How AI Can Transform Education - But Who's Getting Left Behind? | Coffee with Chandru Ep 4
AI is already changing classrooms, but will it uplift everyone or widen the gap? Chandra Kumar explores AI's real impact on education.
About This Episode
AI is already changing classrooms, but will it uplift everyone or widen the gap?
In this episode, Chandra Kumar cuts through the noise to explore AI's real impact on education. He shares hard-won insights on how AI can personalize learning, reduce burnout for teachers, and help underprivileged students gain access. He also addresses academic misuse, resistance from educators, and the societal fear of job loss.
Coffee with Chandru is for busy professionals, SME owners, founders, and anyone curious about what it really takes to build, lead, and grow in a world shaped by AI.
Key Takeaways
- AI can personalize learning experiences, but inclusive implementation matters.
- Teacher burnout can be reduced through AI assistance when educators get proper training.
- Underprivileged students can benefit from AI accessibility tools if the digital divide is addressed.
- Academic misuse requires balanced policies and AI literacy.
- Resistance often stems from job security fears that need practical reskilling answers.
Episode Transcript
Timestamped segments
Morning Toshar. So yeah great to again uh catch
Toshar. So yeah great to again uh catch up right and uh welcome to my podcast.
up right and uh welcome to my podcast. So essential idea was when you reached
So essential idea was when you reached out I knew this is an important topic of
out I knew this is an important topic of AI and education especially for the
AI and education especially for the underprivileged uh kids students.
underprivileged uh kids students. Um yes we have been doing quite a bit of
Um yes we have been doing quite a bit of work in the past eight years much before
work in the past eight years much before even Chad GPT got launched.
even Chad GPT got launched. Yes. And uh uh I know we spoke uh
Yes. And uh uh I know we spoke uh probably some of it during our meet up
probably some of it during our meet up for the startup evaluation uh sessions,
for the startup evaluation uh sessions, right? Um so uh you you mentioned of
right? Um so uh you you mentioned of course you are going to be delivering a
course you are going to be delivering a talk as well as uh uh probably a write
talk as well as uh uh probably a write up in terms of the same uh
up in terms of the same uh intent on AI and education for
intent on AI and education for underprivileged right?
underprivileged right? Yes. So um broadly I I will just give a
Yes. So um broadly I I will just give a broad sort of introduction then you ask
broad sort of introduction then you ask me questions so it's easy for me to sure
me questions so it's easy for me to sure you don't want to monologue.
you don't want to monologue. Yeah yeah totally agree with you.
Yeah yeah totally agree with you. Yeah. So um of all the um I would call
Yeah. So um of all the um I would call as the domains that artificial
as the domains that artificial intelligence as a technology
intelligence as a technology has uh immediately impacted the first
has uh immediately impacted the first one has been education.
one has been education. Mhm. Um, of course, when you look at uh
Mhm. Um, of course, when you look at uh the broad hype about uh uh products like
the broad hype about uh uh products like Chad GPT or Anthropic or you you name
Chad GPT or Anthropic or you you name it, right? I mean, I'm sure there are
it, right? I mean, I'm sure there are some 200 different products which are
some 200 different products which are now quite popular
now quite popular and we are hearing about unheard sums of
and we are hearing about unheard sums of money and investment pouring into all
money and investment pouring into all this sector.
this sector. But the constant sort of gripe among
But the constant sort of gripe among people is there is no viable business
people is there is no viable business use case
use case and it's like uh it's all hype and there
and it's like uh it's all hype and there actually not leading to anything. uh one
actually not leading to anything. uh one side we have CEOs who are saying it's
side we have CEOs who are saying it's leading to job losses they are replacing
leading to job losses they are replacing 30% of the workforce but on the other
30% of the workforce but on the other hand if you look at it people are still
hand if you look at it people are still hiring people I don't at least I've not
hiring people I don't at least I've not seen any magical AI agent replacing
seen any magical AI agent replacing people end to end sort of stuff
people end to end sort of stuff at best we may have heard about some
at best we may have heard about some people doing some uh content getting uh
people doing some uh content getting uh created or probably about code being
created or probably about code being generated and things like that
generated and things like that yep
yep um however when we look at the education
um however when we look at the education space and this is something we did
space and this is something we did notice even as I said about 8 years back
notice even as I said about 8 years back when I started off wisely wise and now
when I started off wisely wise and now we have the product on smart me uh we
we have the product on smart me uh we did notice that AI has the capability of
did notice that AI has the capability of uh rapidly disrupting every facet of
uh rapidly disrupting every facet of education
education and uh if you look at uh usually the top
and uh if you look at uh usually the top three sort of complaints about the
three sort of complaints about the education industry per se is one it has
education industry per se is one it has become very industrialized which means
become very industrialized which means there's no sort of personalized
there's no sort of personalized attention given to students defeating
attention given to students defeating the very purpose of going to school.
the very purpose of going to school. Yeah.
Yeah. Second that uh sort of I would say uh
Second that uh sort of I would say uh social initiative of education has come
social initiative of education has come uh become very commercialized. Uh it's a
uh become very commercialized. Uh it's a business right today we call it as an
business right today we call it as an industry.
industry. Yes.
Yes. While that's a disconnect. So if I say
While that's a disconnect. So if I say for example I'm launching an e-commerce
for example I'm launching an e-commerce business people are happy about it. But
business people are happy about it. But uh the same thing if you try to do
uh the same thing if you try to do something in education people are more
something in education people are more suspicious and you don't really want to
suspicious and you don't really want to associate profit making with education
associate profit making with education sector
sector so overtly profit centered you don't
so overtly profit centered you don't want it to be
want it to be that's a I would just say societal
that's a I would just say societal perception right in terms of how
perception right in terms of how education as a sector I mean education
education as a sector I mean education healthcare are two sectors which come to
healthcare are two sectors which come to my mind where people um don't want to be
my mind where people um don't want to be like be seen as profit taking
like be seen as profit taking uh reality might be different but that's
uh reality might be different but that's a story for another podcast
a story for another podcast but
but this is the second gripe against this
this is the second gripe against this particular area domain vertical whatever
particular area domain vertical whatever you call it right
you call it right third is of course uh the cost of
third is of course uh the cost of education has gone up tremendously high
education has gone up tremendously high whether it's tuition fees it is the cost
whether it's tuition fees it is the cost of other allied stuff and uh people
of other allied stuff and uh people nowadays call it as a supply chain so
nowadays call it as a supply chain so you start from somewhere in your uh
you start from somewhere in your uh kindergarten years then go on to
kindergarten years then go on to schooling for 12 years and then college
schooling for 12 years and then college is probably another four years and uh
is probably another four years and uh there is no way that anybody can escape
there is no way that anybody can escape this. Finally land up in the rat race in
this. Finally land up in the rat race in the corporate world and uh the cost of
the corporate world and uh the cost of doing this and going into very specific
doing this and going into very specific brands has skyrocketed in the past few
brands has skyrocketed in the past few years.
years. True. Um while on one hand you do see
True. Um while on one hand you do see many colleges and universities opening
many colleges and universities opening up, people can travel freely but still
up, people can travel freely but still it is a big chunk of anybody's salary.
it is a big chunk of anybody's salary. Yeah, absolutely.
Yeah, absolutely. So these are the top three if you ask me
So these are the top three if you ask me are the gripe against industry and AI is
are the gripe against industry and AI is seen as a savior here. Why one you could
seen as a savior here. Why one you could do personalized one is to one education
do personalized one is to one education through chat bots and you know uh other
through chat bots and you know uh other forms like you have of course like your
forms like you have of course like your um products like Chad GBT which you can
um products like Chad GBT which you can build other products and things like
build other products and things like that
that second is uh uh of course it cannot be
second is uh uh of course it cannot be too costly right because it's the same
too costly right because it's the same AI many people can share the same chat
AI many people can share the same chat bot so costs probably are going to you
bot so costs probably are going to you know really come down and u obviously
know really come down and u obviously because the costs are coming down it's
because the costs are coming down it's not going to be seen being profit
not going to be seen being profit making. I mean how much can you earn
making. I mean how much can you earn from a chatbot? Um so uh because you're
from a chatbot? Um so uh because you're not like for example going to have uh
not like for example going to have uh lot of people, teachers, human
lot of people, teachers, human employees. So the costs are going up. if
employees. So the costs are going up. if I need to have a building, you know, all
I need to have a building, you know, all of those cost are
of those cost are so AI is seen as a savior and that's why
so AI is seen as a savior and that's why it is um coming up with a very rapid
it is um coming up with a very rapid adoption in this particular um segment.
adoption in this particular um segment. And uh I see my personal experiences
And uh I see my personal experiences teachers, professors gain a lot by
teachers, professors gain a lot by adopting AI.
adopting AI. It brings down their levels of u um
It brings down their levels of u um work. The administrative work alone is
work. The administrative work alone is uh probably 40 to 60% depending upon the
uh probably 40 to 60% depending upon the level of teacher.
level of teacher. Correct. And uh in the US the number one
Correct. And uh in the US the number one cause of turnover of teachers is uh
cause of turnover of teachers is uh stress felt by the teachers which I'm
stress felt by the teachers which I'm sure is true in other countries as
sure is true in other countries as almost everywhere. Yeah.
almost everywhere. Yeah. Yeah. And my my mom herself used to be a
Yeah. And my my mom herself used to be a teacher and I firsthand seen that even
teacher and I firsthand seen that even like 30 years back uh the amount of
like 30 years back uh the amount of administrative work a teacher has to do.
administrative work a teacher has to do. Uh everything from creating lesson plans
Uh everything from creating lesson plans to creating uh what we call as notes of
to creating uh what we call as notes of lessons and then submitting to
lessons and then submitting to authorities. I I could go on and on and
authorities. I I could go on and on and on.
on. Yeah. Yeah.
Yeah. Yeah. And whenever the government launches a
And whenever the government launches a new scheme in many countries, they
new scheme in many countries, they actually use the teachers as the civil
actually use the teachers as the civil servants to go out and implement those
servants to go out and implement those schemes.
schemes. So you would see that AI is being used
So you would see that AI is being used now by teachers to bring down that
now by teachers to bring down that administrative work.
administrative work. Right? Slowly it has also gone to the
Right? Slowly it has also gone to the level where uh teachers are using it to
level where uh teachers are using it to let's say correct
let's say correct exam papers, set new exam papers,
exam papers, set new exam papers, set papers. Yeah,
set papers. Yeah, it it could now suddenly you know it's
it it could now suddenly you know it's all about content creation and uh the
all about content creation and uh the teachers find that instead of me
teachers find that instead of me spending like uh two weeks 3 weeks I can
spending like uh two weeks 3 weeks I can do it in probably 3 hours or four hours.
do it in probably 3 hours or four hours. Mhm. Mhm.
Mhm. Mhm. Right. And many of them are doing many
Right. And many of them are doing many creative
creative uh things with that. uh it could extend
uh things with that. uh it could extend not just in terms of uh lesson plans but
not just in terms of uh lesson plans but it could be in terms of creating images
it could be in terms of creating images um it could be in terms of even videos
um it could be in terms of even videos nowadays voice based things so suddenly
nowadays voice based things so suddenly teachers are also seeing theirh teaching
teachers are also seeing theirh teaching techniques are becoming more effective
techniques are becoming more effective why because it's no more the written
why because it's no more the written word
word I can use so many forms of communication
I can use so many forms of communication multimodal kind of a
multimodal kind of a correct
correct concept as well
concept as well correct now the same thing if uh people
correct now the same thing if uh people argue that we always had CBDs right
argue that we always had CBDs right computer based tutorials we had YouTube
computer based tutorials we had YouTube and all of that.
and all of that. Yeah.
Yeah. But the two challenges with those sort
But the two challenges with those sort of forms of uh technology is one is it
of forms of uh technology is one is it is not uh interactive.
is not uh interactive. I mean what can you do with a YouTube
I mean what can you do with a YouTube video? You can only see that.
video? You can only see that. Yeah. You can just watch it. Yeah.
Yeah. You can just watch it. Yeah. Yeah. And second it's not customized. So
Yeah. And second it's not customized. So I may be a teacher. I have a certain
I may be a teacher. I have a certain style of doing stuff and I want it to be
style of doing stuff and I want it to be uh maybe I want to just build a quick
uh maybe I want to just build a quick video game explaining the uh let's say
video game explaining the uh let's say the uh atom and the molecule and I don't
the uh atom and the molecule and I don't want to go for some general video
want to go for some general video somebody probably has done in the UK or
somebody probably has done in the UK or the US.
the US. Yeah.
Yeah. So that's another aspect why AI is being
So that's another aspect why AI is being rapidly being adopted. So that's a whole
rapidly being adopted. So that's a whole gamut of adoption happening. So if you
gamut of adoption happening. So if you look at uh companies like Google or open
look at uh companies like Google or open AI
AI that's why the very very first
that's why the very very first initiatives they have launched for the
initiatives they have launched for the education domain
education domain and the very first of people
and the very first of people who have been beta testing the products
who have been beta testing the products or adopting the products you would see
or adopting the products you would see are typically professors
are typically professors correct correct very true
correct correct very true so that's a model I'm sure you would
so that's a model I'm sure you would recall has been successfully done by
recall has been successfully done by companies like uh Microsoft starting in
companies like uh Microsoft starting in the '90s
the '90s go behind there because that's that's
go behind there because that's that's where your workforce is originating
where your workforce is originating from.
from. So you capture their mind share at that
So you capture their mind share at that point of time and then later on they
point of time and then later on they come in and adopt your technologies.
come in and adopt your technologies. Yeah.
Yeah. So these guys are all following the same
So these guys are all following the same playbook.
playbook. So they're using the old classic
So they're using the old classic principles but adopting it to the
principles but adopting it to the technologies they bring to the table.
technologies they bring to the table. Correct. So
Correct. So an interesting perspective actually.
an interesting perspective actually. It's a very valid one.
It's a very valid one. Yes. So when we go again we have been
Yes. So when we go again we have been taking a stance that you know great AI
taking a stance that you know great AI is great and all of that stuff is great
is great and all of that stuff is great lot of infrastructure we are enjoying
lot of infrastructure we are enjoying all of the technology but what about the
all of the technology but what about the underprivileged
underprivileged students
students now when we talk about underprivileged
now when we talk about underprivileged it's both financially
it's both financially uh physically underprivileged and
uh physically underprivileged and probably don't even have access and
probably don't even have access and which I've seen with my own eyes in many
which I've seen with my own eyes in many parts of the world because I myself I'm
parts of the world because I myself I'm a master teacher I go and take classes
a master teacher I go and take classes in these schools right from some of the
in these schools right from some of the most prominent international ones in
most prominent international ones in Singapore to some of them which are
Singapore to some of them which are quite remote in Indonesia and India.
quite remote in Indonesia and India. We also do with schools surprisingly
We also do with schools surprisingly even in the US with not lot of access.
even in the US with not lot of access. Yeah. Oh okay.
Yeah. Oh okay. So you'd be very surprised that access
So you'd be very surprised that access is very unequal worldwide not
is very unequal worldwide not necessarily only in um I would say
necessarily only in um I would say developing countries if I can use the
developing countries if I can use the term anymore.
term anymore. Yeah. uh and it's a uh what you could
Yeah. uh and it's a uh what you could call that um many people are simply not
call that um many people are simply not even aware that something like is coming
even aware that something like is coming up.
up. Correct.
Correct. Um in my various travels I've done to
Um in my various travels I've done to many colleges and all of them the there
many colleges and all of them the there is strong resistance by the computer
is strong resistance by the computer science departments to adopt AI because
science departments to adopt AI because they they view it as a existential
they they view it as a existential threat.
threat. They think they know AI which is not the
They think they know AI which is not the case.
case. Yeah. um the other departments like
Yeah. um the other departments like chemistry or language are very keen to
chemistry or language are very keen to adopt it. So look at it very recently in
adopt it. So look at it very recently in the Singapore ministry had uh the tech
the Singapore ministry had uh the tech excel fest where I actually took a
excel fest where I actually took a workshop for about 120 teachers for
workshop for about 120 teachers for especially for language teaching using
especially for language teaching using artificial intelligence.
artificial intelligence. Okay. Uh that was the piece that you
Okay. Uh that was the piece that you published on LinkedIn.
published on LinkedIn. Yeah. Correct.
Yeah. Correct. Yeah. Yeah. So they are very hungry to
Yeah. Yeah. So they are very hungry to adopt this
adopt this but you won't see that equally done
but you won't see that equally done maybe even within the same school or
maybe even within the same school or even within the same uh college or
even within the same uh college or university.
university. So we have been trying to break this
So we have been trying to break this mold also by partnering with many
mold also by partnering with many foundations, many uh CSRs that corporate
foundations, many uh CSRs that corporate social responsible uh organizations
social responsible uh organizations um I mean nonprofits in the broad sense
um I mean nonprofits in the broad sense of the term which probably also includes
of the term which probably also includes governments.
governments. Yeah. And um we have uh done this again
Yeah. And um we have uh done this again in quite some remote parts of the world
in quite some remote parts of the world and uh they have been sponsoring lot of
and uh they have been sponsoring lot of these and we have been giving it at
these and we have been giving it at quite uh I would say dirt cheap rates
quite uh I would say dirt cheap rates because we want the volumes to be there
because we want the volumes to be there um otherwise it just turns into another
um otherwise it just turns into another profitm initiative.
profitm initiative. Correct. Correct.
Correct. Correct. Um and we had to design a curriculum. We
Um and we had to design a curriculum. We had to design u what we can call the
had to design u what we can call the teacher training material. We had to
teacher training material. We had to design an online course and uh slowly
design an online course and uh slowly over that particular um sort of
over that particular um sort of initiative we also figured out that we
initiative we also figured out that we have to create age appropriate
have to create age appropriate curricular content.
curricular content. It has to be in line with international
It has to be in line with international standards.
standards. Okay.
