A curious mix of chance and trying hard; who would have thought? I am very grateful to all those who helped me along the way.
I learn by the seat of my pants, making lots of mistakes, never repeating them. Being self-educated is great. So is listening, asking questions, reading print books, learning to use tools to make things, challenging every assumption,"strong opinions, weakly held", subject to change as factual evidence emerges via robust Science. We are all capable of doing this.
We are all smarter than we give ourselves credit for.
Mike is the inventor and architect of Pipi and the founder of Ajabbi.
I have been very lucky. I have had a lot of people in my life who were a good influence on me. (I get rid of anyone who sabotages or is a bad influence)
My grandmother Bessie showered me with attention and love, gave me endless things to pull apart to see how they worked, and took me to meet very clever people in a small-minded backwater town.
Family holidays in wild New Zealand, next to rivers, beaches, forests and mountains, which ignited a lifelong obsession with the patterns of nature, the why in my life.
My best friend right through school; he was the brightest kid in NZ.
My high school science teacher, Alan Morgan, let me play in the chemistry lab, doing experiments after school unsupervised for several years, and taught me the scientific method on my very last day at school, the most important thing I learned in 12 wasted years.
The wise old tradesmen, who took a skinny kid from sweeping the floor to being able to make anything, by learning on the job, trying hard, and having my butt kicked.
Nelson Mandela taught me to have the courage of my convictions and never give up.
The sculptor Neil Dawson and the set designer Tony Geddes taught me how to work authentically.
My blind friend Grant, who made and gave away $60 M NZD, taught me, while he was cutting down bushes with a chainsaw, determination, quiet courage and human decency.
The magnificent 50,000 working people of South Christchurch, who trusted me to lead a volunteer residents army doing recovery work for 3 years, after the Christchurch Earthquake, teaching me humility, what honour is and valuable leadership skills gained by trial and error in the moment.
My beloved Tracy, the bravest woman I have ever met, the only paraplegic to do the Coast-to-Coast Iron Man, who married an undomesticated autistic male and made me a much better man. Her unwavering devotion, encouragement and loyalty made all this possible.
They all shaped me; I can't thank them enough. May their memories be a blessing.
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Last Updated
24/04/2026
"Intention is what we need": Neeru Khosla on the Future of Education and
Learning with AI
By: Kesnia Se
Turing Post: 18/04/2026
Over two decades in tech, with the last seven years focused on ML and AI. Our analysis stays precise and grounded. Our educational series walk you through the foundations and help you explore the deeper layers. We trace the arc of AI – its past, its present, and the direction it’s pulling us toward. We track the research that matters, the systems being built, and the ideas that define how AI actually works. And we break it down with clarity, so you can make better decisions. Join 100,000+ professionals who rely on Turing Post.
Neeru Khosla is the co-founder of CK-12 Foundation, a nonprofit focused on free, adaptive learning materials for students and teachers. In this interview, she explains why AI in education matters less as an “answer machine” and more as a way to understand how students think: what misconception they hold, where they are confused, and what kind of support can help them learn more deeply. CK-12’s AI tutor, Flexi, is built around that idea, using AI to support personalized learning, knowledge tracing, and student curiosity at scale.
How the CK-12 co-founder thinks about using AI to rethink, personalize, and
gradually change the education system
Attention is what taught the machines. But now, in this AI world, we need
to have intention and judgment. Intention is what we need.”
I loved that conversation with Neeru Khosla, co-founder of the CK-12
Foundation, a nonprofit focused on free, adaptive learning materials for
students and teachers. She articulated one of the most important shifts now
unfolding in education. For years, digital learning has focused on access:
more content, more devices, more formats, more scale. But Neeru’s point is
that the real shift brought by AI is the possibility of understanding how a
student is actually thinking – where they are confused, what misconception
they hold, what question they are really trying to ask, and what kind of
help might move them forward.
Khosla has been working on this problem for nearly two decades. CK-12
started with an idea to make high-quality learning materials free, flexible,
and adaptable to the needs of individual students. Long before the current
AI boom, the foundation was already building multimodal learning tools,
adaptive systems, and concept-based content designed to meet learners where
they are. But as Neeru describes it, the missing layer was always insight.
