools bythemselves can't just solve on
their own, um, but in fact,teachers can probably use the
tools to help them in thatendeavor.
Um, which is sort of like themeta aspect of the technology is

(33:36):
, like you know, I don't believethat ai is going to solve the
problems that it's going tocreate.
I'm not a techno optimist tothat extent, um, but maybe I'll
put it a different way and I'mcurious for your take on this, I
I feel like the.
The only solution to cheating isfor teachers like, like right
now, the the, the fact thatstudents are able to use AI to

(33:57):
get it like around theirteacher's assignments.
It's coming from the fact thatthey are just more experienced
in the tools than their teachers, and so the teachers are at a
disadvantage, because it's veryhard to design like a, an llm
resistant homework assignment ifyou don't really understand
what it's capable of.
And I see this with, like youknow, teachers who say, oh,

(34:19):
there's, like you know, I put atrojan horse in my assignment.
This is, like you know, theidea that you, if you have like
a writing prompt, you in, like,you add like white text and like
white font, you know somethinglike, oh, add the word
Frankenstein somewhere in the inthe output, and that probably
works for a period.

(34:39):
But then the kids figure it outand they are utilizing, you
know, social media andcommunication tools that will,
you know, allow them to quicklyget ahead of that, and so these
are just band-aids.
The only thing that a teachercan do to really stay ahead is
to make sure that theythemselves are, you know,
proficient, if not power users.
I don't know that they have tobe power users, but they have to

(35:00):
know what the tools can andcan't do.
Another example is when I heareducators say, oh well, I just
have students.
Uh, you know, I say it's okayto use chat gbt and then I ask
them to critique the outputs.
Um, so, like you know, likehave the ai, create an output
and then, like you know, sort oflike, go through and identify,

(35:22):
you know, the mistakes or, youknow, provide some commentary or
another example ofself-reflection, and to me that
just demonstrates that teachersdon't realize or haven't really
thought that like thought a fewsteps down the the road where
it's like you can just ask chatjpg to critique itself, um, you
know, that's literally just oneextra prompt that you like, sure

(35:45):
, like you've added a step, um,but by itself, you know, and and
a self-reflection is the samething.

Zach Kennelly (35:50):
You can.

Alex Kotran (aiEDU) (35:51):
It's not that hard.
It maybe takes a few extrasentences in the prompt
engineering.
It's not maybe a singlesentence prompt, but you can
probably get a pretty damn goodreflection, and and maybe you
and I disagree about this I'llmake a statement that you can
react to.
So I really believe that youtalked about friction.
I'll reframe it as likeproductive struggle.

(36:13):
I think what teachers aregetting right is that AI does
make it easier for students toshortcut work, the result of
which can mean that they're justnot going through the
productive struggle that we knowis so critical to their
development as learners.
And so like for me, as someonewho did a lot of writing in

(36:35):
college and high school, youknow sitting in front of a blank
piece of paper and strugglingwith, like, how do I start this
essay?
How do I get what's in my headonto that piece of paper?
It is the hardest part ofwriting, but it's also like the.
Maybe the most important partis like building the.
You know persistence to, to getpast the writer's block, and if

(36:58):
your instinct is always just tolike, oh, I'll just open up
chat GBT and have it create anoutline, and then I'll like, go
through the outline and providesome feedback and then boom, I
have like in a first draft andI'm editing the draft and that's
.
And actually I was just so thethe same vc that I mentioned
earlier.
Like he, his model is he has twodifferent lms create outlines.
He shares each outline with oneanother and then he has them
sort of like, incorporate themand create the better you know,

(37:21):
create like a revised outline,and then he gets the draft.
Um, but even that I, you knowhe and I were reflecting that
part of why he's effective atprompt engineering and using AI
to help him write is because hewas already a really good writer
.
And I worry about students thatyou know, before we get them to
use AI to augment theirabilities as writers, they need

(37:43):
to kind of build that corewriting expertise.
And I think it's different thanprompt engineering.
Right, you know writing isnecessary to be able to prompt,
but it doesn't necessarily goback and forth.
I don't know that if you justlearn prompt engineering, that
you're now also learning, sortof like, all the core skills in
writing.

