December 12, 2023 • 30 mins
AI is a rapidly evolving space, creating a need for data scientists and developers. This also creates the importance for more specified education programs to prepare the upcoming workforce for these emerging roles. Habib Matar, a former Intel supervisor and current professor at Chandler-Gilbert Community College, discusses Intel's AI for Workforce program and why AI education should be implemented in non-traditional education programs. We’ll unpack how AI revolutionized learning and created more gateways for STEM careers.
Learn more about how Intel is leading the charge in the AI Revolution at Intel.com/AIperformance
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Episode Transcript
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Speaker 1 (00:03):
In a world where technology continues to advance at breakneck speeds,
education is evolving to meet the needs of the future.
Years ago, if you were told that the average person
would have a STEM job, that is, a career in science, technology, engineering,
or math, a natural assumption would be that the world
had progressed to most people having advanced degrees. On the contrary,
(00:25):
it is the technology that progresses and with it our
ability to keep up with the times. When I was
growing up, our classroom only had one computer for all
of us to share. Now my children have their own
individual iPads and laptops to research, create and learn. It's
amazing how far we have come with using technology to
(00:46):
educate our young With their early adoption of technology comes
to added responsibility of preparing them for how to use
technology for their future occupations. For many students, those jobs
will begin sooner than graduating from cos Whether it is
learning to manage a small team of AI powered self
service machines at the local grocery store, or learning coding
(01:08):
skills to oversee a large autonomous robotic warehouse. Education is
shaping a brighter future, one student at a time. Hey, there,
I'm grain class and this is technically speaking. An Intel podcast,
the show is dedicated to highlighting the technology is revolutionizing
the way we live, work and move. In every episode,
(01:31):
we'll connect with innovators in areas like artificial intelligence to
better understand the human centered technology they've developed. We tend
to see an education and STEM that is science, technology, engineering,
and maths as something that's highly academic, involving several years
in high education. Most of the guests on the series
have graduated from some of the top universities around the world,
(01:54):
or even developing AI tools before they entered college. While
it is true that AI and technology are being innovated
by some of the greatest minds in the world, those
minds aren't always acquiring their skills the same way because
it's not always about the degrees that you have, but
your passion for knowledge and your ability to learn. One
of the recurring themes for me in recording this series
(02:16):
is how AI tools have made things more accessible for
people around the world. However, it is important for education
around AI and machine learning to be accessible as well.
In this episode, i'll explore how learning AI is becoming
more accessible with the help of Intel's AI for Workforce program.
Before we get into it. Let me introduce our guest
(02:39):
jotting me now is the lead faculty of Intel's AI
for Workforce program at Chandler Gilbert Community College. Habib Mattah
Habib was considered a child prodigy in STEM, beginning his
collegiate career at the Chandler Gilbert Community College before graduating
from Arizona State University at age sixteen. Following up his
bachelor's with the mark in Computer Science, Habib went on
(03:02):
to become a production lead at Intel, where he oversaw
the analysis of statistics and led a team of manufacturing engineers. Ultimately,
it was his love for AI and STEM that inspired
him to transition into education. He wants to be the
catalyst and making AI tools a part of the education
system permanently and ensuring that a new generation of kids
(03:24):
are fully immersed instead education. Welcome have you, It's good
to be here.
Speaker 2 (03:32):
Wow. I couldn't have written that. That's one of the
best introductions I've heard ever, So thank you so much.
Speaker 1 (03:39):
It wasn't from chat GPT either.
Speaker 2 (03:41):
I was about to say that, but well, I get
it up with those jokes already, being an AI professor.
Speaker 1 (03:47):
That's right, that's right. So I mean, I have a
son who's twelve and he's just started high school. You
started college at age twelve, and I can't imagine him
heading off to universe. So your early achievements are really remarkable.
What did that experience teach you about learning stem tools
at an early age and how has it shaped your
(04:09):
approach to teaching.
Speaker 2 (04:11):
So a small correction there, I was one year older.
I was thirteen when I started, okay, and I was
that's just, I know, not a big deal in terms
of age. So I was going into eighth grade, and
at the time, I always knew that I was going
to do some kind of engineering because my dad is
an electrical engineer, and I wanted to see if it
(04:35):
was possible to accelerate that process. I had no idea
what the college space would have been like and how
I would have came out on the other side of it,
but I knew that my dad worked there at Chandler
Gilbert Community College as well as my mom does as well.