Schools could see whether a student got something right or wrong. They could
not easily see why.
That is where the last three years changed everything. In Neeru’s view, AI
is not most interesting as an answer machine.
“Just knowing that the answer is right or wrong doesn’t tell anybody
anything.”
It is most useful when it helps surface the learner’s internal process. A
question like “How does the sun burn if there’s no oxygen in space?” is not
just a cute moment of curiosity – it reveals a specific misunderstanding
that a good tutor can work with. This is the logic behind Flexi, CK-12’s AI
tutor, which Neeru says has already been used by tens of millions of
students and has processed more than 150 million questions. No one needs
automation for its own sake. New tools give us the ability to trace learning
more deeply than standardized testing ever could.
But there is a lot of fear in the system. Our conversation moves well
beyond product and platform design. We talk about why schools often resist
free tools, why they now resist AI tools, why teachers need open-mindedness
more than technical fluency, why AI literacy may become as foundational as
reading and writing, and why creativity, critical thinking, collaboration,
communication, and community remain the real non-negotiables. Khosla also
makes a broader argument: education is one of the few places where society
cannot afford to treat access as optional. If AI is going to matter in the
classroom, it has to help more children learn more deeply – not just help
the most privileged students move faster. She argues that if the US wants to
maintain its lead, it needs to rethink education and how it is
delivered.
There is also something personal and unusually grounded in the way she
talks about all this. Neeru came to education from molecular biology, then
spent years in classrooms watching children learn one by one before building
CK-12. That background gives her a practical lens on both technology and
human development. She is enthusiastic about AI, but not dazzled by it.
Again and again, she returns to the same principle: tools matter, but what
matters more is whether they help us show up – for students, for teachers,
and for one another.
Neeru believes in two AIs: Augmented Intelligence and Amplified Intention,
and I’m 100 percent agree with her.
As I keep saying, AI literacy is extremely important, and this conversation
is a great way to learn how to move from fear to understanding. Please watch
it and share it →
YouTube video by Turing Post
AI Could Change Education Forever – Neeru Khosla Explains Why
Edited interview transcript
Ksenia:
Today I’m very honored to speak with Neeru Khosla. She is an entrepreneur
and philanthropist known for her work in education and social impact. She is
the co-founder of CK-12 Foundation, which provides free, customizable
learning materials to students and teachers worldwide.
I’m very passionate about education, especially in this new era of AI, so
thank you so much for joining me.
Neeru:
Thank you for having me.
Ksenia:
This podcast is called Inference – because we’re trying to make sense of
what’s happening and draw conclusions from it.
Neeru:
Thank you for inviting me to Inference. I love talking to people about what
I care deeply about, because education is one of the most important things
we can give back to society. We can create all kinds of financial freedom,
but that can only happen if we truly help young students understand what
they need to know – and how to use that knowledge.
Education in the AI Era
Ksenia:
The last three years have been pretty disruptive for many industries. How
has that changed your perspective on education and on the CK-12
Foundation?
Neeru:
Let me go back a little.
When we started CK-12, we were trying to answer a simple question: how
might we make education available and meaningful for all children? At the
time, textbooks were very one-sided. You got what you got. But true learning
only happens when students can make their own connections to what they are
learning.
As technology began to evolve in the early 2000s, I knew it was going to go
far. I thought this would be one way to reach many more students and help
them. So from the beginning, we made CK-12 free.
Technology gave us capabilities that learning really needs – especially
multimodality. You cannot always learn effectively just by reading a
textbook or just by watching a video. A concept has to be presented in the
modality that works best for the learner.
Take physics, for example. If you are learning about electricity, reading
in a textbook about how electrons move doesn’t really make it come alive.
Now we have simulations. We have ways for students to actually see and
interact with what they’re learning.
That was powerful. But even then, we still didn’t really know what was
going on in the minds of students. We didn’t know whether they truly
understood what we were trying to teach.
It was only with the arrival of AI in the last three years that we realized
there was a real opportunity there. It wasn’t perfect – and no technology
ever arrives 100 percent ready. Technology matures through iteration, and
that requires all of us to participate.