Zach Kennelly (37:59):
I completely agree.
Okay, that statement Okay I washoping you would disagree, but I
but I have.
I have a lot of nuance here.
So the first thing I have tosay so I'm very lucky in that my
mom was an early an ECEeducator for many years,
director, right.
My sister is a K through fiveinterventionist, but she was a

(38:19):
kindergarten teacher for manyyears.
Three kids I've got my son,like he is learning to read with
paper books, and so I do reallybelieve, exactly like you said,
the daunting experience of ablank page and having to create

(38:41):
that matters, um, the bigchallenge that I have.
So the first thing I would sayis, like reading and writing and
math are as relevant as everand possibly even more important
.
I want to say, okay, so I thinkSocratic circles, right, that
required deep analysis.

(39:01):
Those types of things are asimportant as ever.
Types of things are asimportant as ever.
I also think, exactly like youright, that expert writers are
the ones who are able to havethe taste needed to
differentiate with AI, and so,at the same time, we have a huge
problem in education and that'sthat people don't get feedback.

(39:24):
And so, in addition, if I wereto like really put all of my
theses together into, it'd belike essentially two, maybe
three buckets.
The first is like impactfocused, human centered AI
leveraged creation.
For young people, that'sespecially in subjects like
history, stem, science, right.

(39:47):
These kids should be creatingmore.
Reading and writing areessential, and the best use that
I have seen is immediatefeedback.
Now I do art.
I can see people saying, well,the immediate feedback can slow
things down.
I've used class companion.

(40:09):
I've seen folks working onQuill, really curious about
Quill.
Both of those like I candefinitely vouch for class
companion.
The reason I vouch for it andthe analogy I love to use is
like kids who shoot free throwsand then they find out two weeks
later whether or not it wentthrough, and I have a really
large number of MLL learners whoreally need that feedback right

(40:33):
away.
So two places that I use AI forwriting is I help build sentence
frames and exemplars Like thisis something I'm an expert in,
but it takes an incredibleamount of time.
So sentence frames areessentially like the mortar
language the language that holdstogether the content expertise

(40:53):
students have.
A lot of MLLs need support withthis, and so we want to use it
as a scaffold.
They use it and then they moveon from it.
I use AI to build those.
That's a huge use case.
The next is immediate feedback,and so that's where young people
get feedback right away ontheir writing and impact.

(41:14):
It impacts their ability toimprove faster, and that's an
extension of me.
Like, I don't want the AI toown that.
I want to be able to create theconditions for what type of
feedback would I give, or wouldhopefully somebody better than
me give, and then help thatyoung person improve faster?
And so there are a bunch ofplaces where, like kids using AI

(41:38):
to write especially really fromK to maybe nine or until they
develop some place ofproficiency, will undermine it
long term.
And so, yeah, I really agreewith that and I have pushes
around like how do we supportyoung people leveraging AI in a
way that was never possible?
How do we give feedback fasterin a way that was never possible

(42:01):
?

Alex Kotran (aiEDU) (42:03):
Yeah, one of the.
So you hit on something that Ithat opened up my mind about how
to think about this, and it waslike if you think about other
technologies and how theyimpacted the way we learn.
People talk about the calculator, which maybe it's an overused
analogy, but it's also, I think,quite apt, because I don't

(42:25):
think anybody would say that thecalculator you know, prevented
us from teaching math, but itcertainly changed the focus from
being just, you know, goingthrough like the raw arithmetic,
to problem solving and showingyour work, and so that was like
a.
Really that's a narrow tool andso maybe it has a narrow

(42:45):
solution.
That's a narrow tool and somaybe it has a narrow solution.

(43:10):
But I was actually doing some.
I used the deep research toolon chat, gpt and Gemini's
research tool as well, and thequestion I had was is there any
evidence that, or like whathappened to the volume of
writing before and after?
After uh, students had accessto, like you know, uh, computers
and keyboards, um, and yeah, itturns out like, if you go to
like the 1980s and then compareit to like the 2000s, like the
2010s, it's like uh, long formwriting the, the, the average
length increased by three tofive x.
So before it was like about, Ithink, per week.