She's an English faculty, and so I knew i'd be
in a safe place going to the community college, and
(04:56):
I'd be around family when I'm not in classes. So
I just ventured out into that big world. I didn't
really even realize that everyone around me was, you know,
five or six years older. I was so focused on
reaching that goal of becoming an engineer like my dad.
Speaker 1 (05:13):
And it was actually quite interesting that you said that
your father was an electrical engineer. My dad was an
electronic engineer, and I remember spending quite a bit of
time in his workshops at a young age. Perhaps tell
me a little bit more, I mean of his influence
on yourself going up.
Speaker 2 (05:30):
Well, it's an influence of his and as well as
the culture. My name's Habib, which is Lebanese. It's actually
my grandpa's name. And part of the Lebanese culture is
is that you become either a doctor, a lawyer, or
an engineer, right, and so I had to choose one
of those, and I wasn't too good with blood, and
so engineer definitely was that. On top of that, my
(05:55):
dad would give me little incentives growing up. So I
was super video games and he would say, okay, I'll
give you one dollar for every math sheet that you do.
So I would do these large multiplication tables just so
I can get like one dollar and save up for
that game I wanted.
Speaker 1 (06:15):
Ah, that's cool. I mean, I remember my dad giving
me sort of logic puzzles and numerical puzzles as well.
Going out. You didn't give you any money though, that's
crying shame. So yeah, so I'm quite interested in the
whole accelerated program that you went through. What sort of
challenges are there for students to get access to that
sort of program.
Speaker 2 (06:36):
We had found that if I went through homeschooling and
tested out of homeschooling, then that could get me admitted
into the community college. Once I started that process, all
I did was a placement test, which is very standard
across all community college goers. To do this placement test,
I tested into like the hundreds, so not even the
(06:57):
one hundred classes because again I'm thirteen. But within a
year I was able to begin my program similarly to
someone who had just got out of high school. From there,
my memory of the time was very normal, Like the
students around me were all pretty mature. I was able
to talk to the other nerds and play video games
(07:20):
with them, and so I had found myself in a
pretty fun community that was quite nice. And actually I
have people that I've talked to in my life that
have kids and they've had their own kids go through
that route as well.
Speaker 1 (07:38):
Despite spending most of his childhood becoming a scholar and STEM,
his passions lie in teaching and helping others. This education
is valuable to have even when you're not working in
a STEM field. In such a role as an engineer,
just having that sort of background can help others better
understand the technologies we engage with regularly. If you've ever
(07:59):
had to help a grandparent use a phone or printer,
you know the exact challenges of helping others become tech savvy.
In terms of the role now that you have at
the college, maybe you could give a little bit of
a summary. What are the courses, what are the programs
that you're teaching there?
Speaker 2 (08:17):
Yeah, So when I transitioned from working at Intel into
Chandler Gilbert, Intel approached us saying, we have a high
school program that we're using in I believe Singapore for
teaching AI. Is there any way we could take this
high school program and make it into like a two
year vocational program. And so my background was in computer
(08:41):
science and AI, and I had already been working at
Intel and I had family at Chandler Gilbert. Right, So
it's like this perfect marriage between the three. And so
the program I teach at Chandler Gilbert is in essence
that it's a two year vocational program for someone to
learn about artificial intelligence. Now, we started this in twenty nineteen.
(09:03):
This was before chat GPT and the boom a popularity
of AI. So what my focus has been since twenty
nineteen is how can I give my students marketable skills
while still keeping it accessible Because typically AI is a
graduate field right now you have to have a master's
(09:24):
or a PhD to learn about the topic. How can
I keep this field accessible to learn as well as
marketable with the skills that they do learn throughout the
two year program. And so we have six different classes
that we teach following that goal. Intro to AI is
one of them, intro to Machine Learning, intro to Natural
(09:46):
Language Processing, so this is, you know, how does SII
know what when you say Hey Siri? Or how can
chat GPT seem to understand the text that you write?
Then we have computer vision, where it's how do cars
driving on the road see other cars and pedestrians and
no one to stop. The last two classes are intro
(10:08):
to Business Solutions. We actually have an employee from Intel
teaching that class, giving students important aspects of what work
looks like in AI, like benchmarking and copyright issues that
come with data. And then we have a capstone class
where the students get a whole semester to explore an
(10:30):
AI project.