When OpenAI suddenly reached enormous adoption in a very short time, it was
clear something major was happening. A lot of people were afraid: students
will cheat, machines will replace us, and so on. I was afraid as well. But I
also noticed something important: prompting itself is a learning tool.
Ksenia:
Absolutely. It’s the skill of asking questions.
Neeru:
Exactly. That’s why I kept telling people not to be afraid. If students can
prompt a machine in a way that gets them where they want to go, they are
thinking. They are thinking about concepts, about application, about whether
something sounds right or wrong, about whether they want to go deeper.
They may not describe it that way, but they do know when an answer doesn’t
sound right. Then they keep prompting. If we can teach children to question
– to keep asking why, the five whys – that itself is a huge learning
process.
So over the last three years, we built on top of everything we had already
done in learning science, concept maps, and knowledge connections. Two and a
half years ago, we introduced Flexi, our student tutor. Today we have over
50 million students using it.
Ksenia:
Wow. And how are the results?
Neeru:
We’ve had over 150 million questions asked.
From the beginning, I told the team that we had to categorize and tag the
questions students were asking. Many are procedural: help me solve this,
define this, help me understand this. Those are fine.
But the questions that really matter are the ones that reveal thinking. For
example: How does the sun burn when there’s no oxygen in space? That’s a
wonderful question from a young learner. You immediately see the
misconception: the child is assuming the sun “burns” through combustion,
when in fact it’s nuclear fusion.
Those are the moments where you can really understand what a student is
thinking and help them deeply.
That is what we built: a platform that connects concepts and content. Our
FlexBooks were always designed to be flexible and personalized – to each
learner’s level, language, standards, and classroom needs. But until AI, we
couldn’t really see inside the learning process at this level.
And that changes everything. Standardized testing only tells you whether an
answer was right or wrong. It doesn’t tell you why a learner got something
wrong. Now we can do deep knowledge tracing and understand where the
misunderstanding happened.
Do We Need to Rethink Education From the Ground Up?
Ksenia:
I have five children, and they’re still in public school. I can see how
early we still are with AI because public schools just can’t catch up that
fast. Do we need to rethink the whole education system from the ground
up?
Neeru:
When I started, I actually avoided trying to get adoption directly in
public schools. Partly because they didn’t want to adopt something free. We
are still free, almost 20 years later, and we intend to remain free.
What surprised me early on was that schools, districts, and states had
money – but they didn’t want to lose the systems around that money. That’s
the legacy system we were dealing with. So yes, politics is part of it, but
also incentives.
We took more of a Trojan horse approach. We built adaptive systems very
early on so we could tell where students were missing things and support
them in ways that were individualized.
But the reality is that schools still define success primarily through
standardized testing. That is deeply embedded in the thinking of teachers,
schools, districts, and systems.
So we started working not only with teachers but more directly with
students as well – because I felt that maybe we had to disrupt the system
from the learner side. But changing an entire system is hard. You have to
move carefully. You take one step, stabilize, then take the next.
What has changed in the last three years is that AI finally gives us tools
that make deeper change more possible. We now have a teacher assistant that
shows educators where each student is and how they are likely to progress
into the next concept. That kind of support can help create systemic
change.
Ksenia:
Do you follow what teachers are asking for? What they want from AI?
Neeru:
Yes, very much. We work with teachers all the time, and we get many
requests. But teachers are very different from one another. Some can imagine
what’s possible and are ready to move. Others are afraid, tired, or not
ready to take risks. So you have to work with many different profiles.
That’s one reason we’ve been around this long. Change in education takes a
long-term view.
If you ask me whether the whole system can change, I would say yes – but
not overnight. I don’t think it will take another 25 years. I think within
five years we’ll start to see deeper systemic change. But we have to change
the system.
Ksenia:
At the systemic level.
Neeru:
Yes. There is still a lot of fear. But if people can see that the change is
real and not scary, adoption can happen faster.
And of course there will always be bad actors. But that’s true of any
technology. When we created content, we had domain experts and human review.
We constantly checked quality – what the systems were saying, how students
were interacting with them. That quality control still matters. Now
automation can help, but responsibility still matters.