Okay. A doesn't have one common international
A doesn't have one common international standard. I doubt if there are any
standard. I doubt if there are any standards probably worldwide. There are
standards probably worldwide. There are a lot of I would say policies and
a lot of I would say policies and guidelines given by
guidelines given by Yeah. Yeah.
Yeah. Yeah. We have to do everything from scratch.
We have to do everything from scratch. Yeah.
Yeah. And uh then comes the challenge of
And uh then comes the challenge of language.
language. You typically do it in English but
You typically do it in English but not everybody speaks English or things
not everybody speaks English or things in English.
in English. Correct.
Correct. We had to do it in other languages which
We had to do it in other languages which means we had to bring in uh people who
means we had to bring in uh people who are like bilingual or triilingual uh
are like bilingual or triilingual uh English plus another language. Then
English plus another language. Then again we had to shoot all the videos. Um
again we had to shoot all the videos. Um and then we started encountering more
and then we started encountering more specific problems because people have uh
specific problems because people have uh issues on buying data plans. It's not
issues on buying data plans. It's not easy to run an online
easy to run an online so you need sponsors for all of that.
so you need sponsors for all of that. So we had to work with these uh
So we had to work with these uh nonprofits and uh then the nonprofits
nonprofits and uh then the nonprofits figured out a lot of issues. Then they
figured out a lot of issues. Then they actually bought mobiles, tablets,
actually bought mobiles, tablets, distributed it to schools. Um and it's
distributed it to schools. Um and it's not so easy to do under government uh
not so easy to do under government uh policy.
policy. Oh yeah, absolutely.
Oh yeah, absolutely. So they had to put lot of effort to get
So they had to put lot of effort to get all the permissions locally. I can't
all the permissions locally. I can't just for example walk into a government
just for example walk into a government school.
school. No, no, no chance.
No, no, no chance. It's no chance. Yeah. I've dealt a
It's no chance. Yeah. I've dealt a little bit with even poly techchnics and
little bit with even poly techchnics and it and I know what you mean.
it and I know what you mean. Yeah.
Yeah. So, completely understand.
So, completely understand. Right. So that is how we've been doing
Right. So that is how we've been doing for the past 8 years because our
for the past 8 years because our intention is that first let us reduce
intention is that first let us reduce the access inequality
the access inequality and uh once you are able to get it
and uh once you are able to get it through to those who really can adopt it
through to those who really can adopt it and require it and uh then we slowly
and require it and uh then we slowly start solving one after the other
start solving one after the other challenges right I can't do everything
challenges right I can't do everything on day one
on day one yeah yeah
yeah yeah uh then we slowly also worked with the
uh then we slowly also worked with the government so for example we do did it
government so for example we do did it with some of the state governments in
with some of the state governments in India. We connected our portal to their
India. We connected our portal to their portal for the online courses. Uh in
portal for the online courses. Uh in fact, we also did it with NSDC, the
fact, we also did it with NSDC, the National Skill Development Corporation
National Skill Development Corporation in India.
in India. Yeah.
Yeah. And any anybody who's a citizen can just
And any anybody who's a citizen can just log in and access our courses free of
log in and access our courses free of cost.
Oh. And then u people wanted us to do
And then u people wanted us to do physical courses in which means you have
physical courses in which means you have to go to the schools and colleges to do
to go to the schools and colleges to do which we started recruiting people
which we started recruiting people training them giving them meaningful
training them giving them meaningful employment and sending them out to these
employment and sending them out to these various schools and colleges in a
various schools and colleges in a physical mode also.
physical mode also. Okay. So now if you look at it education
Okay. So now if you look at it education has become even more challenging because
has become even more challenging because postcoid people want uh depending on
postcoid people want uh depending on their uh what you can call criteria they
their uh what you can call criteria they either want fully online
either want fully online or they want fully physical or they want
or they want fully physical or they want a hybrid.
a hybrid. So becomes very challenging as an
So becomes very challenging as an operating model
operating model because uh you simply cannot just uh
because uh you simply cannot just uh have resources to cater to all types of
have resources to cater to all types of operating models at the same time.
operating models at the same time. Correct. Correct. Yeah. So um and at at
Correct. Correct. Yeah. So um and at at the same time I noticed a pattern in the
the same time I noticed a pattern in the past two years that these AI and AI
past two years that these AI and AI agents which we prominently call in 2025
agents which we prominently call in 2025 are going to rapidly become the norm as
are going to rapidly become the norm as we go forward.
we go forward. It may not be in a good shape at this
It may not be in a good shape at this point of time
point of time but I'm pretty sure that before end of
but I'm pretty sure that before end of this year the things will change
this year the things will change dramatically.
dramatically. Yeah. In fact, yesterday I think OpenAI
Yeah. In fact, yesterday I think OpenAI new model launched and I believe it it
new model launched and I believe it it won the gold medal in the international
won the gold medal in the international max Olympia which is never done by any
max Olympia which is never done by any AI model.
AI model. Wow.
Wow. So okay
So okay the benchmarks are being broken on on a
the benchmarks are being broken on on a literally weekly basis.
literally weekly basis. Right.
Right. So we said u look the future is not
So we said u look the future is not probably going to be education is not
probably going to be education is not going to be in the same model as we have
going to be in the same model as we have done till now. probably it is going to
done till now. probably it is going to be that you are going to be like how we
be that you are going to be like how we are working with a computer now or a
are working with a computer now or a mobile it's going to be with an AI agent
mobile it's going to be with an AI agent it's not going to be probably over the
it's not going to be probably over the next few years that I have to really go
next few years that I have to really go to a training center I need a teacher I
to a training center I need a teacher I need to do uh you know sort of resources
need to do uh you know sort of resources and stuff like that
and stuff like that I will learn more by doing then first
I will learn more by doing then first learning and then doing
learning and then doing and uh
and uh okay
okay we then slowly We figured out that uh we
we then slowly We figured out that uh we need to have AI agents which we build
need to have AI agents which we build and give it to both teachers and
and give it to both teachers and students and give them the full power of
students and give them the full power of how to use AI which means everything
how to use AI which means everything from they can create their own agents. A
from they can create their own agents. A student for example can take the lesson
student for example can take the lesson plan from their teachers and then they
plan from their teachers and then they can create their own study plan and the
can create their own study plan and the study plan is customized to what the
study plan is customized to what the teacher has given to them as a lesson
teacher has given to them as a lesson plan and there is complete sync in what
plan and there is complete sync in what both of them are doing and they only
both of them are doing and they only contact the teacher or the teacher
contact the teacher or the teacher contacts the student when they want a
contacts the student when they want a one is to one personalized sort of doubt
one is to one personalized sort of doubt clearing sessions or the teacher wants
clearing sessions or the teacher wants to conduct a assessment or the
to conduct a assessment or the governmentmandated exams. So it's
governmentmandated exams. So it's rapidly going towards that space.
rapidly going towards that space. So that means that do you think that
So that means that do you think that means that there is going to be less and
means that there is going to be less and less social interaction between student
less social interaction between student and teacher as in physical?
and teacher as in physical? I think that's what is going to be the
I think that's what is going to be the uh prominent model and that is what I
uh prominent model and that is what I would say the next generations are
would say the next generations are wanting also.
wanting also. So in a very I would say uh it's fast
So in a very I would say uh it's fast moving towards a sweet spot where all of
moving towards a sweet spot where all of these factors are coming together.
these factors are coming together. So
So interesting.
interesting. I mean people may argue it is 5 years
I mean people may argue it is 5 years down the line, 50 years down the line
down the line, 50 years down the line but I can see it happening already. Uh
but I can see it happening already. Uh you already are seeing people only going
you already are seeing people only going for online courses. Online degrees are
for online courses. Online degrees are now daen about 3 years back I never
now daen about 3 years back I never heard about online degrees.
heard about online degrees. Yeah.
Yeah. Uh but now I'm talking about proper uh I
Uh but now I'm talking about proper uh I would say registered and you know
would say registered and you know accredited university giving online
accredited university giving online degrees.
degrees. Yes. Online degrees. You see even the IT
Yes. Online degrees. You see even the IT are now giving their bachelors online.
are now giving their bachelors online. Oh is it?
Oh is it? Yeah I see many of them uh I've met many
Yeah I see many of them uh I've met many folks who are doing this sitting in
folks who are doing this sitting in Delhi and then taking a course with
Delhi and then taking a course with let's say I met Madras.
let's say I met Madras. So you simply cannot escape the tsunami
So you simply cannot escape the tsunami of change which is happening in this
of change which is happening in this space. Earlier we used to have remember
space. Earlier we used to have remember uh OG what is it open un open OGU or
uh OG what is it open un open OGU or what is it in India open university
what is it in India open university there something igno
there something igno ignoign
ignoign igno right
igno right that we used to get I think by postal
that we used to get I think by postal the document
the document correct
correct people used to take it
people used to take it so that is now you're saying that model
so that is now you're saying that model is now moving on to the online space
is now moving on to the online space pretty much
pretty much yes
yes okay interesting
very very interesting Okay. Okay. So in in that given all of this
Okay. So in in that given all of this context
context which aspect do you think
would keep schools or administrators up at night? One if you had to just start
at night? One if you had to just start with one two three I mean I can't say
with one two three I mean I can't say just one because there's no one. And
just one because there's no one. And then secondly, therefore, which aspects
then secondly, therefore, which aspects would also the audience or the students
would also the audience or the students really want to see the fastest shift in?
really want to see the fastest shift in? See, right now I think the
See, right now I think the administrators and the professors or
administrators and the professors or teachers are really having sleepless
teachers are really having sleepless nights with u the content creation and
nights with u the content creation and assessments by students. It is being
assessments by students. It is being completely done by CHBT as we speak.
completely done by CHBT as we speak. You take a school student or you take a
You take a school student or you take a college student, even a PhD level
college student, even a PhD level student, right? I'm sure you are aware
student, right? I'm sure you are aware of the controversies in N US uh
of the controversies in N US uh because somebody submitted even some
because somebody submitted even some thesis papers using chatb some stuff
thesis papers using chatb some stuff like that right
like that right now what happens if even at PhD level
now what happens if even at PhD level people are sort of refusing to do it the
people are sort of refusing to do it the old manual way uh and trying to do it
old manual way uh and trying to do it within a few minutes of using chat GBD.
within a few minutes of using chat GBD. Now that is uh really becoming a big
Now that is uh really becoming a big friction point between the I would call
friction point between the I would call the uh system on one side and the
the uh system on one side and the students on the other side.
students on the other side. Yeah.
Yeah. Uh I don't see any easy way out. I'm
Uh I don't see any easy way out. I'm sure some of them are experimenting with
sure some of them are experimenting with pen and paper.
pen and paper. Mhm.
Mhm. But the
But the student side of story is that uh if the
student side of story is that uh if the professors are using chipd why can't we
professors are using chipd why can't we which is a fair question to ask right
which is a fair question to ask right fair question
fair question if you're using AI why should I be
if you're using AI why should I be denied that uh whole technology being
denied that uh whole technology being used um I mean we can always debate
used um I mean we can always debate whether it's ethically wrong people are
whether it's ethically wrong people are comparing it to having used calculators
comparing it to having used calculators I still remember for the entrance exams
I still remember for the entrance exams we used to memorize the lock tables the
we used to memorize the lock tables the pi tables Absolutely
pi tables Absolutely right. Multiplication tables you
right. Multiplication tables you probably go up to 30 40 or so
probably go up to 30 40 or so easy. Yeah. Yeah.
easy. Yeah. Yeah. And uh we used to buy those small books
And uh we used to buy those small books from the secondhand bookshops and you
from the secondhand bookshops and you know that used to be a different thing
know that used to be a different thing right today I can't expect any of them
right today I can't expect any of them to literally memorize or do the stuff
to literally memorize or do the stuff that we used to do.
that we used to do. I mean they can't even memorize a single
I mean they can't even memorize a single phone number probably.
phone number probably. Correct. So
Correct. So this is the challenge in front of the
this is the challenge in front of the administrators and u the adoption rate
administrators and u the adoption rate is if you ask me at least the quite the
is if you ask me at least the quite the creamy layers of society worldwide is
creamy layers of society worldwide is 100%.
100%. Which again comes back to the same
Which again comes back to the same access problem.
access problem. It's an access the equity equitable
It's an access the equity equitable access for all.
access for all. Yeah. If I can write a better essay and
Yeah. If I can write a better essay and I can get admission to university and
I can get admission to university and another student who's probably more
another student who's probably more gifted and brilliant but they do not
gifted and brilliant but they do not have access they will be denied a seat.
have access they will be denied a seat. Uh maybe I will learn better with this
Uh maybe I will learn better with this model. The other person still has to go
model. The other person still has to go with older teacher and and I have seen
with older teacher and and I have seen people arguing that you know you cannot
people arguing that you know you cannot like replace teachers or whatever. I'm
like replace teachers or whatever. I'm telling them do you know 95% of them
telling them do you know 95% of them don't even have teachers. Forget whether
don't even have teachers. Forget whether they have good teachers or bad teachers.
they have good teachers or bad teachers. I know schools where the government has
I know schools where the government has decided to close down the schools
decided to close down the schools because there are not enough teachers.
because there are not enough teachers. I've heard this as well.
I've heard this as well. And you have teachers who are going
And you have teachers who are going through a lot of physical hardship
through a lot of physical hardship crossing mountains and rivers to go and
crossing mountains and rivers to go and probably teach a class of 10 people or
probably teach a class of 10 people or 10 students or so.
10 students or so. These are all use cases where I feel AI
These are all use cases where I feel AI is a very good fit. M
is a very good fit. M you you can't like have a big butcher's
you you can't like have a big butcher's knife and cut entire area and say like
knife and cut entire area and say like no this is all bad we need to have uh
no this is all bad we need to have uh you know
you know uh teachers and uh you can't replace see
uh teachers and uh you can't replace see even within the same school you may not
even within the same school you may not have all of them operating at the same
have all of them operating at the same level. Yes, of course.
level. Yes, of course. And you also cannot have um teachers
And you also cannot have um teachers being at the same level, let's say after
being at the same level, let's say after 10 years of experience
10 years of experience or probably on the from January to
or probably on the from January to February, they may have different uh
February, they may have different uh sort of uh energy level
sort of uh energy level time frame and energy. Yeah.
time frame and energy. Yeah. And people go through life stages at at
And people go through life stages at at the end of it everyone is a human being.
the end of it everyone is a human being. Yes.
Yes. And you have to be very know conscious
And you have to be very know conscious of the fact also that teachers are the
of the fact also that teachers are the lowest paid in society.
lowest paid in society. Yes. Yes. Yes,
Yes. Yes. Yes, they're not your IT worker.
they're not your IT worker. Absolutely.
Absolutely. What you can call a media person
What you can call a media person that you can sort of claim and uh there
that you can sort of claim and uh there is so much of social responsibility on
is so much of social responsibility on them. Sort of so much of emotional
them. Sort of so much of emotional responsibility on them.
responsibility on them. Correct. Correct.
Correct. Correct. So why do you want to really burden all
So why do you want to really burden all of this when you really have methods to
of this when you really have methods to improve that? Right.
improve that? Right. Yeah.
Yeah. Um and uh we always say good teachers
Um and uh we always say good teachers but how many good teachers are
but how many good teachers are available?
available? True. Right. I'm I'm sure if you go back
True. Right. I'm I'm sure if you go back to your school days or college days, I
to your school days or college days, I don't think that you'll say that all of
don't think that you'll say that all of them were equally good.
them were equally good. No, I think probably across what 16 17
No, I think probably across what 16 17 years in school and college or 18 years,
years in school and college or 18 years, maybe 10 in total.
maybe 10 in total. Correct. And maybe students in your
Correct. And maybe students in your class uh have a different opinion.
class uh have a different opinion. Yes. Each one will have a different
Yes. Each one will have a different opinion. Correct.
opinion. Correct. Correct.
Correct. Absolutely. So it's probably in in the
Absolutely. So it's probably in in the hands of people
hands of people uh to the seniors to really look at
uh to the seniors to really look at where AI can really make an impact
where AI can really make an impact and bring those for all this very
and bring those for all this very repetitive very sort of boring task like
repetitive very sort of boring task like for example answering doubts very simple
for example answering doubts very simple things like should I submit an
things like should I submit an assignment tomorrow or uh if I am a
assignment tomorrow or uh if I am a visual learner maybe you learn it better
visual learner maybe you learn it better with uh text and textbook or whatever.
with uh text and textbook or whatever. Yeah, but somebody else with images.
Yeah, but somebody else with images. I'm more of a visual learner. So why are
I'm more of a visual learner. So why are you denying me the opportunity of
you denying me the opportunity of learning it? Because at the end of the
learning it? Because at the end of the day, I'm paying my fees.
day, I'm paying my fees. Yes,
Yes, I'm not coming there to waste my time,
I'm not coming there to waste my time, right? And if I look at the lens of an
right? And if I look at the lens of an administrator,
administrator, am I if I'm going to put a parabola
am I if I'm going to put a parabola curve and I'm going to say that the
curve and I'm going to say that the first five percentile determines my
first five percentile determines my school's success,
school's success, what about the remaining 95%.
what about the remaining 95%. Yep. The big chunk.
Yep. The big chunk. Yeah. You can't say they're backbenches
Yeah. You can't say they're backbenches and they never come up in life sort of
and they never come up in life sort of story right um I mean there's lot of
story right um I mean there's lot of such discussions which has to come up
such discussions which has to come up and our our objective has been that when
and our our objective has been that when you talk about underprivileged most of
you talk about underprivileged most of them are underprivileged because of all
them are underprivileged because of all these issues
these issues correct correct
correct correct not just because of money or
not just because of money or not just money yeah
not just money yeah yeah
yeah and I gone to hundreds of colleges again
and I gone to hundreds of colleges again um if you look at the higher education
um if you look at the higher education side.
side. What is worrying for me is not the lack
What is worrying for me is not the lack of Wi-Fi or laptops. In fact, that is
of Wi-Fi or laptops. In fact, that is easy in today's world to get for
easy in today's world to get for students.
students. Yeah.