(43:30):
So, like I think before it wasabout like a half a page per
week of of writing, um, and then, after the computer, you're
getting to, you know, uh,multiple pages per week, um, so
the volume increased, but that'sbecause it was, you know, in
the same amount of time, you'reable to write more um and so
whatwhat you're able to write more,

(43:54):
and so what you're describing isalmost like thinking about what
the next iteration of that willbe, where you know the homework
assignment might not just be towrite a self-reflection or to,
you know, to write an essayabout the importance of voting.
You know to write an essayabout the the importance of
voting, um, but rather what youdescribe right is like a project
where you're building an actualapp, uh, to help people

(44:16):
register to vote.
And you know, five years ago,if you described that project to
a teacher, I mean how would youdo it?
It would be like.
I mean, it's like, maybe likeyou know one out of a hundred
kids would would have theresources to be able to figure
that out.
Have to know yeah, that'sexactly, if you're lucky, right?
Yeah, you'd have to know how tocode.
You'd have to have, you know,the tools to be able to, like,

(44:38):
deploy the application.
So, but it does mean raisingthe bar Big time.

Zach Kennelly (44:49):
Yeah, I really love what you just said.
Right, I've got some things toshare.
A couple of my favorite quotesYoung woman like been through so
much right Incredible level ofpoverty, deep trauma, straight.

(45:12):
A student also has her ownbusiness.
So like, as as incredible ahuman as exists.
Her statement at the end ofthis so simple I care a lot more
about things than I knew.
And her statement from thatcame from like analyzing these
really charged ballot measurestatements in Colorado,

(45:36):
informing opinions around themCame from taking ownership of
how people vote.
Another one incredible youngwoman I could run a tech company
.
I could run a tech company.
I could found a tech company.
And you're like, yes, that Ienjoyed working with other

(45:58):
people to do something thatwhere nobody told me how to do
it.
We started and and we said, hey, we actually don't know how to
do it.
We started and we said, hey, weactually don't know how to do
this.
Like, we're really goodteachers, but I never done
anything in software developmentever.
We want to go on a journey withyou.
Let's get in on this.

(46:20):
Like you're invested in thevoter education.
We're in voter empowerment.
We're invested in voterempowerment.
Let's go make this happen.
And that was incrediblyinvigorating for kids, because
so often we say, hey, here's allmy knowledge as a teacher, let
me just deposit it in you, andwe act like that's not true, but

(46:46):
like it's a huge tenet ofmodern education.
And so meeting young peoplethere as peers and saying, hey,
I know that you have a bunch ofexpertise here and we could
build something special, likelet's do this together.
I think there's a lot ofopportunity there and I think
it's going to be really hard fora lot of educators across the
world and across the country tosay I am okay, not being the
keeper of the knowledge, and weare here together to do X, y, z,

(47:11):
um.
And I think it's really specialand I feel really excited about
the opportunity to do that.
And I don't think it's all ornothing, right, I think it's.
It's you know, we we've got.
I love the analogy of thebridge right.
When we, uh, build a new bridge, we keep the old bridge up
while we build the new bridgeand then we transition.
And I see us very much at thismoment, right now.

(47:33):
Right, we're trying to spanthis gap.
We know the future is going torequire new skills.
We've got this giant system andso we've got to be able to do
both at the same time.
You know, build reading, buildwriting.
Both at the same time.
You know, build reading, buildwriting support.
Help kids build the currencythey need for things like an SAT
score, while also inviting themto be creators of the future

(47:57):
they want.

Alex Kotran (aiEDU) (47:58):
The bridge analogy I love.
I love my analogies.
The bridge is cool because it'slike, if you know you're going
to need a new bridge, you needto start building it, and that
doesn't mean that you knock downthe old bridge right away.
And so I think, for folks whoare trying to make sense of
their instinct about well, it'snot that, you know, I push back
on this whole idea of like weneed to revolutionize education,

(48:18):
because I think there's, youknow, the Silicon Valley mindset
of like, move fast and breakthings doesn't work in education
.
But this is one of those placeswhere we need to move fast.
I don't know if we need tobreak things, but we need to
move fast and like, start, youknow, start building and
learning, um, because at somepoint you're going to need that
new bridge and you don't want tobe, and it takes time.