Speaker 1 (10:31):
Well that's all in two years. Two years, yes, Well
that's impressive. And in terms of getting into that sort
of program, what are the some of the prerequisites that
students have to have before joining in.
Speaker 2 (10:47):
So we're a community college and we want to keep
this as accessible as possible. So our first class, Intro
to AI, also named AIM one hundred. AIM stands for
AIM machine Learning and it was a funny, you know,
acronym to put there. But it's no prerequisites to join
(11:07):
our first course. Now, our next class, AIM one ten,
which is intro to Machine Learning, has a prerequisite of
statistics as well as intro to Python, so you'll need
to know a little bit of Python and statistics.
Speaker 1 (11:24):
Just for everyone's benefit. Python is a popular computing language
which actually has a lot of free resources for anyone
to look up and be able to code their own
AI machine learning programs. So, Habi, do you know if
this program is trying to be replicated in other community colleges.
Speaker 2 (11:41):
That's actually at the heart of AI for Workforce. So
I'm the lead faculty at Chandler Gilbert, but I played
a role in helping advise AI for Workforce and now
they're their own separate entity. So what we had at
our campus last week was a summit hosted are at
(12:02):
Channel Gilbert campus called the AI Teaching and Learning Summit,
So we had one hundred different folk faculty and administrators
from across the country and even Canada come to our
campus and try and learn about building their own AI
programs within their institutions. Well, one of the leaders of
AI for Workforce came and talked about I think they've
(12:26):
reached somewhere between thirty two to forty eight community colleges
in the country. They've almost hit every single state in
terms of a community college within the state. So they
have that many community colleges that have at least taken
the INTEL training that they have available now, which is
available for free, to build programs within their own college.
(12:50):
In terms of who I see that has full fledged programs,
think there's only like four or five colleges that I'm
aware of in the country that have an associates or
a certificate in AI at a community college level.
Speaker 1 (13:09):
We'll be right back after a quick break. Welcome back
to Technically Speaking, an Intel podcast. I'd like to get
your thoughts on any data or trends in the job
(13:32):
market around the significance of learning about AI, and is
that demand still there and do you see that growing
and in which areas and which industries do you see
the best potential for your students going through that program.
Speaker 2 (13:49):
It's a hard marker to pin on right now because
it's such an emerging field. There's different routes you could
see AI, this large field of AI going right now.
So I'll start from the most beginner level. You have
people who are like prompt engineers who use something like
chat GPT, these very industry wide models and are able
(14:12):
to interface with that system such that they get autonomous outputs,
automatic outputs that increase productivity and reduce the amount of
work that someone would need to do. Right That prompt
engineer is a great field for someone who's entry into
the AI space. Right It doesn't need nearly as much
math or programming even and there's actually a lot of
(14:35):
drag and drop interface to perform AI modeling platforms where
you can kind of input data, drag and drop what
you need and then get some meaningful output. I can't
say that I target that too much right now because
there's not a lot of stability there just yet. Chat
(14:56):
GPT is still relatively new, no code tools, it's very specified,
So I focus more on level two. I would say,
you can hear my video games speak come out. Level
two is they have some coding. They're like a software developer,
(15:17):
but more equipped to tackle problems that could evolve automation
of let's say text and images, have some of the
data analytics background as well to analyze and process data,
come up with systems that automatically process that data and
give meaningful output. So they have to have a little
(15:40):
bit of math to understand how that data is being
inputed and what the story is behind the data is
what I typically say. And then they have to have
some programming, because if you stick with only no code tools,
you're very limited to what those no code tools can offer.
With programming, it opens the doors. So that's level two
(16:00):
and that's where I try and keep my students. These
concepts in AI can get very sticky mathematically very quickly,
and I can't expect a two year student to be
at that level of foundation. So then level three is
that they have a very solid mathematical foundation to where
(16:24):
pretty much any AI algorithm I throw at them they
can at least orient themselves to quite quickly. Someone with
a master's background or a bachelor's background can do this, right.
You come into a new class and it's like, oh,
that's just the formula I've seen before kind of but
just in a different way.
Speaker 1 (16:41):
Ye gotcha.