Yeah. But the critical college infrastructure
But the critical college infrastructure is missing.
is missing. The buildings are dilapidated. The labs
The buildings are dilapidated. The labs are non-existent. Uh they just don't
are non-existent. Uh they just don't have enough professors, people who are
have enough professors, people who are really skilled in their domain. So you
really skilled in their domain. So you have more systemic problems. Yeah, it's
have more systemic problems. Yeah, it's not a problem if you ask me for
not a problem if you ask me for absolutely no absolutely I'm just trying
absolutely no absolutely I'm just trying to say where are the I I actually meant
to say where are the I I actually meant it as where are the biggest challenges
it as where are the biggest challenges for administrators in general AI might
for administrators in general AI might potentially solve those some of those is
potentially solve those some of those is what I'm trying to say and then for the
what I'm trying to say and then for the students as well what are the biggest
students as well what are the biggest things they want to see changed again
things they want to see changed again educationwide because AI then becomes a
educationwide because AI then becomes a tool of sorts right it is not the
tool of sorts right it is not the solution it is a tool to bring you to a
solution it is a tool to bring you to a solution
solution that that's right. So it is it is fast
that that's right. So it is it is fast moving to a place where probably it'll
moving to a place where probably it'll replace a lot of teachers.
replace a lot of teachers. Now whether it's ethically morally
Now whether it's ethically morally correct is all up for debate.
correct is all up for debate. Yeah.
Um again uh when there is an advent of a
again uh when there is an advent of a new technology it is very tough for
new technology it is very tough for anybody to predict which direction it
anybody to predict which direction it might take.
might take. Correct.
Correct. And change doesn't happen the same
And change doesn't happen the same throughout society.
throughout society. Yep. It probably goes in like very small
Yep. It probably goes in like very small paces of change.
paces of change. Yeah.
Yeah. Now the only thing that the education
Now the only thing that the education sector system administrators have to
sector system administrators have to realize is this change is permanent.
realize is this change is permanent. Yes.
Yes. We're not going to go back to a preAI
We're not going to go back to a preAI era.
era. Yeah.
Yeah. Now start planning for that and then
Now start planning for that and then start you start putting in things which
start you start putting in things which will start changing the system and
will start changing the system and things for the better.
things for the better. Um, you can't like put your hand head in
Um, you can't like put your hand head in the sand and behave like a ostrich,
the sand and behave like a ostrich, right?
right? Ostrich. Yeah. Yeah.
Ostrich. Yeah. Yeah. I'm not going to change all of this
I'm not going to change all of this stuff and nothing is going to change.
stuff and nothing is going to change. You know, good teachers are there. I
You know, good teachers are there. I think that era is over,
think that era is over, right? It's all about skills, right? I
right? It's all about skills, right? I mean, Singapore, for example, the
mean, Singapore, for example, the government is very clear, right? You got
government is very clear, right? You got to upskill. You got to skill yourself.
to upskill. You got to skill yourself. You're not going to sit down and just
You're not going to sit down and just take paper certificates, paper degrees.
take paper certificates, paper degrees. And uh that explains lot of issues in
And uh that explains lot of issues in the job market. So I'm saying that
the job market. So I'm saying that everything is intertwined with each
everything is intertwined with each other. It's not like one issue you can
other. It's not like one issue you can just separate and
just separate and absolutely you you are like sort of
absolutely you you are like sort of already late into this AI game.
already late into this AI game. Uh ideally people should have started 10
Uh ideally people should have started 10 years back
years back and I don't know why they didn't. We've
and I don't know why they didn't. We've been like shouting from the rooftops
been like shouting from the rooftops saying that everybody must be skilled in
saying that everybody must be skilled in AI. uh we did a lot of programs and
AI. uh we did a lot of programs and stuff like that and even now I'm saying
stuff like that and even now I'm saying that the resistance which people are
that the resistance which people are showing in the education sector is
showing in the education sector is mindboggling
mindboggling yes because it is change and change like
yes because it is change and change like you said everybody's afraid of change
you said everybody's afraid of change right like you said first is I lose my
right like you said first is I lose my job the computer science department oops
job the computer science department oops I'm gone I'm I'm history why should I
I'm gone I'm I'm history why should I change and and we see it across not just
change and and we see it across not just education right in every part of facet
education right in every part of facet of the world change is the this
of the world change is the this stumbling block so to say because oops
stumbling block so to say because oops it's fear
it's fear that's right
that's right so you're absolutely right yeah okay
so you're absolutely right yeah okay cool so if you had to look at just
cool so if you had to look at just putting a vision visionary lens ahead
putting a vision visionary lens ahead right and say five years on three I
right and say five years on three I would say let's say three years because
would say let's say three years because AI is changing so rapidly I think
AI is changing so rapidly I think predicting five years is too long maybe
predicting five years is too long maybe two years down the road or whatever you
two years down the road or whatever you think you tell me one year is good two
think you tell me one year is good two years good three years What is the
years good three years What is the biggest change in education do you
biggest change in education do you foresee AI bringing? And I'm not talking
foresee AI bringing? And I'm not talking Singapore because Singapore is a bit
Singapore because Singapore is a bit unique. But if you look at countries
unique. But if you look at countries like Malaysia, India, Indonesia, what is
like Malaysia, India, Indonesia, what is the one big
the one big flick that AI will really cause that
flick that AI will really cause that will change that could change?
will change that could change? Sure.
Sure. Let me just show a real uh
Let me just show a real uh thing so it's easy for
thing so it's easy for just to explain my use case. Okay, cool.
just to explain my use case. Okay, cool. Okay, so are you able to see my screen?
Okay, so are you able to see my screen? Yeah.
Yeah. Okay. So, what I'm just showing you on
Okay. So, what I'm just showing you on screen is my platform, the AI agent
screen is my platform, the AI agent platform, smart, right?
platform, smart, right? Now, could you guess how much time I
Now, could you guess how much time I would have taken to create this
would have taken to create this platform?
platform? I mean, using AI, I don't know, probably
I mean, using AI, I don't know, probably half a day less, 10 minutes.
half a day less, 10 minutes. Okay. So this is a very complicated
Okay. So this is a very complicated platform because we have more than 300
platform because we have more than 300 plus AI agents, right? So for example,
plus AI agents, right? So for example, if I just take education tools,
if I just take education tools, we have developed about 96 tools which
we have developed about 96 tools which helps a teacher or student do everything
helps a teacher or student do everything from behavior support ideas to uh
from behavior support ideas to uh classroom humor assistant to whatever.
classroom humor assistant to whatever. Right.
Right. Right. Right.
Right. Right. Now how many uh like say team members
Now how many uh like say team members you think could have developed all of
you think could have developed all of this? So we we have all these education
this? So we we have all these education tools. We have another 100 uh marketing
tools. We have another 100 uh marketing tools, sales tools. Then we have tools
tools, sales tools. Then we have tools which help us with uh meme generation,
which help us with uh meme generation, PPT generation, you know, all of that.
PPT generation, you know, all of that. Just just a guess,
Just just a guess, three people maybe.
three people maybe. I just did it all by myself.
I just did it all by myself. And
And surprisingly, the whole thing was also
surprisingly, the whole thing was also done by AI.
done by AI. Mhm. in the sense it's not that I used
Mhm. in the sense it's not that I used AI and then AI went and coded. I use AI
AI and then AI went and coded. I use AI so that it can independently create a
so that it can independently create a lot of these products by itself.
lot of these products by itself. Okay. Okay.
Okay. Okay. Right. So imagine training an AI to
Right. So imagine training an AI to develop its own AI.
develop its own AI. So that's a sort of I just want to bring
So that's a sort of I just want to bring across the productivity point
across the productivity point right
right if you had asked me in my tenure earlier
if you had asked me in my tenure earlier in companies like IBM or so I probably
in companies like IBM or so I probably would have said okay this is going to
would have said okay this is going to take let's say 6 months and then
take let's say 6 months and then probably we need a 15 member team we do
probably we need a 15 member team we do everything from they say waterfall model
everything from they say waterfall model or you know different sorts of models
or you know different sorts of models project management the investments in
project management the investments in real estate and you know you can name
real estate and you know you can name all of this probably it would have cost
all of this probably it would have cost me up to a million dollars to develop
me up to a million dollars to develop something like this.
something like this. Now I can just do it for probably less
Now I can just do it for probably less than a few hundred over a period of
than a few hundred over a period of let's say 1 month or so just by myself
let's say 1 month or so just by myself and this is the most latest tech stack
and this is the most latest tech stack also
also right
right so you can imagine the productivity
so you can imagine the productivity which could come now in every segment of
which could come now in every segment of society. Yeah, absolutely.
society. Yeah, absolutely. If you are a lawyer, you could probably
If you are a lawyer, you could probably attend to more cases,
attend to more cases, you could probably instead of having
you could probably instead of having parallegals, right, as they say, uh
parallegals, right, as they say, uh instead of you having 15 juniors team,
instead of you having 15 juniors team, you probably could do it with three
you probably could do it with three juniors.
juniors. Mhm.
Mhm. And you can probably take on more cases.
And you can probably take on more cases. Mhm.
Mhm. Right. If you're a doctor, probably you
Right. If you're a doctor, probably you can segregate your patients and probably
can segregate your patients and probably you could attend to more patients,
you could attend to more patients, increasing your revenue.
increasing your revenue. Yeah. Yeah.
Yeah. Yeah. Right.
Right. Yeah. Now, if I'm a teacher, I could now
Yeah. Now, if I'm a teacher, I could now teach more students
teach more students and have more one-on-one with students
and have more one-on-one with students who really require it
who really require it and allow the others to have the power
and allow the others to have the power of AI to really learn these concepts
of AI to really learn these concepts and uh as I said automate all of the
and uh as I said automate all of the other stuff that is required right from
other stuff that is required right from assessment to your questioning to any of
assessment to your questioning to any of these things which are out over there
these things which are out over there right and I could have continuous
right and I could have continuous assessment I don't have to have let's
assessment I don't have to have let's say two assessments ments half yearly or
say two assessments ments half yearly or yearly.
yearly. I don't have to have maybe monthly test
I don't have to have maybe monthly test and
and I could literally have a report card
I could literally have a report card which is very genuine about a student's
which is very genuine about a student's progress.
progress. Yeah.
Yeah. And I could probably get more metrics in
And I could probably get more metrics in terms of where a student is falling off.
terms of where a student is falling off. Let's say what is an acceptable level of
Let's say what is an acceptable level of learning
learning and then I can plan my interventions.
and then I can plan my interventions. Today it's not scientific, right?
Today it's not scientific, right? Yeah. It is just the teacher looks into
Yeah. It is just the teacher looks into the class physically, visually and then
the class physically, visually and then they come to some conclusions.
they come to some conclusions. Yeah.
Yeah. Yeah. Some
Yeah. Some some international schools might say we
some international schools might say we are dashboards, analytics and all of
are dashboards, analytics and all of that. But this that is all post the
that. But this that is all post the event, right? Not prior to the event.
event, right? Not prior to the event. Correct.
Correct. And they give out whatever cards, report
And they give out whatever cards, report cards which is basically having bunch of
cards which is basically having bunch of numbers which you can't interpret in any
numbers which you can't interpret in any meaningful way.
meaningful way. Meaningful way. Yeah.
Meaningful way. Yeah. Yeah. There are more milestones, right?
Yeah. There are more milestones, right? That is not progress.
That is not progress. Yeah. Yeah. Yeah. Correct. Correct.
Yeah. Yeah. Yeah. Correct. Correct. You're right. I think people forget they
You're right. I think people forget they mix up the two.
mix up the two. Yeah. So I have to assume the progress
Yeah. So I have to assume the progress that's a problem.
that's a problem. Right. So that is the ways that you
Right. So that is the ways that you could be more innovative and I think
could be more innovative and I think this is the direction the vision in
this is the direction the vision in which the whole thing has to go in terms
which the whole thing has to go in terms of uh making it much more productive
of uh making it much more productive for everyone concerned and making it as
for everyone concerned and making it as a win-win situation.
a win-win situation. not the sort of friction I'm seeing
not the sort of friction I'm seeing today on a daily basis in the education
today on a daily basis in the education sector.
sector. Yeah. Yeah. Point.
Yeah. Yeah. Point. Yeah.
Yeah. And I I I have students who you won't
And I I I have students who you won't believe it right from the junior schools
believe it right from the junior schools who have been doing much more complex
who have been doing much more complex engagements and not necessarily IT
engagements and not necessarily IT projects. You know, everybody thinks
projects. You know, everybody thinks that you're teaching it computer science
that you're teaching it computer science projects.
projects. It could be everything from biology to
It could be everything from biology to chemistry,
chemistry, right?
right? they could adopt it as part of their
they could adopt it as part of their overall learning perspective.
overall learning perspective. Like for example, if I looked at uh the
Like for example, if I looked at uh the subject of history, I mean my daughter
subject of history, I mean my daughter came to me and uh she actually asked me
came to me and uh she actually asked me a question about who was the real sort
a question about who was the real sort of mentor or guru of Napoleon.
of mentor or guru of Napoleon. Uh of course I didn't know that. So I
Uh of course I didn't know that. So I said like um um I I was saying I think
said like um um I I was saying I think it was his one of his uh that political
it was his one of his uh that political gurus or somebody and some name was
gurus or somebody and some name was there sort of stuff.
there sort of stuff. Then she argued no because my book says
Then she argued no because my book says that it's his some aunt or somebody was
that it's his some aunt or somebody was the real mentor.
the real mentor. I said well I'm busy I can't really sit
I said well I'm busy I can't really sit down and figure out all of this stuff
down and figure out all of this stuff but why don't I do one thing. So I said
but why don't I do one thing. So I said uh go gone into voice mode with charg
uh go gone into voice mode with charg and said like charge assume yourself you
and said like charge assume yourself you are Napoleon
are Napoleon have a chat with my daughter and answer
have a chat with my daughter and answer all these questions
all these questions then she put the chat GPD on the spot by
then she put the chat GPD on the spot by crossquesting a lot of stuff
crossquesting a lot of stuff and then she could go to many sources of
and then she could go to many sources of information including let's say books
information including let's say books from library or her own books or
from library or her own books or Wikipedia and things like that to come
Wikipedia and things like that to come to a conclusion as to what really
to a conclusion as to what really happened.
Now that process was enlightening for me as thinking that students could now
as thinking that students could now really use AI in the sense of uh you
really use AI in the sense of uh you know getting as we say from the horse's
know getting as we say from the horse's mouth.
mouth. Mhm.
Mhm. What if we get Einstein to come and
What if we get Einstein to come and teach you calculus?
teach you calculus? That's the sort of innovation we should
That's the sort of innovation we should bring in rather than worry about saying
bring in rather than worry about saying that whether AI is hallucinating or
that whether AI is hallucinating or whatever because you have to be in a
whatever because you have to be in a position where you can really analyze
position where you can really analyze um you can cross check lot of stuff
um you can cross check lot of stuff nowadays. I I think that is a very
nowadays. I I think that is a very important point you mentioned about your
important point you mentioned about your daughter's u discussion with you the
daughter's u discussion with you the cross questioning you know the the
cross questioning you know the the concept of crossqu questioning
concept of crossqu questioning comes in when you are able to think and
comes in when you are able to think and challenge that you know I can't take
challenge that you know I can't take everything at face value which is kind
everything at face value which is kind of where the hallucination story also is
of where the hallucination story also is right now right
right now right so one piece is then
so one piece is then how is it going to happen that
how is it going to happen that hallucinations will I won't say minimize
hallucinations will I won't say minimize rather then go to zero because I don't I
rather then go to zero because I don't I can't foresee it. I'm sure they'll go
can't foresee it. I'm sure they'll go down to close to zero. That's one. And
down to close to zero. That's one. And can there be a will that there be a
can there be a will that there be a default state of affairs that in any AI
default state of affairs that in any AI application hallucination will be
application hallucination will be minimized? That's one. Let's assume that
minimized? That's one. Let's assume that happens. But
happens. But if AI becomes a very very integral
if AI becomes a very very integral tool for education across
tool for education across demand and supply very simplistically
demand and supply very simplistically teachers, educators and students,
teachers, educators and students, will they still be able how will they
will they still be able how will they continue being able to cross question or
continue being able to cross question or think that they have to question it? And
think that they have to question it? And secondly,
do you see a reduction in tactical and t sorry tactile experiences because of
sorry tactile experiences because of reliance on AI? That means a lot of our
reliance on AI? That means a lot of our motor skills etc will go down.
motor skills etc will go down. That is another part of the pie, right?
That is another part of the pie, right? That you know I'm constantly looking at
That you know I'm constantly looking at a screen and asking for guidance and
a screen and asking for guidance and looking for answers. But am I therefore
looking for answers. But am I therefore not able to if you play a game of
not able to if you play a game of cricket am I playing the ball correctly?
cricket am I playing the ball correctly? the best possible way to hit a cover
the best possible way to hit a cover drive or bowl the best leg break like a
drive or bowl the best leg break like a Shane Ward something like so so the
Shane Ward something like so so the tactile experience part are we going to
tactile experience part are we going to lose or how do you see that being
lose or how do you see that being impacted by AI over time
impacted by AI over time it's it's purely up to I would say the
it's it's purely up to I would say the people concerned to figure out what is
people concerned to figure out what is the fit use case of AI as to where it
the fit use case of AI as to where it can give you the maximum impact
can give you the maximum impact um I mean to be If you look at for
um I mean to be If you look at for example aviation industry, I was quite
example aviation industry, I was quite surprised that when I found out that
surprised that when I found out that many of the pilots they actually start
many of the pilots they actually start off with the Microsoft flight simulator.
off with the Microsoft flight simulator. Uh then I'm like did they really fly the
Uh then I'm like did they really fly the real planes or probably it was just a
real planes or probably it was just a warm-up before they learn to re the real
warm-up before they learn to re the real planes.
planes. Yes. So uh you do have this sort of real
Yes. So uh you do have this sort of real world experiences where people probably
world experiences where people probably are using technology as more of a
are using technology as more of a simulation for doing a lot of stuff.
simulation for doing a lot of stuff. Yeah.