(48:40):
You know bridges, which is alsowhy I like this analogy.
It's like it's not somethingyou can do overnight, um, and so
, even if you don't necessarilyhave all the things that you
need you may not have all theconcrete like, you could still
start building the scaffoldingand taking this a little bit far
.
But yeah, I think it's a reallygood analogy.

Zach Kennelly (49:00):
I think it goes really far and I think helping
educators know like you don'thave to shift everything
tomorrow, but if you want to,there's a huge opportunity there
.
Or if it's just introducingincreased feedback or if it's
just making things more relevantfor kids, right?
I, you know, on PlayLab, builta bot for AP, psychology, AAQ

(49:25):
questions, article analysisquestions.
It's a brand new curriculum.
I love the curriculum shift,but there was this huge obstacle
I was facing as a teacher.
In one drive to work I usedchat, GPT, voice to generate a
prompt.
I then got to work and put thatprompt into a PlayLab bot and I
have continued to generatethese highly relevant articles

(49:48):
that I give to students rightaway, and the reason that
matters is it's directly relatedto what we're learning then.
So students are more interestedand I think educators can start
wherever they are.
But we all have to start, andthat's one of the things that I
really appreciate about AIEDU isgiving people the spot to start

(50:10):
.

Alex Kotran (aiEDU) (50:13):
So what does it look like for someone
who's listening, whether they'rea teacher or a parent?
How do they get started?
I mean, I think it's likesometimes just getting the
wheels turning is the hardestpart, like, what advice do you
have as someone who I don't knowif you consider yourself a
super user, but certainly apower user of generative AI?

Zach Kennelly (50:34):
It's a great question, Alex, and I would love
to hear your perspective here.
The one thing this is actuallythe title of Eric Liu's book.
He's a big part of it.
We teach students about power,but it's you're more powerful
than you think, and that is, Ithink, helping people see like
you are more powerful than youthink.

(50:54):
Leverage AI to do what you wantto do.
When people see it I think it'sthis like daunting thing that
they have to go learn.
It's scarier versus if they seeit as this thing that can
accelerate the things that theycare about, that can help them
be, you know, a stronger, morepowerful version of themselves,

(51:17):
then it's really wonderful.
Right?
It's not about using what theAI generates.
It's about taking command andmaking the AI generate what you
want, and so helping peoplereally see that they are
powerful and that it islearnable.
If we compare those two things,people will be able to do
special things.

Alex Kotran (aiEDU) (51:38):
Yeah, I'm trying to think of how to get
even more practical and I thinkit's like Good, good for you.
I think it's like I watchingthis, this expert on language
models, um, and he wasdescribing what cyber security
is like in the day and like inthis, in this sort of age of of
language models and generativeai and cyber security is

(52:02):
basically people just sort oflike playing around with these
tools and sort of testing themout and seeing different like
what types of prompts will likeget you know what happens when
you try different types ofprompts and um and and in
abstracted, the advice wasbasically the.
The key to to using anygenerative ai, but specifically

(52:26):
language models, is um.
You have to be using it in someplace where you have expertise,
because you need to be able toknow, because you know it's
they're, they're.
They produce amazing things,but a lot of times they produce
stuff that's wrong.
They make stuff up and, moreimportantly, they are really
good at sounding confident,regardless of how correct or
incorrect they are.
Um.

(52:46):
So it needs to be in an area andit doesn't matter whether it's
you know, basket weaving orhistory or sports or art or
literature I mean using it in ain a domain where you have some
expertise is key and then theother piece is experimentation
um I don't know if there'sanything else.
I don't know there's likeprompts to memorize.

(53:07):
I don't know if there'sanything else, I don't know if
there's like prompts to memorize.
You know, at the end of the day, like you know the best the way
to learn prompt engineering isjust ask the language model.
Hey, this is what I want to do,like how can I prompt you to
get the best output?
And it'll literally tell youlike step by step, here's the
things that it'll say, thingslike give me some context.
And you know, um, one thingthat works with some of like the

(53:31):
older models, not thepre-reasoning models, is, you
know, have the llm sort of takea persona.
So if you're trying to write,let's say, like a history paper,
you say, oh, you're a expert in, you know us history or uS
government.
That's less necessary now withreasoning models, because they
actually do some of thestep-by-step work for you.