Speaker 2 (16:43):
And then the programming expertise of let's say, Okay, we're
not going to do this in Python, now we're going
to do this in R. They know so many programming
languages at that point that they can kind of easily
switch between the two for a quick prototype. So I
see that as level three three, So right now, I
target that level too.
Speaker 1 (17:02):
Okay, just previously, you talked a little bit about some
of the student projects that can be quite exciting for
both the teachers and the students, a like, is there
just one that is top of your brain right now
that is quite exciting that you're working on with your students.
Speaker 2 (17:18):
So the one I do is I have them create
an automatic bubble sheet scanner. So they take a photo
with their phone and they should be able to grade
a bubble sheet just based off of a photo. So
I teach them all about things like how to detect
the bubbles on a sheet, how to know which position
(17:40):
is where on the sheet. It doesn't automatically tell you
where it is, so you have to do that and
then sort them in a list that the top left
is zero and then go on from there all the
way down. Gotcha, And then to know whether or not
it's filled. So that's about an eight week process, not
that one project, but what leads up to that project.
(18:03):
So then let's jump into I guess the capstone projects
where my students are out in the wild West, right.
I have students who do stock market prediction brain tumor
detection based off of MRI or CT scans. One of
my students is a musician, so he likes to handwrite
his musical notes and he wants to be able to
take a picture and have it be electronically printed. I've
(18:28):
had a student who won actually an Intel competition taking
brain wave EEG data and trying to detect if there
is an epileptic seizure occurring within that data. I think
what I find is is that I'm always amazed that
I give them these little seedlings of knowledge and then
(18:50):
that capstone project comes around and they just grow without
me even being there.
Speaker 1 (18:55):
Yeah, Habib, you mentioned a lot of people need graduate
level degrees to work in AI. Right now, what path
have you seen your students go through after these courses?
Have they said it's opened any doors for them?
Speaker 2 (19:09):
So one of the big challenges we're trying to tackle
on the community college AI education side is pathways for
students upon graduation. Right it's pretty bleak in terms of
having a two year degree and meeting minimum jow brecks.
Our college actually is beginning to offer or developing a
bachelor's degree in AI to alleviate that issue. But I'm
(19:32):
seeing that they're still finding positions because of how marketable
AI skills are. Right now, it may not be, you know,
an engineer, but it could be, Hey, here's an entry
level role at a company, but it's easier for them
to get through the door because they have these marketable skills.
Speaker 1 (19:50):
And in your view, how do you see the future
of AI in the workplace And what's your number one
reason that you tell the younger generation and students why
AI tools are so important to learn.
Speaker 2 (20:07):
You know, when AI was first emerging, let's say chat
GPT right into popularity, everyone was like, AI is going
to replace jobs, and actually there's been a new keynote
I guess that people have been saying, which is people
who have AI skills will be better equipped than those without.
(20:27):
I completely agree on that note, because we work so
much with technology. If we're better to interface with that technology,
we're going to be that much more productive. We can
tackle much more complex problems in a shorter amount of time,
and so I see the future workforce being able to
be once again more productive utilizing these tools. I mean
(20:50):
when you're typing an email and gmails like hey, here's
the rest of that sentence. Yeah right, it's just so
convenient and it helps ease the amount of hand to
paper work we have to do. And we can now
be more creative with that time and solve more nuanced,
more complex problems because we have these systems better ready
(21:10):
to assist us. So someone like me and you can
do a lot more with this lifespan that we have.
We can develop, create ID eight more things because we
have more time to do so.
Speaker 1 (21:25):
The way Habib looks at AI as a tool in
assisting the workflow reminds me of the invention of the spreadsheet.
My grandfather worked at the bank for forty years in
the same desk, the same chair, pouring over bank ledges
with paper and pencil, ensuring all figures balanced exactly to
the scent. With the invention of computerized adding machines and
(21:45):
then later spreadsheets on personal computers, there's laborious efforts that
my grandfather previously undertook had now become so quick and accurate.
He retired before the advent of these technologies, but I
often think how helpful those tools would have been for him.
AI in the workplace empowers everyone to focus on what
they do best. Learning these AI tools, like learning how
(22:08):
to use a spreadsheet, gives employees an added edge in
how they work as individuals and within their teams. I'd
just like to get your thoughts about the AI tools
for the non engineers and non tech people.