Yeah. And uh then figure out as to whether u
And uh then figure out as to whether u you go into more uh what you can call
you go into more uh what you can call lesser risk aspects of learning or
lesser risk aspects of learning or implementing.
implementing. So if I'm a let's say I am a city
So if I'm a let's say I am a city planner, I'm a civil engineer.
planner, I'm a civil engineer. Yeah. and I I have to plan for some
Yeah. and I I have to plan for some buildings or some new stuff. Am I going
buildings or some new stuff. Am I going to not use AI
to not use AI and lose out on that whole simulation
and lose out on that whole simulation because AI can probably think in many
because AI can probably think in many data points?
data points? Yeah.
Yeah. Or am I going to still rely on older
Or am I going to still rely on older methods where probably the risk is much
methods where probably the risk is much higher.
higher. I mean I still have to build the
I mean I still have to build the buildings. Yeah. It's not going to do
buildings. Yeah. It's not going to do that for you. Probably it might with
that for you. Probably it might with robots later on. Yeah,
robots later on. Yeah, that is looking at the extremes.
that is looking at the extremes. Mhm. Mhm.
Mhm. Mhm. So we are looking at how do we reduce
So we are looking at how do we reduce the risk on the planet?
the risk on the planet? Yeah.
Yeah. Like if I'm a business guy, how do I
Like if I'm a business guy, how do I reduce the risk for my business?
reduce the risk for my business? I that's no tactile experience I need to
I that's no tactile experience I need to bring in here. I probably have to run a
bring in here. I probably have to run a lot of simulations, lot of strategy
lot of simulations, lot of strategy frameworks.
frameworks. Yeah.
Yeah. And I'm good to go.
And I'm good to go. Right. I could test a lot of business
Right. I could test a lot of business models. H I could ask Charg to be an
models. H I could ask Charg to be an expert to figure out the like loopholes
expert to figure out the like loopholes some places you need regulatory
some places you need regulatory oversight probably things like
oversight probably things like healthcare or insurance
healthcare or insurance that is default right
that is default right correct
correct you don't want to trust a drug which is
you don't want to trust a drug which is created by charg
created by charg oh yeah for sure yeah
oh yeah for sure yeah right
right yeah yeah
yeah yeah just give me a second Yeah.
Yeah. Sorry about that. No problem. Okay. So it's it's
No problem. Okay. So it's it's definitely going to be a booming
definitely going to be a booming industry for people to figure out as to
industry for people to figure out as to what's going to happen in which industry
what's going to happen in which industry to what level I have to implement and
to what level I have to implement and see we keep referring even in this
see we keep referring even in this podcast around things only around chd or
podcast around things only around chd or products like Maya but uh the the the I
products like Maya but uh the the the I would say the negative aspect of all the
would say the negative aspect of all the hype is people only think AI is charged
hype is people only think AI is charged is AI which is wrong
is AI which is wrong this is other AI technology machine
this is other AI technology machine learning computer vision uh things which
learning computer vision uh things which are happening out So it is literally a
are happening out So it is literally a mistake not to think about the impact of
mistake not to think about the impact of all of those um on lot of stuff which is
all of those um on lot of stuff which is happening in the world and there
happening in the world and there silently it's happening all around us.
silently it's happening all around us. Yeah absolutely true. Yeah, one one last
Yeah absolutely true. Yeah, one one last piece which I asked you earlier cross
piece which I asked you earlier cross questioning. How do you think um it's
questioning. How do you think um it's that part is going to evolve if people
that part is going to evolve if people rely more and more on AI?
rely more and more on AI? How do you check validation? Is this
How do you check validation? Is this correct verification
correct verification that this I should believe this? Because
that this I should believe this? Because that's I think a lot of students today
that's I think a lot of students today also find that as a challenge that
also find that as a challenge that there's so much information out there. I
there's so much information out there. I don't know what to believe and what not
don't know what to believe and what not to believe.
to believe. So it's for you to um two aspects right.
So it's for you to um two aspects right. Again, you have to be clear where AI can
Again, you have to be clear where AI can really help you.
really help you. No, but as students, you might struggle
No, but as students, you might struggle probably is what I'm trying to think.
probably is what I'm trying to think. Teachers at least, let's say, slightly
Teachers at least, let's say, slightly more thought through process maybe.
more thought through process maybe. But the younger generation,
But the younger generation, that's right. You can't blindly believe
that's right. You can't blindly believe AI. That's for sure.
AI. That's for sure. But at least
But at least how would they go about crossquestioning
how would they go about crossquestioning is the
is the that part is then is it a home thing
that part is then is it a home thing where you and at at home, how are you
where you and at at home, how are you taught to think and learn or also at
taught to think and learn or also at school along with peers? Is it all going
school along with peers? Is it all going to be a mix of I'm so I'm trying to
to be a mix of I'm so I'm trying to bring back the social side into the tech
bring back the social side into the tech side and saying a better combination of
side and saying a better combination of the two.
the two. Yes. So if you are going to as I said
Yes. So if you are going to as I said blindly believe AI is going to lead to a
blindly believe AI is going to lead to a lot of problems.
lot of problems. Um but you also have to have a lot of
Um but you also have to have a lot of common sense in terms of how do I really
common sense in terms of how do I really cross check a lot of stuff that AI is
cross check a lot of stuff that AI is doing.
doing. So for example if I'm doing a math
So for example if I'm doing a math problem it's very easy for me to cross
problem it's very easy for me to cross verify. I just solve it and figure out
verify. I just solve it and figure out whether it's correct or not.
whether it's correct or not. Yeah. Right.
Yeah. Right. But when it comes to things like
But when it comes to things like debates,
debates, whether
whether uh something happened or did not happen
uh something happened or did not happen or what was the real reason it did or
or what was the real reason it did or whatever. The problem is even in today's
whatever. The problem is even in today's society, a lot of these things are up
society, a lot of these things are up for debate.
for debate. That's true. That's true.
That's true. That's true. You may have learned history in a
You may have learned history in a certain way. I may have learned it
certain way. I may have learned it differently. We may not both agree uh
differently. We may not both agree uh you know as to what really happened. I
you know as to what really happened. I may I may like my version of the story.
may I may like my version of the story. Yeah. Yeah. Yeah. what I got taught
Yeah. Yeah. Yeah. what I got taught the personal biases of sorts unconscious
the personal biases of sorts unconscious correct
correct preferences not biases
preferences not biases so I always say that the issues with all
so I always say that the issues with all of these is not about AI AI is just
of these is not about AI AI is just trained on data from society
trained on data from society correct
correct if you are having all fake data
if you are having all fake data artificial data data which is in one
artificial data data which is in one direction well AI is also going to top
direction well AI is also going to top down the same stuff
down the same stuff correct it almost is like your prompt
correct it almost is like your prompt engineering right the the way you ask
engineering right the the way you ask your question you'll get an answer on
your question you'll get an answer on the on the chat GPT equivalent models
the on the chat GPT equivalent models Correct. Correct.
Correct. Correct. Almost biased towards your question.
Yeah. So that's that's the thing that you know we it's it's a tall order,
you know we it's it's a tall order, right? It's more often uh we call it as
right? It's more often uh we call it as the paradise which probably will never
the paradise which probably will never reach. Um are we going to eliminate all
reach. Um are we going to eliminate all that so-called bias and things and stuff
that so-called bias and things and stuff like that? I doubt it's going to happen.
like that? I doubt it's going to happen. Yeah.
Yeah. But if you don't do that then don't
But if you don't do that then don't blame the AI.
blame the AI. I think that is that is the important
I think that is that is the important point that don't blame the tool, don't
point that don't blame the tool, don't blame the messenger pretty much.
blame the messenger pretty much. Correct. So it's it's it's a it's a it's
Correct. So it's it's it's a it's a it's a societal issue. It's got nothing to do
a societal issue. It's got nothing to do with the technology per se and um it's
with the technology per se and um it's not it's not going to get better,
not it's not going to get better, right?
right? It's it's a um AI is like uh say it's
It's it's a um AI is like uh say it's it's an amplification.
it's an amplification. If you already have a problem, it's only
If you already have a problem, it's only going to amplify the problem. It's not
going to amplify the problem. It's not going to solve the problem.
going to solve the problem. Yeah.
Yeah. Either the problem or the the solution.
Either the problem or the the solution. Either way, it'll amplify. One of the
Either way, it'll amplify. One of the two.
two. Yeah. In computer science, we have the
Yeah. In computer science, we have the term called gigo, right? Garbage in,
term called gigo, right? Garbage in, garbage out.
garbage out. Yep. Yep. Yep.
Yep. Yep. Yep. So, if you have rotten society, it's
So, if you have rotten society, it's going to be equally rotten.
going to be equally rotten. Very true. This is very, very true. It's
Very true. This is very, very true. It's a societal issue. You're right.
a societal issue. You're right. Absolutely. Cool. I'm Hey, thanks a lot
Absolutely. Cool. I'm Hey, thanks a lot for your time, Chandra. This is really
for your time, Chandra. This is really useful. Um, I will, like I said, you are
useful. Um, I will, like I said, you are the very first person I'm talking to.
the very first person I'm talking to. I'm going to talk to a few more and as I
I'm going to talk to a few more and as I put stuff together, I'm happy to share
put stuff together, I'm happy to share it with you.
it with you. Sure.
Sure. And maybe one day I'll also introduce
And maybe one day I'll also introduce you to this person here in Singapore who
you to this person here in Singapore who runs the nonprofit and let's see. If
runs the nonprofit and let's see. If nothing else, it will be a good
nothing else, it will be a good conversation with them.
conversation with them. Absolutely. Always nice to network,
Absolutely. Always nice to network, right?
right? And let's catch up some point in time
And let's catch up some point in time anyway. Oh,
anyway. Oh, sure. Sure. We will do. Yeah. All right.
sure. Sure. We will do. Yeah. All right. We'll do. Thanks so much, Andra. Catch
We'll do. Thanks so much, Andra. Catch you later. Thank you. Bye. Bye.
Full Episode Transcript
[0:02] Morning Toshar. So yeah great to again uh catch
[0:05] Toshar. So yeah great to again uh catch up right and uh welcome to my podcast.
[0:07] up right and uh welcome to my podcast. So essential idea was when you reached
[0:09] So essential idea was when you reached out I knew this is an important topic of
[0:11] out I knew this is an important topic of AI and education especially for the
[0:14] AI and education especially for the underprivileged uh kids students.
[0:17] underprivileged uh kids students. Um yes we have been doing quite a bit of
[0:19] Um yes we have been doing quite a bit of work in the past eight years much before
[0:22] work in the past eight years much before even Chad GPT got launched.
[0:24] even Chad GPT got launched. Yes. And uh uh I know we spoke uh
[0:27] Yes. And uh uh I know we spoke uh probably some of it during our meet up
[0:30] probably some of it during our meet up for the startup evaluation uh sessions,
[0:33] for the startup evaluation uh sessions, right? Um so uh you you mentioned of
[0:38] right? Um so uh you you mentioned of course you are going to be delivering a
[0:40] course you are going to be delivering a talk as well as uh uh probably a write
[0:42] talk as well as uh uh probably a write up in terms of the same uh
[0:46] up in terms of the same uh intent on AI and education for
[0:47] intent on AI and education for underprivileged right?
[0:48] underprivileged right? Yes. So um broadly I I will just give a
[0:52] Yes. So um broadly I I will just give a broad sort of introduction then you ask
[0:54] broad sort of introduction then you ask me questions so it's easy for me to sure
[0:57] me questions so it's easy for me to sure you don't want to monologue.
[0:59] you don't want to monologue. Yeah yeah totally agree with you.
[1:00] Yeah yeah totally agree with you. Yeah. So um of all the um I would call
[1:06] Yeah. So um of all the um I would call as the domains that artificial
[1:08] as the domains that artificial intelligence as a technology
[1:10] intelligence as a technology has uh immediately impacted the first
[1:13] has uh immediately impacted the first one has been education.
[1:15] one has been education. Mhm. Um, of course, when you look at uh
[1:18] Mhm. Um, of course, when you look at uh the broad hype about uh uh products like
[1:21] the broad hype about uh uh products like Chad GPT or Anthropic or you you name
[1:23] Chad GPT or Anthropic or you you name it, right? I mean, I'm sure there are
[1:25] it, right? I mean, I'm sure there are some 200 different products which are
[1:26] some 200 different products which are now quite popular
[1:28] now quite popular and we are hearing about unheard sums of
[1:30] and we are hearing about unheard sums of money and investment pouring into all
[1:32] money and investment pouring into all this sector.
[1:34] this sector. But the constant sort of gripe among
[1:36] But the constant sort of gripe among people is there is no viable business
[1:37] people is there is no viable business use case
[1:39] use case and it's like uh it's all hype and there
[1:42] and it's like uh it's all hype and there actually not leading to anything. uh one
[1:44] actually not leading to anything. uh one side we have CEOs who are saying it's
[1:46] side we have CEOs who are saying it's leading to job losses they are replacing
[1:48] leading to job losses they are replacing 30% of the workforce but on the other
[1:51] 30% of the workforce but on the other hand if you look at it people are still
[1:53] hand if you look at it people are still hiring people I don't at least I've not
[1:55] hiring people I don't at least I've not seen any magical AI agent replacing
[1:58] seen any magical AI agent replacing people end to end sort of stuff
[2:00] people end to end sort of stuff at best we may have heard about some
[2:02] at best we may have heard about some people doing some uh content getting uh
[2:05] people doing some uh content getting uh created or probably about code being
[2:08] created or probably about code being generated and things like that
[2:10] generated and things like that yep
[2:11] yep um however when we look at the education
[2:14] um however when we look at the education space and this is something we did
[2:15] space and this is something we did notice even as I said about 8 years back
[2:18] notice even as I said about 8 years back when I started off wisely wise and now
[2:19] when I started off wisely wise and now we have the product on smart me uh we
[2:22] we have the product on smart me uh we did notice that AI has the capability of
[2:27] did notice that AI has the capability of uh rapidly disrupting every facet of
[2:29] uh rapidly disrupting every facet of education
[2:31] education and uh if you look at uh usually the top
[2:35] and uh if you look at uh usually the top three sort of complaints about the
[2:37] three sort of complaints about the education industry per se is one it has
[2:39] education industry per se is one it has become very industrialized which means
[2:41] become very industrialized which means there's no sort of personalized
[2:44] there's no sort of personalized attention given to students defeating
[2:47] attention given to students defeating the very purpose of going to school.
[2:49] the very purpose of going to school. Yeah.
[2:49] Yeah. Second that uh sort of I would say uh
[2:54] Second that uh sort of I would say uh social initiative of education has come
[2:58] social initiative of education has come uh become very commercialized. Uh it's a
[3:01] uh become very commercialized. Uh it's a business right today we call it as an
[3:03] business right today we call it as an industry.
[3:04] industry. Yes.
[3:05] Yes. While that's a disconnect. So if I say
[3:07] While that's a disconnect. So if I say for example I'm launching an e-commerce
[3:09] for example I'm launching an e-commerce business people are happy about it. But
[3:12] business people are happy about it. But uh the same thing if you try to do
[3:14] uh the same thing if you try to do something in education people are more
[3:16] something in education people are more suspicious and you don't really want to
[3:18] suspicious and you don't really want to associate profit making with education
[3:21] associate profit making with education sector
[3:22] sector so overtly profit centered you don't
[3:24] so overtly profit centered you don't want it to be
[3:25] want it to be that's a I would just say societal
[3:27] that's a I would just say societal perception right in terms of how
[3:29] perception right in terms of how education as a sector I mean education
[3:31] education as a sector I mean education healthcare are two sectors which come to
[3:33] healthcare are two sectors which come to my mind where people um don't want to be
[3:38] my mind where people um don't want to be like be seen as profit taking
[3:41] like be seen as profit taking uh reality might be different but that's
[3:42] uh reality might be different but that's a story for another podcast
[3:44] a story for another podcast but
[3:46] but this is the second gripe against this
[3:48] this is the second gripe against this particular area domain vertical whatever
[3:50] particular area domain vertical whatever you call it right
[3:51] you call it right third is of course uh the cost of
[3:54] third is of course uh the cost of education has gone up tremendously high
[3:57] education has gone up tremendously high whether it's tuition fees it is the cost
[3:59] whether it's tuition fees it is the cost of other allied stuff and uh people
[4:03] of other allied stuff and uh people nowadays call it as a supply chain so
[4:05] nowadays call it as a supply chain so you start from somewhere in your uh
[4:07] you start from somewhere in your uh kindergarten years then go on to
[4:10] kindergarten years then go on to schooling for 12 years and then college
[4:12] schooling for 12 years and then college is probably another four years and uh
[4:15] is probably another four years and uh there is no way that anybody can escape
[4:17] there is no way that anybody can escape this. Finally land up in the rat race in
[4:20] this. Finally land up in the rat race in the corporate world and uh the cost of
[4:24] the corporate world and uh the cost of doing this and going into very specific
[4:26] doing this and going into very specific brands has skyrocketed in the past few
[4:29] brands has skyrocketed in the past few years.
[4:30] years. True. Um while on one hand you do see
[4:33] True. Um while on one hand you do see many colleges and universities opening
[4:35] many colleges and universities opening up, people can travel freely but still
[4:38] up, people can travel freely but still it is a big chunk of anybody's salary.
[4:41] it is a big chunk of anybody's salary. Yeah, absolutely.