(53:51):
In fact, when I was doing myresearch about you know the
volume of writing you know Iasked for you know, this is what
I want, and it actually sent abunch of questions.
It was like do you want me tofocus specifically on K-12?
Do you want to look at the usor are you open to sort of
international uh, you knowresearch in other countries?

(54:12):
Um, like, what's the timeperiod that you're looking for?
And, um, you know, I think inthe past you'd have to sort of
like add all that contextyourself.
Yep, so, so it's less aboutlearning all those specific tips
and tricks, but but rather justsort of like trying things out,
and what you'll find is often,you know, honestly, 75 of the

(54:34):
time it's faster to do it, tojust do it yourself.
You know, it's not that youneed to change the way you work
and incorporate ai in everysingle piece.
I think this is the case foreducators.
It's, uh, it's, it might not befaster to write a lesson plan
with ChatGBT, because you mightwrite what, you might have a
create one.
You look at it it's like, oh,this isn't very good, and you
spend some time giving itfeedback and by the time you go

(54:55):
back and forth and back andforth to get something that's
good enough to your standards,you probably could have just
written the lesson plan yourself.
But in the process you start tofigure out ways where it can be
helpful, and so maybe it's notwriting a lesson plan, but you
might say can you and I thinkyou mentioned brainstorming.
It's like enlisting as abrainstorming partner.

(55:18):
Hey, I'm trying to write alesson plan about you know
connecting these two topics.
Let's say, you know, let youknow to give your example.
Uh, you know voting and civicsand I want it to be something
that students are.
You know creating some kind ofa project.
Um, you know, you have yourmodel and format for what you
want to do but it.
But you just say, give me like10 ideas and you go through and

(55:39):
maybe all 10 are bad ideas.
But the process of like doingthat, you might think of a good
idea yourself where you mightsay, hey, let's double click on
this one, like can you revisethat a little bit?
And in many cases it's stillnot going to be faster.
I mean, this is the thing islike don't, don't expect it.
It's not going to necessarilybe more efficient or faster
right away, but you will startto find some places.
You know like for us it was insome places.

(56:04):
You know like for us it was yep, we don't.
I do a lot of work.
You know engaging funders andlike school district leaders and
we write.
You know mous, and what wefound is ai is really bad at
writing.
You know a personalized email.
You can use it so you can sayhey, I want to write a
personalized email to zachkennelly, or kennelly, um, he's
a teacher at dsst.
And he'll say like salutation,zach, you know I'm writing on
behalf of the ai educationproject, a non-profit.
And it'll say like salutation,zach, you know I'm writing on
behalf of the AI educationproject, a nonprofit.

(56:24):
And it's like, you know, like Icould spend time saying, oh
well, I don't know, zachactually knows who we are and I
want it to be like, by the timeyou go through that process,
it's faster for me to just writean email.
But if I'm writing an MOU and Ijust need a, you know, a
succinct section describing ourwork and how it aligns to, uh,
this strategy that the districthas, and you sort of upload the

(56:46):
strategy that can be, that canbe really effective, right and
like.
The same goes for likefundraising and like writing
grant applications.
Um, if any of our funders arelistening, like I hate to tell
you, but like a lot of our grantapplications are, um, you know,
heavily influenced by ai, butwe have not just a human in the
loop but a human in the driver'sseat, like holding the steering

(57:07):
wheel with both hands, and sothat means, you know, sure,
using it to get a draft and tosort of like get past the
routine aspects of the writingand content creation and getting
focused on how do we make surethis is in the voice of our
organization, that's reallytruly aligned with the goals
that the funder has.
Um, but you know, writing aoverview boilerplate section at

(57:29):
the top of the grant, that's notreally and funders don't
actually care about that right,like they're looking for
something that is, you know,meeting their needs in terms of,
like, clearly describing thework.
Um, so what do you?
What like?
What keeps you up at night interms of there's a lot that
keeps people up at night with ai, but in terms of, specifically,

(57:50):
like your students and likeyou've seen a lot of amazing
stories of that are inspiring,um, but are there any things
that maybe people aren't talkingabout as much, that you think
need to be on educators minds asthey sort of start to use these
tools and become more familiarwith them?