What Skills Matter Most Now?
Ksenia:
What skills do you think are essential in this AI world – for teachers and
for kids?
Neeru:
Teachers need open minds. They have to be willing to think about what’s
possible.
Every time a new tool appears, people panic. When calculators arrived,
people said students would never learn math. When the internet arrived,
people said students would just cheat. The same story continues.
Of course students still need to know how to think, compute, read, and
reason. But some tasks don’t need to be done by hand forever. That doesn’t
make the underlying understanding less important – it makes it more
important.
Teachers need to understand how these systems work. Right now, many of them
don’t. But they are smart. They will learn.
Students, meanwhile, still need literacy and numeracy. They need to write.
They need to understand language. They need math. What’s interesting now is
that language has become even more powerful. We once thought English majors
might not be especially practical. Now prompt quality and language fluency
are central to how people use AI.
We also need to help students connect their interests to deeper knowledge.
If a child says, “I want to be a stage designer, so I don’t need math or
science,” we can show them that they absolutely do – through lighting,
structure, area, form, efficiency. Creativity and technical understanding
are not opposites.
In the end, students need creativity, critical thinking, collaboration,
communication, and community.
What EdTech Often Gets Wrong
Ksenia:
What do you think companies offering AI in education misunderstand about
kids and teachers?
Neeru:
One big misconception is the belief that AI is enough by itself – that you
can just ask a question and get what you need.
What systems like large language models do is generate the most likely fit
probabilistically. But education has non-negotiables. Learning has
structure. Development matters. Misconceptions matter. Prior knowledge
matters. Current AI systems are not ready to handle all of that on their
own.
That’s why I think every vertical needs to be treated seriously in its own
terms. Education is not the same as medicine. These are different domains
with different responsibilities. You cannot simply take a general model and
assume that is enough.
Ksenia:
And when you say verticals, you mean domains like education and
medicine?
Neeru:
Exactly. Those are different verticals built on top of these foundational
models. And I don’t think we even fully know what AGI means yet, in
practical terms.
Kids, Curiosity, and Learning by Doing
Ksenia:
One thing I keep thinking is that AI is becoming as important as reading
and writing – a new literacy. And maybe we should also follow kids a little
more, because they approach technology with imagination and curiosity.
Neeru:
I saw that even when my own children were in middle school. Kids have
always had their own social graph – their own way of learning from each
other, teaching each other, figuring out who knows what.
I spent more than 15 years deeply involved in education. Originally I was a
molecular biologist doing research at Stanford on oncogenes. Then I became
pregnant with my first child and decided I couldn’t stay around
radioactivity. Later, after having four children, I started thinking
seriously about education.
I found what I thought was the best school for my children – a very
child-centered school. I got deeply involved. I spent about ten years in
classrooms, watching what teachers and students were doing.
Sometimes I would sit down next to a child who was off in a corner alone
and just ask, “What’s going on?” And often that child didn’t need someone to
do the work for them. They just needed someone to say: You’re doing fine.
Keep going. Let me help if you’re stuck.'
That, to me, was powerful. I thought: why can’t every child have
that?
That was really the genesis of CK-12.
Ksenia:
And what does CK-12 stand for?
Neeru:
K-12 is obvious. But the “C” stands for every child – and also for the core
C’s: creativity, critical thinking, collaboration, communication. Those are
non-negotiables for deep learning.
Ksenia:
That’s interesting, because those skills were always important – but now
they feel even more essential.
Neeru:
Exactly.
Why Free Is Hard in Education
Ksenia:
You said something interesting earlier – that because CK-12 was free,
schools had trouble adopting it. That’s such a paradox. Free is so
important, but it’s also hard to make work in education.
Neeru:
Yes. Most free products don’t last. We’ve lasted almost 20 years. But any
system – nonprofit or for-profit – needs sustainable funding.
That’s why my husband Vinod and I have stood behind this. We fund it
because we believe in funding every child.
Ksenia:
And how do children get access to it?
Neeru:
They can just join. It’s open and free. If they’re under 13, they need
teacher or parent permission. That’s one thing that breaks my heart a little
– because if you’re under 13, there are more barriers to independent
learning on platforms like this.