[4:42] Yeah, absolutely. So these are the top three if you ask me
[4:45] So these are the top three if you ask me are the gripe against industry and AI is
[4:47] are the gripe against industry and AI is seen as a savior here. Why one you could
[4:50] seen as a savior here. Why one you could do personalized one is to one education
[4:52] do personalized one is to one education through chat bots and you know uh other
[4:55] through chat bots and you know uh other forms like you have of course like your
[4:58] forms like you have of course like your um products like Chad GBT which you can
[5:00] um products like Chad GBT which you can build other products and things like
[5:01] build other products and things like that
[5:02] that second is uh uh of course it cannot be
[5:05] second is uh uh of course it cannot be too costly right because it's the same
[5:08] too costly right because it's the same AI many people can share the same chat
[5:10] AI many people can share the same chat bot so costs probably are going to you
[5:12] bot so costs probably are going to you know really come down and u obviously
[5:15] know really come down and u obviously because the costs are coming down it's
[5:17] because the costs are coming down it's not going to be seen being profit
[5:19] not going to be seen being profit making. I mean how much can you earn
[5:21] making. I mean how much can you earn from a chatbot? Um so uh because you're
[5:25] from a chatbot? Um so uh because you're not like for example going to have uh
[5:27] not like for example going to have uh lot of people, teachers, human
[5:29] lot of people, teachers, human employees. So the costs are going up. if
[5:30] employees. So the costs are going up. if I need to have a building, you know, all
[5:32] I need to have a building, you know, all of those cost are
[5:34] of those cost are so AI is seen as a savior and that's why
[5:36] so AI is seen as a savior and that's why it is um coming up with a very rapid
[5:39] it is um coming up with a very rapid adoption in this particular um segment.
[5:43] adoption in this particular um segment. And uh I see my personal experiences
[5:45] And uh I see my personal experiences teachers, professors gain a lot by
[5:48] teachers, professors gain a lot by adopting AI.
[5:50] adopting AI. It brings down their levels of u um
[5:53] It brings down their levels of u um work. The administrative work alone is
[5:55] work. The administrative work alone is uh probably 40 to 60% depending upon the
[5:58] uh probably 40 to 60% depending upon the level of teacher.
[6:00] level of teacher. Correct. And uh in the US the number one
[6:02] Correct. And uh in the US the number one cause of turnover of teachers is uh
[6:05] cause of turnover of teachers is uh stress felt by the teachers which I'm
[6:07] stress felt by the teachers which I'm sure is true in other countries as
[6:10] sure is true in other countries as almost everywhere. Yeah.
[6:11] almost everywhere. Yeah. Yeah. And my my mom herself used to be a
[6:13] Yeah. And my my mom herself used to be a teacher and I firsthand seen that even
[6:15] teacher and I firsthand seen that even like 30 years back uh the amount of
[6:18] like 30 years back uh the amount of administrative work a teacher has to do.
[6:20] administrative work a teacher has to do. Uh everything from creating lesson plans
[6:23] Uh everything from creating lesson plans to creating uh what we call as notes of
[6:25] to creating uh what we call as notes of lessons and then submitting to
[6:27] lessons and then submitting to authorities. I I could go on and on and
[6:29] authorities. I I could go on and on and on.
[6:30] on. Yeah. Yeah.
[6:31] Yeah. Yeah. And whenever the government launches a
[6:33] And whenever the government launches a new scheme in many countries, they
[6:34] new scheme in many countries, they actually use the teachers as the civil
[6:37] actually use the teachers as the civil servants to go out and implement those
[6:39] servants to go out and implement those schemes.
[6:41] schemes. So you would see that AI is being used
[6:44] So you would see that AI is being used now by teachers to bring down that
[6:47] now by teachers to bring down that administrative work.
[6:48] administrative work. Right? Slowly it has also gone to the
[6:51] Right? Slowly it has also gone to the level where uh teachers are using it to
[6:53] level where uh teachers are using it to let's say correct
[6:55] let's say correct exam papers, set new exam papers,
[6:58] exam papers, set new exam papers, set papers. Yeah,
[6:59] set papers. Yeah, it it could now suddenly you know it's
[7:01] it it could now suddenly you know it's all about content creation and uh the
[7:04] all about content creation and uh the teachers find that instead of me
[7:06] teachers find that instead of me spending like uh two weeks 3 weeks I can
[7:09] spending like uh two weeks 3 weeks I can do it in probably 3 hours or four hours.
[7:11] do it in probably 3 hours or four hours. Mhm. Mhm.
[7:12] Mhm. Mhm. Right. And many of them are doing many
[7:14] Right. And many of them are doing many creative
[7:15] creative uh things with that. uh it could extend
[7:17] uh things with that. uh it could extend not just in terms of uh lesson plans but
[7:20] not just in terms of uh lesson plans but it could be in terms of creating images
[7:22] it could be in terms of creating images um it could be in terms of even videos
[7:24] um it could be in terms of even videos nowadays voice based things so suddenly
[7:28] nowadays voice based things so suddenly teachers are also seeing theirh teaching
[7:30] teachers are also seeing theirh teaching techniques are becoming more effective
[7:32] techniques are becoming more effective why because it's no more the written
[7:34] why because it's no more the written word
[7:35] word I can use so many forms of communication
[7:39] I can use so many forms of communication multimodal kind of a
[7:41] multimodal kind of a correct
[7:42] correct concept as well
[7:43] concept as well correct now the same thing if uh people
[7:46] correct now the same thing if uh people argue that we always had CBDs right
[7:48] argue that we always had CBDs right computer based tutorials we had YouTube
[7:49] computer based tutorials we had YouTube and all of that.
[7:51] and all of that. Yeah.
[7:51] Yeah. But the two challenges with those sort
[7:53] But the two challenges with those sort of forms of uh technology is one is it
[7:57] of forms of uh technology is one is it is not uh interactive.
[7:59] is not uh interactive. I mean what can you do with a YouTube
[8:00] I mean what can you do with a YouTube video? You can only see that.
[8:02] video? You can only see that. Yeah. You can just watch it. Yeah.
[8:03] Yeah. You can just watch it. Yeah. Yeah. And second it's not customized. So
[8:05] Yeah. And second it's not customized. So I may be a teacher. I have a certain
[8:07] I may be a teacher. I have a certain style of doing stuff and I want it to be
[8:10] style of doing stuff and I want it to be uh maybe I want to just build a quick
[8:11] uh maybe I want to just build a quick video game explaining the uh let's say
[8:14] video game explaining the uh let's say the uh atom and the molecule and I don't
[8:17] the uh atom and the molecule and I don't want to go for some general video
[8:19] want to go for some general video somebody probably has done in the UK or
[8:21] somebody probably has done in the UK or the US.
[8:22] the US. Yeah.
[8:24] Yeah. So that's another aspect why AI is being
[8:26] So that's another aspect why AI is being rapidly being adopted. So that's a whole
[8:30] rapidly being adopted. So that's a whole gamut of adoption happening. So if you
[8:32] gamut of adoption happening. So if you look at uh companies like Google or open
[8:35] look at uh companies like Google or open AI
[8:36] AI that's why the very very first
[8:38] that's why the very very first initiatives they have launched for the
[8:39] initiatives they have launched for the education domain
[8:42] education domain and the very first of people
[8:45] and the very first of people who have been beta testing the products
[8:47] who have been beta testing the products or adopting the products you would see
[8:49] or adopting the products you would see are typically professors
[8:51] are typically professors correct correct very true
[8:53] correct correct very true so that's a model I'm sure you would
[8:55] so that's a model I'm sure you would recall has been successfully done by
[8:57] recall has been successfully done by companies like uh Microsoft starting in
[8:59] companies like uh Microsoft starting in the '90s
[9:01] the '90s go behind there because that's that's
[9:03] go behind there because that's that's where your workforce is originating
[9:05] where your workforce is originating from.
[9:06] from. So you capture their mind share at that
[9:07] So you capture their mind share at that point of time and then later on they
[9:09] point of time and then later on they come in and adopt your technologies.
[9:11] come in and adopt your technologies. Yeah.
[9:11] Yeah. So these guys are all following the same
[9:13] So these guys are all following the same playbook.
[9:15] playbook. So they're using the old classic
[9:17] So they're using the old classic principles but adopting it to the
[9:19] principles but adopting it to the technologies they bring to the table.
[9:21] technologies they bring to the table. Correct. So
[9:23] Correct. So an interesting perspective actually.
[9:24] an interesting perspective actually. It's a very valid one.
[9:25] It's a very valid one. Yes. So when we go again we have been
[9:29] Yes. So when we go again we have been taking a stance that you know great AI
[9:32] taking a stance that you know great AI is great and all of that stuff is great
[9:34] is great and all of that stuff is great lot of infrastructure we are enjoying
[9:36] lot of infrastructure we are enjoying all of the technology but what about the
[9:37] all of the technology but what about the underprivileged
[9:39] underprivileged students
[9:40] students now when we talk about underprivileged
[9:42] now when we talk about underprivileged it's both financially
[9:44] it's both financially uh physically underprivileged and
[9:47] uh physically underprivileged and probably don't even have access and
[9:49] probably don't even have access and which I've seen with my own eyes in many
[9:50] which I've seen with my own eyes in many parts of the world because I myself I'm
[9:53] parts of the world because I myself I'm a master teacher I go and take classes
[9:55] a master teacher I go and take classes in these schools right from some of the
[9:58] in these schools right from some of the most prominent international ones in
[10:00] most prominent international ones in Singapore to some of them which are
[10:02] Singapore to some of them which are quite remote in Indonesia and India.
[10:04] quite remote in Indonesia and India. We also do with schools surprisingly
[10:07] We also do with schools surprisingly even in the US with not lot of access.
[10:10] even in the US with not lot of access. Yeah. Oh okay.
[10:12] Yeah. Oh okay. So you'd be very surprised that access
[10:14] So you'd be very surprised that access is very unequal worldwide not
[10:16] is very unequal worldwide not necessarily only in um I would say
[10:19] necessarily only in um I would say developing countries if I can use the
[10:20] developing countries if I can use the term anymore.
[10:22] term anymore. Yeah. uh and it's a uh what you could
[10:25] Yeah. uh and it's a uh what you could call that um many people are simply not
[10:28] call that um many people are simply not even aware that something like is coming
[10:30] even aware that something like is coming up.
[10:31] up. Correct.
[10:31] Correct. Um in my various travels I've done to
[10:34] Um in my various travels I've done to many colleges and all of them the there
[10:37] many colleges and all of them the there is strong resistance by the computer
[10:39] is strong resistance by the computer science departments to adopt AI because
[10:42] science departments to adopt AI because they they view it as a existential
[10:44] they they view it as a existential threat.
[10:46] threat. They think they know AI which is not the
[10:48] They think they know AI which is not the case.
[10:49] case. Yeah. um the other departments like
[10:52] Yeah. um the other departments like chemistry or language are very keen to
[10:55] chemistry or language are very keen to adopt it. So look at it very recently in
[10:59] adopt it. So look at it very recently in the Singapore ministry had uh the tech
[11:02] the Singapore ministry had uh the tech excel fest where I actually took a
[11:05] excel fest where I actually took a workshop for about 120 teachers for
[11:09] workshop for about 120 teachers for especially for language teaching using
[11:12] especially for language teaching using artificial intelligence.
[11:14] artificial intelligence. Okay. Uh that was the piece that you
[11:15] Okay. Uh that was the piece that you published on LinkedIn.
[11:16] published on LinkedIn. Yeah. Correct.
[11:17] Yeah. Correct. Yeah. Yeah. So they are very hungry to
[11:21] Yeah. Yeah. So they are very hungry to adopt this
[11:23] adopt this but you won't see that equally done
[11:26] but you won't see that equally done maybe even within the same school or
[11:27] maybe even within the same school or even within the same uh college or
[11:29] even within the same uh college or university.
[11:31] university. So we have been trying to break this
[11:33] So we have been trying to break this mold also by partnering with many
[11:35] mold also by partnering with many foundations, many uh CSRs that corporate
[11:38] foundations, many uh CSRs that corporate social responsible uh organizations
[11:43] social responsible uh organizations um I mean nonprofits in the broad sense
[11:45] um I mean nonprofits in the broad sense of the term which probably also includes
[11:47] of the term which probably also includes governments.
[11:48] governments. Yeah. And um we have uh done this again
[11:52] Yeah. And um we have uh done this again in quite some remote parts of the world
[11:57] in quite some remote parts of the world and uh they have been sponsoring lot of
[11:59] and uh they have been sponsoring lot of these and we have been giving it at
[12:01] these and we have been giving it at quite uh I would say dirt cheap rates
[12:04] quite uh I would say dirt cheap rates because we want the volumes to be there
[12:06] because we want the volumes to be there um otherwise it just turns into another
[12:08] um otherwise it just turns into another profitm initiative.
[12:10] profitm initiative. Correct. Correct.
[12:10] Correct. Correct. Um and we had to design a curriculum. We
[12:13] Um and we had to design a curriculum. We had to design u what we can call the
[12:16] had to design u what we can call the teacher training material. We had to
[12:18] teacher training material. We had to design an online course and uh slowly
[12:21] design an online course and uh slowly over that particular um sort of
[12:25] over that particular um sort of initiative we also figured out that we
[12:27] initiative we also figured out that we have to create age appropriate
[12:30] have to create age appropriate curricular content.
[12:32] curricular content. It has to be in line with international
[12:34] It has to be in line with international standards.
[12:35] standards. Okay.
[12:35] Okay. A doesn't have one common international
[12:37] A doesn't have one common international standard. I doubt if there are any
[12:39] standard. I doubt if there are any standards probably worldwide. There are
[12:41] standards probably worldwide. There are a lot of I would say policies and
[12:43] a lot of I would say policies and guidelines given by
[12:44] guidelines given by Yeah. Yeah.
[12:45] Yeah. Yeah. We have to do everything from scratch.
[12:47] We have to do everything from scratch. Yeah.
[12:48] Yeah. And uh then comes the challenge of
[12:50] And uh then comes the challenge of language.
[12:51] language. You typically do it in English but
[12:53] You typically do it in English but not everybody speaks English or things
[12:55] not everybody speaks English or things in English.
[12:56] in English. Correct.
[12:56] Correct. We had to do it in other languages which
[12:58] We had to do it in other languages which means we had to bring in uh people who
[13:00] means we had to bring in uh people who are like bilingual or triilingual uh
[13:03] are like bilingual or triilingual uh English plus another language. Then
[13:06] English plus another language. Then again we had to shoot all the videos. Um
[13:09] again we had to shoot all the videos. Um and then we started encountering more
[13:11] and then we started encountering more specific problems because people have uh
[13:14] specific problems because people have uh issues on buying data plans. It's not
[13:17] issues on buying data plans. It's not easy to run an online
[13:20] easy to run an online so you need sponsors for all of that.
[13:22] so you need sponsors for all of that. So we had to work with these uh
[13:25] So we had to work with these uh nonprofits and uh then the nonprofits
[13:27] nonprofits and uh then the nonprofits figured out a lot of issues. Then they
[13:29] figured out a lot of issues. Then they actually bought mobiles, tablets,
[13:31] actually bought mobiles, tablets, distributed it to schools. Um and it's
[13:34] distributed it to schools. Um and it's not so easy to do under government uh
[13:37] not so easy to do under government uh policy.
[13:38] policy. Oh yeah, absolutely.
[13:39] Oh yeah, absolutely. So they had to put lot of effort to get
[13:42] So they had to put lot of effort to get all the permissions locally. I can't
[13:44] all the permissions locally. I can't just for example walk into a government
[13:45] just for example walk into a government school.
[13:46] school. No, no, no chance.
[13:47] No, no, no chance. It's no chance. Yeah. I've dealt a
[13:50] It's no chance. Yeah. I've dealt a little bit with even poly techchnics and
[13:52] little bit with even poly techchnics and it and I know what you mean.
[13:54] it and I know what you mean. Yeah.
[13:54] Yeah. So, completely understand.
[13:56] So, completely understand. Right. So that is how we've been doing
[13:58] Right. So that is how we've been doing for the past 8 years because our
[14:00] for the past 8 years because our intention is that first let us reduce
[14:02] intention is that first let us reduce the access inequality
[14:06] the access inequality and uh once you are able to get it
[14:09] and uh once you are able to get it through to those who really can adopt it
[14:12] through to those who really can adopt it and require it and uh then we slowly
[14:14] and require it and uh then we slowly start solving one after the other
[14:17] start solving one after the other challenges right I can't do everything
[14:18] challenges right I can't do everything on day one
[14:19] on day one yeah yeah
[14:20] yeah yeah uh then we slowly also worked with the
[14:22] uh then we slowly also worked with the government so for example we do did it
[14:25] government so for example we do did it with some of the state governments in
[14:27] with some of the state governments in India. We connected our portal to their
[14:29] India. We connected our portal to their portal for the online courses. Uh in
[14:32] portal for the online courses. Uh in fact, we also did it with NSDC, the
[14:34] fact, we also did it with NSDC, the National Skill Development Corporation
[14:35] National Skill Development Corporation in India.
[14:36] in India. Yeah.
[14:37] Yeah. And any anybody who's a citizen can just
[14:39] And any anybody who's a citizen can just log in and access our courses free of
[14:41] log in and access our courses free of cost.
[14:43] Oh. And then u people wanted us to do
[14:48] And then u people wanted us to do physical courses in which means you have
[14:49] physical courses in which means you have to go to the schools and colleges to do
[14:51] to go to the schools and colleges to do which we started recruiting people
[14:53] which we started recruiting people training them giving them meaningful
[14:55] training them giving them meaningful employment and sending them out to these
[14:57] employment and sending them out to these various schools and colleges in a
[14:59] various schools and colleges in a physical mode also.
[15:00] physical mode also. Okay. So now if you look at it education
[15:02] Okay. So now if you look at it education has become even more challenging because
[15:05] has become even more challenging because postcoid people want uh depending on
[15:09] postcoid people want uh depending on their uh what you can call criteria they
[15:11] their uh what you can call criteria they either want fully online
[15:14] either want fully online or they want fully physical or they want
[15:16] or they want fully physical or they want a hybrid.