Zach Kennelly (58:07):
Definitely.
So just about I'm going to liketie these two together.
And the first is so like earlyI built a prompting framework
like RCCP method role, context,content, prompt.
I've like turned that into RCCP, which is role, context and
content together in prompt.
I've like turned that into RCP,which is role, context and
content together, and prompt,and like it will change with

(58:28):
reasoning models and things likethat.
But I do think, like you said,prompting is going to continue
to keep people at the front end,and so it's like it's an
incredibly valuable thing tolearn.
And the reason I say that isbecause at some point there's
going to be real trade-offsEither you're going to be really
good at prompting or you'regoing to have to give up your

(58:48):
privacy to use AI, and, like Ido think AI will get better at
that at just intuiting thingsout but people will have to give
up quite a bit of privacy toget that.
And so this is, I wouldencourage people, just like you,
to start prompting, start usingit.
I love the area of expertise.
The next is I don't thinkanybody is getting very much

(59:11):
from AI unless they're usingcustom bots.
Right On Claude, this isproject Gemini gems custom GPTs.
I had this great experiencetoday.
Just like you said, a grantapplication I was planning a
professional development and,like a year ago, I had built a
professional development bot,trained on massive amount of

(59:32):
like DSST, strategic plan, dsstvalues, a bunch of projects I'd
done.
I was able to go in give abrief set of context and had
this.
I was able to go in give abrief set of context and had
this amazing professionaldevelopment in like 15 minutes.
It was exactly what I wanted.
You know, I changed some of thecase studies, et cetera.

(59:53):
The power for so many people islike first learning to prompt,
then understanding how to scalethat through a custom, a custom
project.
So that's the big thing.
What keeps me up at night isthe accelerating inequality that
is such a huge risk here thatpeople who are really effective

(01:00:14):
at leveraging ai, companies etc.
Are going to be able togenerate massive amounts of
value, even if it's like, evenif they're spending the same
amount of time, they're creatingmore and better in that amount
of time, and the people who arenot just become consumers, who
are entertained by it and arenot capturing value.

(01:00:36):
And so the acceleration ofinequality in the age of AI is
one of the biggest concerns thatI have Acceleration of

(01:01:01):
inequality.
In a time of acceleratinginequality and hopefully it can
be a time of acceleratingequality and that is what keeps
me up at night and a big part ofmy mission and why I'm a public
school educator, similar toy'all.
I love your focus on rural andbringing people together.

Alex Kotran (aiEDU) (01:01:34):
I love your focus on rural and bringing
people together is like how dowe ensure that we don't leave
more people behind with thisextraordinary opportunity to
democratize, or of many?
I know that you're embarking onsort of a new chapter in your
own career and, you know, onceyou've had some time to get your
sea legs, I'd love to, you know, check back in and kind of hear
your perspective.
You know, from sort of like aslightly higher vantage point,

(01:01:56):
but you know this reallyresonates.
You know, if if we're going toassign more writing, have
students write five pagesinstead of one because they have
access to a computer, if astudent doesn't have access to a
computer, they're going to fallbehind, and I think the same
goes.
You might say, okay, we're justgoing to increase the volume or

(01:02:16):
make the project morecomplicated or challenging.
Knowing that students are usingAI, there's this assumption
built in that there's sort ofequal access and that which is
why this is so it's allconnected.
You know school is thinkingabout how do we make sure
students have access to AI toolsand have the privacy and the

(01:02:36):
safety policies in place?
Those are connected to teachingand learning.
You know the questions aroundteaching and learning as well,
zach Cannelli, thank you so muchfor joining us.
I know this is a Friday.
You're probably getting readyfor the weekend.
You're one hour ahead of me, sohopefully you have some fun
plans in store.
But it was really fun hangingout with you in San Diego and

(01:02:58):
I'm looking forward to the nextof many conversations with you.

Zach Kennelly (01:03:03):
Same Alex Cotran, aiedu man so excited about this
relationship.
We're really grateful right forthe opportunity to think deeply
and have this conversation andbe a part of the movement to
empower folks leveraging AI inthoughtful, responsible ways.
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