Speaker 2 (22:24):
Well, I think I've been giving this rose colored glasses
look onto AI right where AI is always beneficial and
always used in the right way. But we know that's
not the case. I think that it's important to know
what algorithms and what AI can do because our number
one interface with AI every day is things like the
(22:47):
Internet and social media. And so I have students who
may be dealing with some kind of addictive behavior and
they don't realize that AI recommendation systems that are used
in sol social media are constantly feeding them content that
may make them feel stuck in that frame of mind
and that addictive cycle. And so I think it's important
(23:10):
for the general public to know what AI thinked imagery
looks like, what algorithms are out there, and how they
use your preferences to feed you more content that you like,
just for our own mental wellbeing. So I see my
class AA in one hundred as a place where people
(23:30):
can come and learn about these technologies so that they're
better equipped to personally manage their interface with them right
mentally manage it.
Speaker 1 (23:38):
Yeah, and are there any ethical considerations you try and
emphasize when teaching your course to your students.
Speaker 2 (23:46):
So I try to give my students a broad overview
of AI ethics, because again, you could dig into one
quite a bit and there's still a ton of content
left there. So I started talking about, like what topics
there are in AI ethics. There's privacy and surveillance, there's
manipulation of behavior, there's jobs and autonomy. So those are
(24:11):
all like separate topics that I go over. Then I
can take a step further and I talk about frameworks.
So what frameworks are out there in terms of AI ethics,
Like the European AI Act came out and they have
a framework for how they want to regulate this technology.
Now we're seeing policy on the America side on AI.
(24:33):
My last little tidbit in the AI ethics realm is
trying to dispel some of the fear. I am personally
of the belief that there's not some looming AI monster
coming to eat us, and if there would be, we
would see the development of it, Like we've seen the
development of this technology all along chat GPT wasn't grown
(24:55):
in a lab and everyone was like, oh, I've never
seen this before. We had GPT one, GPT two, GPT three. Yes,
we saw the progress of that technology.
Speaker 1 (25:06):
Yeah, and I generally agree with that that there's going
to be a net positive to the AI growth that
we're seeing. But I think it's incumbent upon people like
you to actually teach and guide students around at least
understanding some of that, as you said, the ethical frameworks
around it, because they're the ones that are going to
(25:26):
be producing these things. Right. So I have three kids,
two of them are now in high school. What advice
would you give to parents and educators who are looking
to introduce AI and STAM related concepts to children at
an early age.
Speaker 2 (25:42):
Man, that's a great question. I've never been asked that.
I've done so many interviews that I've never announced that.
What advice would I give them? You know, I'm a
family oriented person, right, I'm twenty six. I'm hoping to
have a family someday, So I kind of think about
this a lot. One thing I find my classroom is
is if you make it fun, the students get involved
(26:04):
and they get interested. Right. It's like if you have
dessert after your salad. Right, people are just more willing
to eat the salad so that they can have that
dessert and feel okay about it. So, getting your kids
involved in things like Legos Mindstorm, which is a subsect
(26:26):
like a robotic subsect of Legos, even like video games
that are less so dopamine addiction for them and more
so building and creating things using their intelligence in their mind.
I think making the space more fun for them to access,
and then on top of that, making it social, having
(26:47):
them find a friend group where they can relate to
other people about these kinds of things. I think loneliness
epidemic is pretty bad in today's world, and there's ways
you can alleviate that early on in their lives by
getting them involved in a community of other kids who
are open to doing those kinds of things.
Speaker 1 (27:04):
Yeah, what do you envision as the future of AI
and education And what's the number one thing that excites
you most about the role of AI in shaping the
learning experiences?
Speaker 2 (27:16):
I think the way we're interfacing what technology is changing
and being spurred on by AI, that's what we've named this,
and so I'm really excited for the shift that will
come in how we interface with technology. On the education side, right,
we teach people how to use technology, So now we're
going to teach them how to better their use of
(27:38):
technology by including AI education. So I'm really excited that
this new workforce that's coming will be better equipped again
to tackle more complex problems, and who knows, maybe some
of the problems that we've been trying to tackle for
so long will seem simplistic in the next twenty to
thirty years, and I'm really excited for or this emergence
(28:01):
of that, and I hope that we use it in
the right way to better society.
Speaker 1 (28:07):
Awesome. Thanks very much, Havib, Well.