[15:18] a hybrid. So becomes very challenging as an
[15:20] So becomes very challenging as an operating model
[15:22] operating model because uh you simply cannot just uh
[15:25] because uh you simply cannot just uh have resources to cater to all types of
[15:27] have resources to cater to all types of operating models at the same time.
[15:29] operating models at the same time. Correct. Correct. Yeah. So um and at at
[15:32] Correct. Correct. Yeah. So um and at at the same time I noticed a pattern in the
[15:34] the same time I noticed a pattern in the past two years that these AI and AI
[15:37] past two years that these AI and AI agents which we prominently call in 2025
[15:40] agents which we prominently call in 2025 are going to rapidly become the norm as
[15:42] are going to rapidly become the norm as we go forward.
[15:44] we go forward. It may not be in a good shape at this
[15:46] It may not be in a good shape at this point of time
[15:47] point of time but I'm pretty sure that before end of
[15:49] but I'm pretty sure that before end of this year the things will change
[15:51] this year the things will change dramatically.
[15:52] dramatically. Yeah. In fact, yesterday I think OpenAI
[15:54] Yeah. In fact, yesterday I think OpenAI new model launched and I believe it it
[15:57] new model launched and I believe it it won the gold medal in the international
[15:59] won the gold medal in the international max Olympia which is never done by any
[16:01] max Olympia which is never done by any AI model.
[16:02] AI model. Wow.
[16:03] Wow. So okay
[16:04] So okay the benchmarks are being broken on on a
[16:07] the benchmarks are being broken on on a literally weekly basis.
[16:09] literally weekly basis. Right.
[16:10] Right. So we said u look the future is not
[16:13] So we said u look the future is not probably going to be education is not
[16:15] probably going to be education is not going to be in the same model as we have
[16:17] going to be in the same model as we have done till now. probably it is going to
[16:19] done till now. probably it is going to be that you are going to be like how we
[16:22] be that you are going to be like how we are working with a computer now or a
[16:24] are working with a computer now or a mobile it's going to be with an AI agent
[16:28] mobile it's going to be with an AI agent it's not going to be probably over the
[16:30] it's not going to be probably over the next few years that I have to really go
[16:31] next few years that I have to really go to a training center I need a teacher I
[16:35] to a training center I need a teacher I need to do uh you know sort of resources
[16:38] need to do uh you know sort of resources and stuff like that
[16:39] and stuff like that I will learn more by doing then first
[16:42] I will learn more by doing then first learning and then doing
[16:45] learning and then doing and uh
[16:46] and uh okay
[16:46] okay we then slowly We figured out that uh we
[16:50] we then slowly We figured out that uh we need to have AI agents which we build
[16:53] need to have AI agents which we build and give it to both teachers and
[16:54] and give it to both teachers and students and give them the full power of
[16:58] students and give them the full power of how to use AI which means everything
[17:00] how to use AI which means everything from they can create their own agents. A
[17:02] from they can create their own agents. A student for example can take the lesson
[17:05] student for example can take the lesson plan from their teachers and then they
[17:06] plan from their teachers and then they can create their own study plan and the
[17:10] can create their own study plan and the study plan is customized to what the
[17:11] study plan is customized to what the teacher has given to them as a lesson
[17:13] teacher has given to them as a lesson plan and there is complete sync in what
[17:16] plan and there is complete sync in what both of them are doing and they only
[17:17] both of them are doing and they only contact the teacher or the teacher
[17:19] contact the teacher or the teacher contacts the student when they want a
[17:20] contacts the student when they want a one is to one personalized sort of doubt
[17:23] one is to one personalized sort of doubt clearing sessions or the teacher wants
[17:25] clearing sessions or the teacher wants to conduct a assessment or the
[17:27] to conduct a assessment or the governmentmandated exams. So it's
[17:30] governmentmandated exams. So it's rapidly going towards that space.
[17:32] rapidly going towards that space. So that means that do you think that
[17:34] So that means that do you think that means that there is going to be less and
[17:35] means that there is going to be less and less social interaction between student
[17:37] less social interaction between student and teacher as in physical?
[17:41] and teacher as in physical? I think that's what is going to be the
[17:43] I think that's what is going to be the uh prominent model and that is what I
[17:45] uh prominent model and that is what I would say the next generations are
[17:47] would say the next generations are wanting also.
[17:48] wanting also. So in a very I would say uh it's fast
[17:51] So in a very I would say uh it's fast moving towards a sweet spot where all of
[17:53] moving towards a sweet spot where all of these factors are coming together.
[17:57] these factors are coming together. So
[17:58] So interesting.
[17:59] interesting. I mean people may argue it is 5 years
[18:00] I mean people may argue it is 5 years down the line, 50 years down the line
[18:02] down the line, 50 years down the line but I can see it happening already. Uh
[18:05] but I can see it happening already. Uh you already are seeing people only going
[18:07] you already are seeing people only going for online courses. Online degrees are
[18:10] for online courses. Online degrees are now daen about 3 years back I never
[18:12] now daen about 3 years back I never heard about online degrees.
[18:14] heard about online degrees. Yeah.
[18:15] Yeah. Uh but now I'm talking about proper uh I
[18:19] Uh but now I'm talking about proper uh I would say registered and you know
[18:21] would say registered and you know accredited university giving online
[18:24] accredited university giving online degrees.
[18:24] degrees. Yes. Online degrees. You see even the IT
[18:27] Yes. Online degrees. You see even the IT are now giving their bachelors online.
[18:29] are now giving their bachelors online. Oh is it?
[18:30] Oh is it? Yeah I see many of them uh I've met many
[18:34] Yeah I see many of them uh I've met many folks who are doing this sitting in
[18:35] folks who are doing this sitting in Delhi and then taking a course with
[18:37] Delhi and then taking a course with let's say I met Madras.
[18:39] let's say I met Madras. So you simply cannot escape the tsunami
[18:43] So you simply cannot escape the tsunami of change which is happening in this
[18:45] of change which is happening in this space. Earlier we used to have remember
[18:48] space. Earlier we used to have remember uh OG what is it open un open OGU or
[18:52] uh OG what is it open un open OGU or what is it in India open university
[18:54] what is it in India open university there something igno
[18:56] there something igno ignoign
[18:56] ignoign igno right
[18:57] igno right that we used to get I think by postal
[19:00] that we used to get I think by postal the document
[19:01] the document correct
[19:01] correct people used to take it
[19:02] people used to take it so that is now you're saying that model
[19:04] so that is now you're saying that model is now moving on to the online space
[19:06] is now moving on to the online space pretty much
[19:07] pretty much yes
[19:08] yes okay interesting
[19:15] very very interesting Okay. Okay. So in in that given all of this
[19:18] Okay. So in in that given all of this context
[19:21] context which aspect do you think
[19:28] would keep schools or administrators up at night? One if you had to just start
[19:30] at night? One if you had to just start with one two three I mean I can't say
[19:32] with one two three I mean I can't say just one because there's no one. And
[19:34] just one because there's no one. And then secondly, therefore, which aspects
[19:36] then secondly, therefore, which aspects would also the audience or the students
[19:39] would also the audience or the students really want to see the fastest shift in?
[19:43] really want to see the fastest shift in? See, right now I think the
[19:44] See, right now I think the administrators and the professors or
[19:46] administrators and the professors or teachers are really having sleepless
[19:49] teachers are really having sleepless nights with u the content creation and
[19:54] nights with u the content creation and assessments by students. It is being
[19:56] assessments by students. It is being completely done by CHBT as we speak.
[19:59] completely done by CHBT as we speak. You take a school student or you take a
[20:01] You take a school student or you take a college student, even a PhD level
[20:02] college student, even a PhD level student, right? I'm sure you are aware
[20:04] student, right? I'm sure you are aware of the controversies in N US uh
[20:07] of the controversies in N US uh because somebody submitted even some
[20:09] because somebody submitted even some thesis papers using chatb some stuff
[20:12] thesis papers using chatb some stuff like that right
[20:13] like that right now what happens if even at PhD level
[20:16] now what happens if even at PhD level people are sort of refusing to do it the
[20:19] people are sort of refusing to do it the old manual way uh and trying to do it
[20:22] old manual way uh and trying to do it within a few minutes of using chat GBD.
[20:26] within a few minutes of using chat GBD. Now that is uh really becoming a big
[20:29] Now that is uh really becoming a big friction point between the I would call
[20:33] friction point between the I would call the uh system on one side and the
[20:35] the uh system on one side and the students on the other side.
[20:36] students on the other side. Yeah.
[20:37] Yeah. Uh I don't see any easy way out. I'm
[20:40] Uh I don't see any easy way out. I'm sure some of them are experimenting with
[20:41] sure some of them are experimenting with pen and paper.
[20:43] pen and paper. Mhm.
[20:45] Mhm. But the
[20:47] But the student side of story is that uh if the
[20:50] student side of story is that uh if the professors are using chipd why can't we
[20:52] professors are using chipd why can't we which is a fair question to ask right
[20:54] which is a fair question to ask right fair question
[20:55] fair question if you're using AI why should I be
[20:57] if you're using AI why should I be denied that uh whole technology being
[21:00] denied that uh whole technology being used um I mean we can always debate
[21:03] used um I mean we can always debate whether it's ethically wrong people are
[21:05] whether it's ethically wrong people are comparing it to having used calculators
[21:08] comparing it to having used calculators I still remember for the entrance exams
[21:10] I still remember for the entrance exams we used to memorize the lock tables the
[21:12] we used to memorize the lock tables the pi tables Absolutely
[21:14] pi tables Absolutely right. Multiplication tables you
[21:16] right. Multiplication tables you probably go up to 30 40 or so
[21:18] probably go up to 30 40 or so easy. Yeah. Yeah.
[21:19] easy. Yeah. Yeah. And uh we used to buy those small books
[21:21] And uh we used to buy those small books from the secondhand bookshops and you
[21:23] from the secondhand bookshops and you know that used to be a different thing
[21:25] know that used to be a different thing right today I can't expect any of them
[21:27] right today I can't expect any of them to literally memorize or do the stuff
[21:29] to literally memorize or do the stuff that we used to do.
[21:31] that we used to do. I mean they can't even memorize a single
[21:33] I mean they can't even memorize a single phone number probably.
[21:35] phone number probably. Correct. So
[21:37] Correct. So this is the challenge in front of the
[21:40] this is the challenge in front of the administrators and u the adoption rate
[21:43] administrators and u the adoption rate is if you ask me at least the quite the
[21:47] is if you ask me at least the quite the creamy layers of society worldwide is
[21:49] creamy layers of society worldwide is 100%.
[21:51] 100%. Which again comes back to the same
[21:52] Which again comes back to the same access problem.
[21:53] access problem. It's an access the equity equitable
[21:55] It's an access the equity equitable access for all.
[21:56] access for all. Yeah. If I can write a better essay and
[21:58] Yeah. If I can write a better essay and I can get admission to university and
[21:59] I can get admission to university and another student who's probably more
[22:01] another student who's probably more gifted and brilliant but they do not
[22:03] gifted and brilliant but they do not have access they will be denied a seat.
[22:07] have access they will be denied a seat. Uh maybe I will learn better with this
[22:09] Uh maybe I will learn better with this model. The other person still has to go
[22:10] model. The other person still has to go with older teacher and and I have seen
[22:13] with older teacher and and I have seen people arguing that you know you cannot
[22:14] people arguing that you know you cannot like replace teachers or whatever. I'm
[22:16] like replace teachers or whatever. I'm telling them do you know 95% of them
[22:19] telling them do you know 95% of them don't even have teachers. Forget whether
[22:21] don't even have teachers. Forget whether they have good teachers or bad teachers.
[22:23] they have good teachers or bad teachers. I know schools where the government has
[22:26] I know schools where the government has decided to close down the schools
[22:27] decided to close down the schools because there are not enough teachers.
[22:30] because there are not enough teachers. I've heard this as well.
[22:31] I've heard this as well. And you have teachers who are going
[22:33] And you have teachers who are going through a lot of physical hardship
[22:35] through a lot of physical hardship crossing mountains and rivers to go and
[22:38] crossing mountains and rivers to go and probably teach a class of 10 people or
[22:40] probably teach a class of 10 people or 10 students or so.
[22:43] 10 students or so. These are all use cases where I feel AI
[22:45] These are all use cases where I feel AI is a very good fit. M
[22:48] is a very good fit. M you you can't like have a big butcher's
[22:51] you you can't like have a big butcher's knife and cut entire area and say like
[22:53] knife and cut entire area and say like no this is all bad we need to have uh
[22:56] no this is all bad we need to have uh you know
[22:57] you know uh teachers and uh you can't replace see
[23:00] uh teachers and uh you can't replace see even within the same school you may not
[23:02] even within the same school you may not have all of them operating at the same
[23:04] have all of them operating at the same level. Yes, of course.
[23:06] level. Yes, of course. And you also cannot have um teachers
[23:09] And you also cannot have um teachers being at the same level, let's say after
[23:11] being at the same level, let's say after 10 years of experience
[23:13] 10 years of experience or probably on the from January to
[23:16] or probably on the from January to February, they may have different uh
[23:18] February, they may have different uh sort of uh energy level
[23:20] sort of uh energy level time frame and energy. Yeah.
[23:22] time frame and energy. Yeah. And people go through life stages at at
[23:24] And people go through life stages at at the end of it everyone is a human being.
[23:26] the end of it everyone is a human being. Yes.
[23:26] Yes. And you have to be very know conscious
[23:29] And you have to be very know conscious of the fact also that teachers are the
[23:30] of the fact also that teachers are the lowest paid in society.
[23:32] lowest paid in society. Yes. Yes. Yes,
[23:33] Yes. Yes. Yes, they're not your IT worker.
[23:36] they're not your IT worker. Absolutely.
[23:37] Absolutely. What you can call a media person
[23:40] What you can call a media person that you can sort of claim and uh there
[23:43] that you can sort of claim and uh there is so much of social responsibility on
[23:45] is so much of social responsibility on them. Sort of so much of emotional
[23:46] them. Sort of so much of emotional responsibility on them.
[23:48] responsibility on them. Correct. Correct.
[23:49] Correct. Correct. So why do you want to really burden all
[23:51] So why do you want to really burden all of this when you really have methods to
[23:53] of this when you really have methods to improve that? Right.
[23:55] improve that? Right. Yeah.
[23:56] Yeah. Um and uh we always say good teachers
[23:59] Um and uh we always say good teachers but how many good teachers are
[24:00] but how many good teachers are available?
[24:02] available? True. Right. I'm I'm sure if you go back
[24:04] True. Right. I'm I'm sure if you go back to your school days or college days, I
[24:06] to your school days or college days, I don't think that you'll say that all of
[24:08] don't think that you'll say that all of them were equally good.
[24:09] them were equally good. No, I think probably across what 16 17
[24:12] No, I think probably across what 16 17 years in school and college or 18 years,
[24:13] years in school and college or 18 years, maybe 10 in total.
[24:15] maybe 10 in total. Correct. And maybe students in your
[24:18] Correct. And maybe students in your class uh have a different opinion.
[24:21] class uh have a different opinion. Yes. Each one will have a different
[24:22] Yes. Each one will have a different opinion. Correct.
[24:23] opinion. Correct. Correct.
[24:23] Correct. Absolutely. So it's probably in in the
[24:27] Absolutely. So it's probably in in the hands of people
[24:29] hands of people uh to the seniors to really look at
[24:33] uh to the seniors to really look at where AI can really make an impact
[24:36] where AI can really make an impact and bring those for all this very
[24:38] and bring those for all this very repetitive very sort of boring task like
[24:41] repetitive very sort of boring task like for example answering doubts very simple
[24:43] for example answering doubts very simple things like should I submit an
[24:45] things like should I submit an assignment tomorrow or uh if I am a
[24:48] assignment tomorrow or uh if I am a visual learner maybe you learn it better
[24:51] visual learner maybe you learn it better with uh text and textbook or whatever.
[24:54] with uh text and textbook or whatever. Yeah, but somebody else with images.
[24:55] Yeah, but somebody else with images. I'm more of a visual learner. So why are
[24:58] I'm more of a visual learner. So why are you denying me the opportunity of
[24:59] you denying me the opportunity of learning it? Because at the end of the
[25:00] learning it? Because at the end of the day, I'm paying my fees.
[25:01] day, I'm paying my fees. Yes,
[25:02] Yes, I'm not coming there to waste my time,
[25:03] I'm not coming there to waste my time, right? And if I look at the lens of an
[25:08] right? And if I look at the lens of an administrator,
[25:10] administrator, am I if I'm going to put a parabola
[25:12] am I if I'm going to put a parabola curve and I'm going to say that the
[25:13] curve and I'm going to say that the first five percentile determines my
[25:17] first five percentile determines my school's success,
[25:19] school's success, what about the remaining 95%.
[25:21] what about the remaining 95%. Yep. The big chunk.
[25:22] Yep. The big chunk. Yeah. You can't say they're backbenches
[25:24] Yeah. You can't say they're backbenches and they never come up in life sort of
[25:25] and they never come up in life sort of story right um I mean there's lot of
[25:29] story right um I mean there's lot of such discussions which has to come up
[25:31] such discussions which has to come up and our our objective has been that when
[25:35] and our our objective has been that when you talk about underprivileged most of
[25:37] you talk about underprivileged most of them are underprivileged because of all
[25:39] them are underprivileged because of all these issues
[25:40] these issues correct correct
[25:41] correct correct not just because of money or
[25:43] not just because of money or not just money yeah
[25:44] not just money yeah yeah
[25:46] yeah and I gone to hundreds of colleges again
[25:50] and I gone to hundreds of colleges again um if you look at the higher education
[25:51] um if you look at the higher education side.
[25:53] side. What is worrying for me is not the lack
[25:55] What is worrying for me is not the lack of Wi-Fi or laptops. In fact, that is
[25:58] of Wi-Fi or laptops. In fact, that is easy in today's world to get for
[25:59] easy in today's world to get for students.