Ksenia:
That is a real barrier. There’s also a big difference between open-source
culture in software – where people help each other build things – and
education, where openness still feels unusual.
Neeru:
Yes. When we started, there was more conversation around OER – Open
Educational Resources. But not many survived.
Wikipedia was there, of course, but it wasn’t foundational for children.
Most things online were not at the right level for kids. They didn’t account
for prior knowledge, which is a major non-negotiable in learning. You have
to figure out what the child already knows. Otherwise, if something is too
hard or too easy, they lose interest.
That’s why cold start matters so much in learning systems.
Philanthropy, Access, and Human Potential
Ksenia:
If we go back to philanthropy, how do we make it more impactful in systems
that are so hard to penetrate?
Neeru:
Education is one of those things we simply cannot ignore. It is a human
rights issue. If the US – or any country – wants to remain strong, it has to
make sure the next generation is equipped.
And I think this can happen fast, because in countries like India and
China, children are hungry to learn. In many places, children understand
that education is their path forward. If you are born into hardship, your
family may not be able to help you study – but we can.
That is how you do it.
Ksenia:
My big hope is that AI can really accelerate that. Do you feel the same
way?
Neeru:
Absolutely. AI lets us deeply trace where a child misunderstood something
and help them recover faster. The current education system often expects a
child to make up years of missing knowledge in one year. That’s nearly
impossible without support.
That is why Flexi matters. It is there all the time.
Raising Grounded Children
Ksenia:
If I can ask something a little more personal – you really strike me as a
grounded and modest person. With all the resources you have, how do you
raise children to stay humble and grateful? What are your core values?
Neeru:
For me, the core values are about caring – for people, for animals, for the
world around you. My children have inherited that.
I also don’t think privilege should be something you flaunt. We always
encouraged our children not to chase the fanciest places or the most
prestigious labels, but to explore. We’d go to places like the Amazon or the
Galápagos – not for status, but for discovery.
When they were in middle school, we organized trips with other families and
a teacher to South America, where the children lived in villages and helped
with practical things – building toilets, helping where help was needed. We
wanted them to see how most people actually live.
Those are the values that matter: help where you can, whether through
money, mentorship, or simply showing up.
And I often think about how many educated women in the world have skills
and talent that go underused. What if more of them helped mentor children
around them? What if they became available to teach, guide, and support?
That could go a very long way.
Ksenia:
I see some of that in my community too, but we live in a small town. It
feels harder in big cities.
Neeru:
Maybe. But schools are still there. Parents can volunteer. In my children’s
school, many parents brought their expertise into the classroom and helped
teachers. You can do that. Show up.
Ksenia:
So it’s more about showing than telling.
Neeru:
Yes. Show up. All of us have to show up.
Intention, Not Just Attention
Neeru:
One more thing. In machine learning, people say attention is all you need.
That’s what taught the machines. But for humans – for education, for society
– attention is not enough.
We need intention. We need judgment.
Why am I learning this? Why does it matter? It cannot just be let AI do it.
That’s what I would say.
Hope and Concern in the AI Age
Ksenia:
What is most exciting for you in this AI world right now?
Neeru:
Two things.
First, I’m going to become a grandmother for the first time.
Ksenia:
Congratulations!
Neeru:
Thank you. But I mean something larger too: humanity continues. Even though
our time is limited, human beings continue. That matters.
Second, I really believe that if we use AI as augmented intelligence –
something that helps us – we can do wonders. Don’t be afraid of it.
That excites me.
Ksenia:
And what are your concerns?
Neeru:
Fear is a real concern. And sometimes fear is grounded in reality. Human
beings fight for dominance, for advantage, for shortcuts. There will always
be people who try to game the system. We’ve seen that in every technological
wave – from crypto scams to identity theft.
Those are real problems. But again, no technology arrives fully ready. Not
even a baby comes ready-made. We have to stay involved and keep making
systems better.
My concern is when a small number of people capture all the benefits and
hoard them. That worries me.
Books That Shaped Neeru
Ksenia:
I always end with a question about books. What’s a book that significantly
influenced you – either recently or from childhood?