[26:00] students. Yeah.
[26:01] Yeah. But the critical college infrastructure
[26:03] But the critical college infrastructure is missing.
[26:05] is missing. The buildings are dilapidated. The labs
[26:07] The buildings are dilapidated. The labs are non-existent. Uh they just don't
[26:11] are non-existent. Uh they just don't have enough professors, people who are
[26:13] have enough professors, people who are really skilled in their domain. So you
[26:16] really skilled in their domain. So you have more systemic problems. Yeah, it's
[26:18] have more systemic problems. Yeah, it's not a problem if you ask me for
[26:20] not a problem if you ask me for absolutely no absolutely I'm just trying
[26:22] absolutely no absolutely I'm just trying to say where are the I I actually meant
[26:24] to say where are the I I actually meant it as where are the biggest challenges
[26:26] it as where are the biggest challenges for administrators in general AI might
[26:30] for administrators in general AI might potentially solve those some of those is
[26:32] potentially solve those some of those is what I'm trying to say and then for the
[26:34] what I'm trying to say and then for the students as well what are the biggest
[26:36] students as well what are the biggest things they want to see changed again
[26:38] things they want to see changed again educationwide because AI then becomes a
[26:40] educationwide because AI then becomes a tool of sorts right it is not the
[26:44] tool of sorts right it is not the solution it is a tool to bring you to a
[26:46] solution it is a tool to bring you to a solution
[26:47] solution that that's right. So it is it is fast
[26:49] that that's right. So it is it is fast moving to a place where probably it'll
[26:52] moving to a place where probably it'll replace a lot of teachers.
[26:54] replace a lot of teachers. Now whether it's ethically morally
[26:56] Now whether it's ethically morally correct is all up for debate.
[26:57] correct is all up for debate. Yeah.
[27:00] Um again uh when there is an advent of a
[27:03] again uh when there is an advent of a new technology it is very tough for
[27:05] new technology it is very tough for anybody to predict which direction it
[27:07] anybody to predict which direction it might take.
[27:08] might take. Correct.
[27:08] Correct. And change doesn't happen the same
[27:10] And change doesn't happen the same throughout society.
[27:12] throughout society. Yep. It probably goes in like very small
[27:17] Yep. It probably goes in like very small paces of change.
[27:18] paces of change. Yeah.
[27:19] Yeah. Now the only thing that the education
[27:21] Now the only thing that the education sector system administrators have to
[27:23] sector system administrators have to realize is this change is permanent.
[27:25] realize is this change is permanent. Yes.
[27:25] Yes. We're not going to go back to a preAI
[27:27] We're not going to go back to a preAI era.
[27:28] era. Yeah.
[27:29] Yeah. Now start planning for that and then
[27:32] Now start planning for that and then start you start putting in things which
[27:34] start you start putting in things which will start changing the system and
[27:36] will start changing the system and things for the better.
[27:38] things for the better. Um, you can't like put your hand head in
[27:41] Um, you can't like put your hand head in the sand and behave like a ostrich,
[27:43] the sand and behave like a ostrich, right?
[27:43] right? Ostrich. Yeah. Yeah.
[27:44] Ostrich. Yeah. Yeah. I'm not going to change all of this
[27:46] I'm not going to change all of this stuff and nothing is going to change.
[27:47] stuff and nothing is going to change. You know, good teachers are there. I
[27:49] You know, good teachers are there. I think that era is over,
[27:52] think that era is over, right? It's all about skills, right? I
[27:54] right? It's all about skills, right? I mean, Singapore, for example, the
[27:56] mean, Singapore, for example, the government is very clear, right? You got
[27:57] government is very clear, right? You got to upskill. You got to skill yourself.
[27:59] to upskill. You got to skill yourself. You're not going to sit down and just
[28:01] You're not going to sit down and just take paper certificates, paper degrees.
[28:04] take paper certificates, paper degrees. And uh that explains lot of issues in
[28:07] And uh that explains lot of issues in the job market. So I'm saying that
[28:09] the job market. So I'm saying that everything is intertwined with each
[28:10] everything is intertwined with each other. It's not like one issue you can
[28:12] other. It's not like one issue you can just separate and
[28:14] just separate and absolutely you you are like sort of
[28:16] absolutely you you are like sort of already late into this AI game.
[28:19] already late into this AI game. Uh ideally people should have started 10
[28:20] Uh ideally people should have started 10 years back
[28:21] years back and I don't know why they didn't. We've
[28:23] and I don't know why they didn't. We've been like shouting from the rooftops
[28:25] been like shouting from the rooftops saying that everybody must be skilled in
[28:26] saying that everybody must be skilled in AI. uh we did a lot of programs and
[28:28] AI. uh we did a lot of programs and stuff like that and even now I'm saying
[28:31] stuff like that and even now I'm saying that the resistance which people are
[28:33] that the resistance which people are showing in the education sector is
[28:34] showing in the education sector is mindboggling
[28:36] mindboggling yes because it is change and change like
[28:38] yes because it is change and change like you said everybody's afraid of change
[28:41] you said everybody's afraid of change right like you said first is I lose my
[28:43] right like you said first is I lose my job the computer science department oops
[28:46] job the computer science department oops I'm gone I'm I'm history why should I
[28:49] I'm gone I'm I'm history why should I change and and we see it across not just
[28:51] change and and we see it across not just education right in every part of facet
[28:53] education right in every part of facet of the world change is the this
[28:56] of the world change is the this stumbling block so to say because oops
[28:58] stumbling block so to say because oops it's fear
[29:01] it's fear that's right
[29:03] that's right so you're absolutely right yeah okay
[29:05] so you're absolutely right yeah okay cool so if you had to look at just
[29:08] cool so if you had to look at just putting a vision visionary lens ahead
[29:11] putting a vision visionary lens ahead right and say five years on three I
[29:14] right and say five years on three I would say let's say three years because
[29:15] would say let's say three years because AI is changing so rapidly I think
[29:16] AI is changing so rapidly I think predicting five years is too long maybe
[29:19] predicting five years is too long maybe two years down the road or whatever you
[29:21] two years down the road or whatever you think you tell me one year is good two
[29:23] think you tell me one year is good two years good three years What is the
[29:24] years good three years What is the biggest change in education do you
[29:26] biggest change in education do you foresee AI bringing? And I'm not talking
[29:29] foresee AI bringing? And I'm not talking Singapore because Singapore is a bit
[29:30] Singapore because Singapore is a bit unique. But if you look at countries
[29:32] unique. But if you look at countries like Malaysia, India, Indonesia, what is
[29:34] like Malaysia, India, Indonesia, what is the one big
[29:36] the one big flick that AI will really cause that
[29:39] flick that AI will really cause that will change that could change?
[29:42] will change that could change? Sure.
[29:43] Sure. Let me just show a real uh
[29:47] Let me just show a real uh thing so it's easy for
[29:51] thing so it's easy for just to explain my use case. Okay, cool.
[29:54] just to explain my use case. Okay, cool. Okay, so are you able to see my screen?
[29:57] Okay, so are you able to see my screen? Yeah.
[29:57] Yeah. Okay. So, what I'm just showing you on
[30:00] Okay. So, what I'm just showing you on screen is my platform, the AI agent
[30:02] screen is my platform, the AI agent platform, smart, right?
[30:05] platform, smart, right? Now, could you guess how much time I
[30:07] Now, could you guess how much time I would have taken to create this
[30:09] would have taken to create this platform?
[30:11] platform? I mean, using AI, I don't know, probably
[30:14] I mean, using AI, I don't know, probably half a day less, 10 minutes.
[30:17] half a day less, 10 minutes. Okay. So this is a very complicated
[30:20] Okay. So this is a very complicated platform because we have more than 300
[30:22] platform because we have more than 300 plus AI agents, right? So for example,
[30:24] plus AI agents, right? So for example, if I just take education tools,
[30:27] if I just take education tools, we have developed about 96 tools which
[30:31] we have developed about 96 tools which helps a teacher or student do everything
[30:33] helps a teacher or student do everything from behavior support ideas to uh
[30:37] from behavior support ideas to uh classroom humor assistant to whatever.
[30:39] classroom humor assistant to whatever. Right.
[30:40] Right. Right. Right.
[30:41] Right. Right. Now how many uh like say team members
[30:44] Now how many uh like say team members you think could have developed all of
[30:46] you think could have developed all of this? So we we have all these education
[30:48] this? So we we have all these education tools. We have another 100 uh marketing
[30:51] tools. We have another 100 uh marketing tools, sales tools. Then we have tools
[30:53] tools, sales tools. Then we have tools which help us with uh meme generation,
[30:56] which help us with uh meme generation, PPT generation, you know, all of that.
[30:57] PPT generation, you know, all of that. Just just a guess,
[31:00] Just just a guess, three people maybe.
[31:03] three people maybe. I just did it all by myself.
[31:06] I just did it all by myself. And
[31:07] And surprisingly, the whole thing was also
[31:11] surprisingly, the whole thing was also done by AI.
[31:13] done by AI. Mhm. in the sense it's not that I used
[31:15] Mhm. in the sense it's not that I used AI and then AI went and coded. I use AI
[31:19] AI and then AI went and coded. I use AI so that it can independently create a
[31:21] so that it can independently create a lot of these products by itself.
[31:23] lot of these products by itself. Okay. Okay.
[31:24] Okay. Okay. Right. So imagine training an AI to
[31:27] Right. So imagine training an AI to develop its own AI.
[31:30] develop its own AI. So that's a sort of I just want to bring
[31:33] So that's a sort of I just want to bring across the productivity point
[31:36] across the productivity point right
[31:36] right if you had asked me in my tenure earlier
[31:38] if you had asked me in my tenure earlier in companies like IBM or so I probably
[31:42] in companies like IBM or so I probably would have said okay this is going to
[31:43] would have said okay this is going to take let's say 6 months and then
[31:44] take let's say 6 months and then probably we need a 15 member team we do
[31:47] probably we need a 15 member team we do everything from they say waterfall model
[31:49] everything from they say waterfall model or you know different sorts of models
[31:52] or you know different sorts of models project management the investments in
[31:54] project management the investments in real estate and you know you can name
[31:56] real estate and you know you can name all of this probably it would have cost
[31:59] all of this probably it would have cost me up to a million dollars to develop
[32:01] me up to a million dollars to develop something like this.
[32:04] something like this. Now I can just do it for probably less
[32:07] Now I can just do it for probably less than a few hundred over a period of
[32:10] than a few hundred over a period of let's say 1 month or so just by myself
[32:15] let's say 1 month or so just by myself and this is the most latest tech stack
[32:18] and this is the most latest tech stack also
[32:19] also right
[32:20] right so you can imagine the productivity
[32:22] so you can imagine the productivity which could come now in every segment of
[32:24] which could come now in every segment of society. Yeah, absolutely.
[32:27] society. Yeah, absolutely. If you are a lawyer, you could probably
[32:29] If you are a lawyer, you could probably attend to more cases,
[32:32] attend to more cases, you could probably instead of having
[32:34] you could probably instead of having parallegals, right, as they say, uh
[32:38] parallegals, right, as they say, uh instead of you having 15 juniors team,
[32:43] instead of you having 15 juniors team, you probably could do it with three
[32:44] you probably could do it with three juniors.
[32:45] juniors. Mhm.
[32:46] Mhm. And you can probably take on more cases.
[32:48] And you can probably take on more cases. Mhm.
[32:50] Mhm. Right. If you're a doctor, probably you
[32:52] Right. If you're a doctor, probably you can segregate your patients and probably
[32:54] can segregate your patients and probably you could attend to more patients,
[32:55] you could attend to more patients, increasing your revenue.
[32:57] increasing your revenue. Yeah. Yeah.
[32:58] Yeah. Yeah. Right.
[32:58] Right. Yeah. Now, if I'm a teacher, I could now
[33:01] Yeah. Now, if I'm a teacher, I could now teach more students
[33:03] teach more students and have more one-on-one with students
[33:06] and have more one-on-one with students who really require it
[33:08] who really require it and allow the others to have the power
[33:10] and allow the others to have the power of AI to really learn these concepts
[33:13] of AI to really learn these concepts and uh as I said automate all of the
[33:15] and uh as I said automate all of the other stuff that is required right from
[33:17] other stuff that is required right from assessment to your questioning to any of
[33:21] assessment to your questioning to any of these things which are out over there
[33:24] these things which are out over there right and I could have continuous
[33:26] right and I could have continuous assessment I don't have to have let's
[33:28] assessment I don't have to have let's say two assessments ments half yearly or
[33:30] say two assessments ments half yearly or yearly.
[33:31] yearly. I don't have to have maybe monthly test
[33:33] I don't have to have maybe monthly test and
[33:34] and I could literally have a report card
[33:36] I could literally have a report card which is very genuine about a student's
[33:38] which is very genuine about a student's progress.
[33:39] progress. Yeah.
[33:40] Yeah. And I could probably get more metrics in
[33:42] And I could probably get more metrics in terms of where a student is falling off.
[33:44] terms of where a student is falling off. Let's say what is an acceptable level of
[33:46] Let's say what is an acceptable level of learning
[33:47] learning and then I can plan my interventions.
[33:51] and then I can plan my interventions. Today it's not scientific, right?
[33:53] Today it's not scientific, right? Yeah. It is just the teacher looks into
[33:55] Yeah. It is just the teacher looks into the class physically, visually and then
[33:57] the class physically, visually and then they come to some conclusions.
[33:59] they come to some conclusions. Yeah.
[34:00] Yeah. Yeah. Some
[34:01] Yeah. Some some international schools might say we
[34:02] some international schools might say we are dashboards, analytics and all of
[34:04] are dashboards, analytics and all of that. But this that is all post the
[34:06] that. But this that is all post the event, right? Not prior to the event.
[34:09] event, right? Not prior to the event. Correct.
[34:10] Correct. And they give out whatever cards, report
[34:12] And they give out whatever cards, report cards which is basically having bunch of
[34:14] cards which is basically having bunch of numbers which you can't interpret in any
[34:17] numbers which you can't interpret in any meaningful way.
[34:18] meaningful way. Meaningful way. Yeah.
[34:19] Meaningful way. Yeah. Yeah. There are more milestones, right?
[34:20] Yeah. There are more milestones, right? That is not progress.
[34:21] That is not progress. Yeah. Yeah. Yeah. Correct. Correct.
[34:22] Yeah. Yeah. Yeah. Correct. Correct. You're right. I think people forget they
[34:24] You're right. I think people forget they mix up the two.
[34:25] mix up the two. Yeah. So I have to assume the progress
[34:27] Yeah. So I have to assume the progress that's a problem.
[34:30] that's a problem. Right. So that is the ways that you
[34:33] Right. So that is the ways that you could be more innovative and I think
[34:36] could be more innovative and I think this is the direction the vision in
[34:38] this is the direction the vision in which the whole thing has to go in terms
[34:40] which the whole thing has to go in terms of uh making it much more productive
[34:44] of uh making it much more productive for everyone concerned and making it as
[34:46] for everyone concerned and making it as a win-win situation.
[34:49] a win-win situation. not the sort of friction I'm seeing
[34:50] not the sort of friction I'm seeing today on a daily basis in the education
[34:52] today on a daily basis in the education sector.
[34:53] sector. Yeah. Yeah. Point.
[34:56] Yeah. Yeah. Point. Yeah.
[34:56] Yeah. And I I I have students who you won't
[34:59] And I I I have students who you won't believe it right from the junior schools
[35:02] believe it right from the junior schools who have been doing much more complex
[35:05] who have been doing much more complex engagements and not necessarily IT
[35:07] engagements and not necessarily IT projects. You know, everybody thinks
[35:08] projects. You know, everybody thinks that you're teaching it computer science
[35:09] that you're teaching it computer science projects.
[35:12] projects. It could be everything from biology to
[35:14] It could be everything from biology to chemistry,
[35:16] chemistry, right?
[35:17] right? they could adopt it as part of their
[35:19] they could adopt it as part of their overall learning perspective.
[35:22] overall learning perspective. Like for example, if I looked at uh the
[35:25] Like for example, if I looked at uh the subject of history, I mean my daughter
[35:28] subject of history, I mean my daughter came to me and uh she actually asked me
[35:30] came to me and uh she actually asked me a question about who was the real sort
[35:33] a question about who was the real sort of mentor or guru of Napoleon.
[35:36] of mentor or guru of Napoleon. Uh of course I didn't know that. So I
[35:38] Uh of course I didn't know that. So I said like um um I I was saying I think
[35:42] said like um um I I was saying I think it was his one of his uh that political
[35:45] it was his one of his uh that political gurus or somebody and some name was
[35:47] gurus or somebody and some name was there sort of stuff.
[35:49] there sort of stuff. Then she argued no because my book says
[35:52] Then she argued no because my book says that it's his some aunt or somebody was
[35:54] that it's his some aunt or somebody was the real mentor.
[35:56] the real mentor. I said well I'm busy I can't really sit
[35:58] I said well I'm busy I can't really sit down and figure out all of this stuff
[36:00] down and figure out all of this stuff but why don't I do one thing. So I said
[36:01] but why don't I do one thing. So I said uh go gone into voice mode with charg
[36:04] uh go gone into voice mode with charg and said like charge assume yourself you
[36:06] and said like charge assume yourself you are Napoleon
[36:08] are Napoleon have a chat with my daughter and answer
[36:10] have a chat with my daughter and answer all these questions
[36:13] all these questions then she put the chat GPD on the spot by
[36:18] then she put the chat GPD on the spot by crossquesting a lot of stuff
[36:20] crossquesting a lot of stuff and then she could go to many sources of
[36:22] and then she could go to many sources of information including let's say books
[36:23] information including let's say books from library or her own books or
[36:26] from library or her own books or Wikipedia and things like that to come
[36:28] Wikipedia and things like that to come to a conclusion as to what really
[36:30] to a conclusion as to what really happened.
[36:36] Now that process was enlightening for me as thinking that students could now
[36:39] as thinking that students could now really use AI in the sense of uh you
[36:42] really use AI in the sense of uh you know getting as we say from the horse's
[36:45] know getting as we say from the horse's mouth.
[36:46] mouth. Mhm.
[36:46] Mhm. What if we get Einstein to come and
[36:48] What if we get Einstein to come and teach you calculus?
[36:50] teach you calculus? That's the sort of innovation we should
[36:52] That's the sort of innovation we should bring in rather than worry about saying
[36:54] bring in rather than worry about saying that whether AI is hallucinating or
[36:55] that whether AI is hallucinating or whatever because you have to be in a
[36:58] whatever because you have to be in a position where you can really analyze
[37:01] position where you can really analyze um you can cross check lot of stuff
[37:04] um you can cross check lot of stuff nowadays. I I think that is a very
[37:07] nowadays. I I think that is a very important point you mentioned about your
[37:09] important point you mentioned about your daughter's u discussion with you the
[37:11] daughter's u discussion with you the cross questioning you know the the
[37:14] cross questioning you know the the concept of crossqu questioning
[37:17] concept of crossqu questioning comes in when you are able to think and
[37:20] comes in when you are able to think and challenge that you know I can't take
[37:22] challenge that you know I can't take everything at face value which is kind
[37:25] everything at face value which is kind of where the hallucination story also is
[37:26] of where the hallucination story also is right now right
[37:28] right now right so one piece is then
[37:30] so one piece is then how is it going to happen that
[37:33] how is it going to happen that hallucinations will I won't say minimize
[37:35] hallucinations will I won't say minimize rather then go to zero because I don't I
[37:38] rather then go to zero because I don't I can't foresee it. I'm sure they'll go
[37:39] can't foresee it. I'm sure they'll go down to close to zero. That's one. And
[37:41] down to close to zero. That's one. And can there be a will that there be a
[37:42] can there be a will that there be a default state of affairs that in any AI
[37:45] default state of affairs that in any AI application hallucination will be
[37:46] application hallucination will be minimized? That's one. Let's assume that
[37:49] minimized? That's one. Let's assume that happens. But
[37:53] happens. But if AI becomes a very very integral
[37:58] if AI becomes a very very integral tool for education across
[38:02] tool for education across demand and supply very simplistically
[38:05] demand and supply very simplistically teachers, educators and students,
[38:08] teachers, educators and students, will they still be able how will they
[38:11] will they still be able how will they continue being able to cross question or
[38:14] continue being able to cross question or think that they have to question it? And
[38:16] think that they have to question it? And secondly,
[38:23] do you see a reduction in tactical and t sorry tactile experiences because of
[38:25] sorry tactile experiences because of reliance on AI? That means a lot of our
[38:27] reliance on AI? That means a lot of our motor skills etc will go down.
[38:30] motor skills etc will go down. That is another part of the pie, right?
[38:32] That is another part of the pie, right? That you know I'm constantly looking at
[38:33] That you know I'm constantly looking at a screen and asking for guidance and
[38:35] a screen and asking for guidance and looking for answers. But am I therefore
[38:37] looking for answers. But am I therefore not able to if you play a game of
[38:39] not able to if you play a game of cricket am I playing the ball correctly?
[38:42] cricket am I playing the ball correctly? the best possible way to hit a cover
[38:44] the best possible way to hit a cover drive or bowl the best leg break like a
[38:48] drive or bowl the best leg break like a Shane Ward something like so so the
[38:49] Shane Ward something like so so the tactile experience part are we going to
[38:51] tactile experience part are we going to lose or how do you see that being
[38:53] lose or how do you see that being impacted by AI over time
[38:57] impacted by AI over time it's it's purely up to I would say the
[39:01] it's it's purely up to I would say the people concerned to figure out what is
[39:02] people concerned to figure out what is the fit use case of AI as to where it
[39:05] the fit use case of AI as to where it can give you the maximum impact
[39:09] can give you the maximum impact um I mean to be If you look at for
[39:13] um I mean to be If you look at for example aviation industry, I was quite
[39:14] example aviation industry, I was quite surprised that when I found out that
[39:17] surprised that when I found out that many of the pilots they actually start
[39:19] many of the pilots they actually start off with the Microsoft flight simulator.
[39:22] off with the Microsoft flight simulator. Uh then I'm like did they really fly the
[39:25] Uh then I'm like did they really fly the real planes or probably it was just a
[39:28] real planes or probably it was just a warm-up before they learn to re the real
[39:31] warm-up before they learn to re the real planes.
[39:32] planes. Yes. So uh you do have this sort of real
[39:35] Yes. So uh you do have this sort of real world experiences where people probably
[39:38] world experiences where people probably are using technology as more of a
[39:40] are using technology as more of a simulation for doing a lot of stuff.
[39:42] simulation for doing a lot of stuff. Yeah.
[39:43] Yeah. And uh then figure out as to whether u
[39:46] And uh then figure out as to whether u you go into more uh what you can call
[39:50] you go into more uh what you can call lesser risk aspects of learning or
[39:53] lesser risk aspects of learning or implementing.
[39:54] implementing. So if I'm a let's say I am a city
[39:57] So if I'm a let's say I am a city planner, I'm a civil engineer.
[39:59] planner, I'm a civil engineer. Yeah. and I I have to plan for some
[40:02] Yeah. and I I have to plan for some buildings or some new stuff. Am I going
[40:06] buildings or some new stuff. Am I going to not use AI
[40:09] to not use AI and lose out on that whole simulation
[40:12] and lose out on that whole simulation because AI can probably think in many
[40:14] because AI can probably think in many data points?
[40:15] data points? Yeah.
[40:15] Yeah. Or am I going to still rely on older
[40:17] Or am I going to still rely on older methods where probably the risk is much
[40:20] methods where probably the risk is much higher.
[40:22] higher. I mean I still have to build the
[40:23] I mean I still have to build the buildings. Yeah. It's not going to do
[40:25] buildings. Yeah. It's not going to do that for you. Probably it might with
[40:27] that for you. Probably it might with robots later on. Yeah,
[40:29] robots later on. Yeah, that is looking at the extremes.
[40:31] that is looking at the extremes. Mhm. Mhm.
[40:32] Mhm. Mhm. So we are looking at how do we reduce
[40:35] So we are looking at how do we reduce the risk on the planet?
[40:36] the risk on the planet? Yeah.
[40:36] Yeah. Like if I'm a business guy, how do I
[40:38] Like if I'm a business guy, how do I reduce the risk for my business?
[40:40] reduce the risk for my business? I that's no tactile experience I need to
[40:42] I that's no tactile experience I need to bring in here. I probably have to run a
[40:45] bring in here. I probably have to run a lot of simulations, lot of strategy
[40:46] lot of simulations, lot of strategy frameworks.
[40:47] frameworks. Yeah.
[40:48] Yeah. And I'm good to go.
[40:50] And I'm good to go. Right. I could test a lot of business
[40:52] Right. I could test a lot of business models. H I could ask Charg to be an
[40:56] models. H I could ask Charg to be an expert to figure out the like loopholes
[41:00] expert to figure out the like loopholes some places you need regulatory
[41:03] some places you need regulatory oversight probably things like
[41:05] oversight probably things like healthcare or insurance
[41:07] healthcare or insurance that is default right
[41:09] that is default right correct
[41:10] correct you don't want to trust a drug which is
[41:11] you don't want to trust a drug which is created by charg
[41:13] created by charg oh yeah for sure yeah
[41:15] oh yeah for sure yeah right
[41:15] right yeah yeah
[41:16] yeah yeah just give me a second Yeah.
[41:31] Yeah. Sorry about that. No problem. Okay. So it's it's
[41:34] No problem. Okay. So it's it's definitely going to be a booming
[41:35] definitely going to be a booming industry for people to figure out as to
[41:37] industry for people to figure out as to what's going to happen in which industry
[41:39] what's going to happen in which industry to what level I have to implement and
[41:41] to what level I have to implement and see we keep referring even in this
[41:42] see we keep referring even in this podcast around things only around chd or
[41:45] podcast around things only around chd or products like Maya but uh the the the I
[41:49] products like Maya but uh the the the I would say the negative aspect of all the
[41:51] would say the negative aspect of all the hype is people only think AI is charged
[41:53] hype is people only think AI is charged is AI which is wrong
[41:55] is AI which is wrong this is other AI technology machine
[41:58] this is other AI technology machine learning computer vision uh things which
[42:00] learning computer vision uh things which are happening out So it is literally a
[42:03] are happening out So it is literally a mistake not to think about the impact of
[42:06] mistake not to think about the impact of all of those um on lot of stuff which is
[42:09] all of those um on lot of stuff which is happening in the world and there
[42:10] happening in the world and there silently it's happening all around us.
[42:12] silently it's happening all around us. Yeah absolutely true. Yeah, one one last
[42:14] Yeah absolutely true. Yeah, one one last piece which I asked you earlier cross
[42:16] piece which I asked you earlier cross questioning. How do you think um it's
[42:20] questioning. How do you think um it's that part is going to evolve if people
[42:22] that part is going to evolve if people rely more and more on AI?
[42:26] rely more and more on AI? How do you check validation? Is this
[42:28] How do you check validation? Is this correct verification
[42:30] correct verification that this I should believe this? Because
[42:31] that this I should believe this? Because that's I think a lot of students today
[42:32] that's I think a lot of students today also find that as a challenge that
[42:34] also find that as a challenge that there's so much information out there. I
[42:35] there's so much information out there. I don't know what to believe and what not
[42:36] don't know what to believe and what not to believe.
[42:39] to believe. So it's for you to um two aspects right.
[42:42] So it's for you to um two aspects right. Again, you have to be clear where AI can
[42:43] Again, you have to be clear where AI can really help you.
[42:45] really help you. No, but as students, you might struggle
[42:46] No, but as students, you might struggle probably is what I'm trying to think.
[42:48] probably is what I'm trying to think. Teachers at least, let's say, slightly
[42:50] Teachers at least, let's say, slightly more thought through process maybe.
[42:53] more thought through process maybe. But the younger generation,
[42:55] But the younger generation, that's right. You can't blindly believe
[42:56] that's right. You can't blindly believe AI. That's for sure.
[42:58] AI. That's for sure. But at least
[42:59] But at least how would they go about crossquestioning
[43:00] how would they go about crossquestioning is the
[43:01] is the that part is then is it a home thing
[43:03] that part is then is it a home thing where you and at at home, how are you
[43:06] where you and at at home, how are you taught to think and learn or also at
[43:09] taught to think and learn or also at school along with peers? Is it all going
[43:11] school along with peers? Is it all going to be a mix of I'm so I'm trying to
[43:13] to be a mix of I'm so I'm trying to bring back the social side into the tech
[43:16] bring back the social side into the tech side and saying a better combination of
[43:20] side and saying a better combination of the two.
[43:22] the two. Yes. So if you are going to as I said
[43:24] Yes. So if you are going to as I said blindly believe AI is going to lead to a
[43:27] blindly believe AI is going to lead to a lot of problems.
[43:28] lot of problems. Um but you also have to have a lot of
[43:30] Um but you also have to have a lot of common sense in terms of how do I really
[43:31] common sense in terms of how do I really cross check a lot of stuff that AI is
[43:33] cross check a lot of stuff that AI is doing.
[43:34] doing. So for example if I'm doing a math
[43:35] So for example if I'm doing a math problem it's very easy for me to cross
[43:36] problem it's very easy for me to cross verify. I just solve it and figure out
[43:38] verify. I just solve it and figure out whether it's correct or not.
[43:40] whether it's correct or not. Yeah. Right.
[43:41] Yeah. Right. But when it comes to things like
[43:42] But when it comes to things like debates,
[43:44] debates, whether
[43:45] whether uh something happened or did not happen
[43:48] uh something happened or did not happen or what was the real reason it did or
[43:51] or what was the real reason it did or whatever. The problem is even in today's
[43:54] whatever. The problem is even in today's society, a lot of these things are up
[43:56] society, a lot of these things are up for debate.
[43:57] for debate. That's true. That's true.
[43:58] That's true. That's true. You may have learned history in a
[44:00] You may have learned history in a certain way. I may have learned it
[44:01] certain way. I may have learned it differently. We may not both agree uh
[44:04] differently. We may not both agree uh you know as to what really happened. I
[44:06] you know as to what really happened. I may I may like my version of the story.
[44:08] may I may like my version of the story. Yeah. Yeah. Yeah. what I got taught
[44:10] Yeah. Yeah. Yeah. what I got taught the personal biases of sorts unconscious
[44:13] the personal biases of sorts unconscious correct
[44:14] correct preferences not biases
[44:15] preferences not biases so I always say that the issues with all
[44:18] so I always say that the issues with all of these is not about AI AI is just
[44:20] of these is not about AI AI is just trained on data from society
[44:22] trained on data from society correct
[44:23] correct if you are having all fake data
[44:25] if you are having all fake data artificial data data which is in one
[44:27] artificial data data which is in one direction well AI is also going to top
[44:30] direction well AI is also going to top down the same stuff
[44:32] down the same stuff correct it almost is like your prompt
[44:34] correct it almost is like your prompt engineering right the the way you ask
[44:35] engineering right the the way you ask your question you'll get an answer on
[44:37] your question you'll get an answer on the on the chat GPT equivalent models
[44:39] the on the chat GPT equivalent models Correct. Correct.
[44:40] Correct. Correct. Almost biased towards your question.
[44:51] Yeah. So that's that's the thing that you know we it's it's a tall order,
[44:53] you know we it's it's a tall order, right? It's more often uh we call it as
[44:56] right? It's more often uh we call it as the paradise which probably will never
[44:58] the paradise which probably will never reach. Um are we going to eliminate all
[45:01] reach. Um are we going to eliminate all that so-called bias and things and stuff
[45:03] that so-called bias and things and stuff like that? I doubt it's going to happen.
[45:05] like that? I doubt it's going to happen. Yeah.
[45:06] Yeah. But if you don't do that then don't
[45:07] But if you don't do that then don't blame the AI.
[45:09] blame the AI. I think that is that is the important
[45:12] I think that is that is the important point that don't blame the tool, don't
[45:16] point that don't blame the tool, don't blame the messenger pretty much.
[45:17] blame the messenger pretty much. Correct. So it's it's it's a it's a it's
[45:21] Correct. So it's it's it's a it's a it's a societal issue. It's got nothing to do
[45:23] a societal issue. It's got nothing to do with the technology per se and um it's
[45:26] with the technology per se and um it's not it's not going to get better,
[45:28] not it's not going to get better, right?
[45:29] right? It's it's a um AI is like uh say it's
[45:34] It's it's a um AI is like uh say it's it's an amplification.
[45:37] it's an amplification. If you already have a problem, it's only
[45:39] If you already have a problem, it's only going to amplify the problem. It's not
[45:40] going to amplify the problem. It's not going to solve the problem.
[45:42] going to solve the problem. Yeah.
[45:44] Yeah. Either the problem or the the solution.
[45:45] Either the problem or the the solution. Either way, it'll amplify. One of the
[45:47] Either way, it'll amplify. One of the two.
[45:47] two. Yeah. In computer science, we have the
[45:48] Yeah. In computer science, we have the term called gigo, right? Garbage in,
[45:50] term called gigo, right? Garbage in, garbage out.
[45:51] garbage out. Yep. Yep. Yep.
[45:52] Yep. Yep. Yep. So, if you have rotten society, it's
[45:55] So, if you have rotten society, it's going to be equally rotten.
[45:57] going to be equally rotten. Very true. This is very, very true. It's
[45:59] Very true. This is very, very true. It's a societal issue. You're right.
[46:01] a societal issue. You're right. Absolutely. Cool. I'm Hey, thanks a lot
[46:04] Absolutely. Cool. I'm Hey, thanks a lot for your time, Chandra. This is really
[46:06] for your time, Chandra. This is really useful. Um, I will, like I said, you are
[46:09] useful. Um, I will, like I said, you are the very first person I'm talking to.
[46:11] the very first person I'm talking to. I'm going to talk to a few more and as I
[46:13] I'm going to talk to a few more and as I put stuff together, I'm happy to share
[46:14] put stuff together, I'm happy to share it with you.
[46:15] it with you. Sure.
[46:15] Sure. And maybe one day I'll also introduce
[46:17] And maybe one day I'll also introduce you to this person here in Singapore who
[46:20] you to this person here in Singapore who runs the nonprofit and let's see. If
[46:23] runs the nonprofit and let's see. If nothing else, it will be a good
[46:24] nothing else, it will be a good conversation with them.
[46:25] conversation with them. Absolutely. Always nice to network,
[46:27] Absolutely. Always nice to network, right?
[46:27] right? And let's catch up some point in time
[46:28] And let's catch up some point in time anyway. Oh,
[46:29] anyway. Oh, sure. Sure. We will do. Yeah. All right.
[46:31] sure. Sure. We will do. Yeah. All right. We'll do. Thanks so much, Andra. Catch
[46:32] We'll do. Thanks so much, Andra. Catch you later. Thank you. Bye. Bye.
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About This Episode
AI is already changing classrooms, but will it uplift everyone or widen the gap?
In this episode, Chandra Kumar cuts through the noise to explore AI's real impact on education. He shares hard-won insights on how AI can personalize learning, reduce burnout for teachers, and help underprivileged students gain access. He also addresses academic misuse, resistance from educators, and the societal fear of job loss.
Coffee with Chandru is for busy professionals, SME owners, founders, and anyone curious about what it really takes to build, lead, and grow in a world shaped by AI.
Key Takeaways
- AI can personalize learning experiences, but inclusive implementation matters.
- Teacher burnout can be reduced through AI assistance when educators get proper training.
- Underprivileged students can benefit from AI accessibility tools if the digital divide is addressed.
- Academic misuse requires balanced policies and AI literacy.
- Resistance often stems from job security fears that need practical reskilling answers.
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