Neeru:
There are several.
I learned to read English through Dr. Seuss and Archie comics. Later, The
Hobbit influenced me a lot. And then Man’s Search for Meaning by Viktor
Frankl had a very deep impact on me.
That book, with its reflections on concentration camps and how people kept
their sanity in terrible circumstances, really stayed with me. It made me
think about how we help children understand that life can be hard – but that
people are also deeply adaptable and resilient.
Ksenia:
Yes. People are very adaptable, and we want them to adapt toward something
better.
Neeru:
Exactly.
And I also love music. I love Hamilton. That line – I’m not throwing away
my shot – really resonates with me. I’m still not giving away my shot. I’m
going to keep taking it.
People say learning is lifelong, and I really believe that. I was around 50
when I went back to college for another degree. I was 52 when I started
working on CK-12.
Ksenia:
What’s next for you to learn?
Neeru:
So much. One area I keep thinking about is economics – especially the
economics of AI.
I’m not worried that AI will simply eliminate all work. Every major
technological shift has opened new kinds of work while removing some forms
of labor people no longer need to suffer through. AI will do some of that
too. But people will have to reskill.
That’s exactly what we want our children to learn: learn broadly, learn
quickly, keep adapting – but truly learn, and apply what you know.
This interview has been edited and condensed for clarity.
I support the concerns expressed in this open letter to the NZ Listener.
"On July 24, 2021, in the context of a review of the secondary school curriculum National Certificate of Educational Achievement (NCEA), seven University of Auckland professors and emeriti professors (known informally as the Listener Seven) published a letter titled "In Defence of Science" in the current affairs magazine New Zealand Listener, which generated considerable controversy for claiming indigenous knowledge (or mātauranga Māori) "falls far short of what can be defined as science itself." " - Wikipedia
A recent report from a Government NCEA working group on proposed changes
to the Māori school curriculum aims “to ensure parity for mātauranga Māori
with the other bodies of knowledge credentialed by NCEA (particularly
Western/Pakeha epistemologies)”. It includes the following description as
part of a new course: “It promotes discussion and analysis of the ways in
which science has been used to support the dominance of Eurocentric views
(among which, its use as a rationale for colonisation of Māori and the
suppression of Māori knowledge); and the notion that science is a Western
European invention and itself evidence of European dominance over Māori
and other indigenous peoples.”
This perpetuates disturbing misunderstandings of science emerging at all
levels of education and in science funding. These encourage mistrust of
science. Science is universal, not especially Western European. It has
origins in ancient Egypt, Mesopotamia, ancient Greece and later India,
with significant contributions in mathematics, astronomy and physics from
mediaeval Islam, before developing in Europe and later the US, with a
strong presence acoss Asia.
Science itself does not colonise. It has been used to aid colonisation,
as have literature and art. However, science also provides immense good,
as well as greatly enhanced understanding of the world. Science is helping
us battle worldwide crises such as Covid, global warming, carbon
pollution, biodiversity loss and environmental degradation. Such science
is informed by the united efforts of many nations and cultures. We
increasingly depend on science, perhaps for our very survival. The future
of our world, and our species, cannot afford mistrust in science.
Indigenous knowledge is critical for the preservation and perpetuation of
culture and local practices, and plays key roles in management and policy.
However, in the discovery of empirical, universal truths, it falls far
short of what we can define as science itself.
To accept it as the equivalent of science is to patronise and fail
indigenous populations; better to ensure that everyone participates in the
world’s scientific enterprises. Indigenous knowledge may indeed help
advance scientific knowledge in some ways, but it is not science.
Kendall Clements Professor, School of Biological Sciences, University of Auckland
Garth Cooper, FRSNZ Professor, School of Biological Sciences, University of Auckland
Michael Corabllis, FRSNZ Emeritus Professor, School of Psychology, University of Auckland
Douglas Elliffe Professor, School of Psychology, University of Auckland
Robert Nola, FRSNZ Emeritus Professor, School of Philosophy, University of Auckland
Elizabeth Rata Professor, Critical Studies in Education, University of Auckland
John Werry Emeritus Professor, Department of Psychological Medicine, University of
Auckland