Speaker 2 (28:09):
Thank you. I appreciate your time. It's been fun.
Speaker 1 (28:17):
Thanks to Habib Mata for joining me on this episode
of Technically Speaking, an Intel podcast. Chatting with Habib was
really an eye opener. Being a dad of three, I'm
always on the hunt for ways to help my kids
flourish in their future careers. What grabs me about the
course that Intel and Habib created is that it's not
(28:37):
just your run of the mill four year degree. It's
like they threw open the doors for people from all
walks of life, no matter where they are in their career,
to jump in and really get their hands dirty in
the emerging fields of AI and STEM. The way Habib
gets his students fired up is pretty cool. He dives
into real world applications right from the get go, sparking
(28:57):
that curiosity bug in his students. This style gets them
hooked early on, and then they dig deeper into the
nitty gritty theory behind those AI projects. It's a far
cry for my old engineering days. It's all about slogging
through thick theory books before getting onto the hands on
fun projects. And now, with the solid backing from Intel
and Habib's relentless effort, this program is rolling out to
(29:20):
more campuses across the US, and who knows, soon it
might be a movement that spans the world. That's something
to be excited about, not just for my kids, but
for anyone ready to ride the AI and STEM wave.
Thank you all for listening. Join us again in two
weeks in December twenty sixth for the season finale of
(29:41):
Technically Speaking, an Intel podcast. There's been a real journey
learning about all these new technologies, and our final episode
will explore the challenges it takes to make them all possible.
You definitely do not want to miss its. Technically Speaking
was produced by Ruby Studios from IHET Radio in partnership
with Intel and hosted by me Graham Class. Our executive
(30:05):
producer is Molly Sosha, our EP of Post Production is
James Foster, and our Supervising producer is Nikir Swinton. This
episode was edited by Sierra Spreen and written and produced
by Tyree Rush,
In a world where technology continues to advance at breakneck speeds,
education is evolving to meet the needs of the future.
Years ago, if you were told that the average person
would have a STEM job, that is, a career in science, technology, engineering,
or math, a natural assumption would be that the world
had progressed to most people having advanced degrees. On the contrary,
(00:25):
it is the technology that progresses and with it our
ability to keep up with the times. When I was
growing up, our classroom only had one computer for all
of us to share. Now my children have their own
individual iPads and laptops to research, create and learn. It's
amazing how far we have come with using technology to
(00:46):
educate our young With their early adoption of technology comes
to added responsibility of preparing them for how to use
technology for their future occupations. For many students, those jobs
will begin sooner than graduating from cos Whether it is
learning to manage a small team of AI powered self
service machines at the local grocery store, or learning coding
(01:08):
skills to oversee a large autonomous robotic warehouse. Education is
shaping a brighter future, one student at a time. Hey, there,
I'm grain class and this is technically speaking. An Intel podcast,
the show is dedicated to highlighting the technology is revolutionizing
the way we live, work and move. In every episode,
(01:31):
we'll connect with innovators in areas like artificial intelligence to
better understand the human centered technology they've developed. We tend
to see an education and STEM that is science, technology, engineering,
and maths as something that's highly academic, involving several years
in high education. Most of the guests on the series
have graduated from some of the top universities around the world,
(01:54):
or even developing AI tools before they entered college. While
it is true that AI and technology are being innovated
by some of the greatest minds in the world, those
minds aren't always acquiring their skills the same way because
it's not always about the degrees that you have, but
your passion for knowledge and your ability to learn. One
of the recurring themes for me in recording this series
(02:16):
is how AI tools have made things more accessible for
people around the world. However, it is important for education
around AI and machine learning to be accessible as well.
In this episode, i'll explore how learning AI is becoming
more accessible with the help of Intel's AI for Workforce program.
Before we get into it. Let me introduce our guest
(02:39):
jotting me now is the lead faculty of Intel's AI
for Workforce program at Chandler Gilbert Community College. Habib Mattah
Habib was considered a child prodigy in STEM, beginning his
collegiate career at the Chandler Gilbert Community College before graduating
from Arizona State University at age sixteen. Following up his
bachelor's with the mark in Computer Science, Habib went on
(03:02):
to become a production lead at Intel, where he oversaw
the analysis of statistics and led a team of manufacturing engineers. Ultimately,
it was his love for AI and STEM that inspired
him to transition into education. He wants to be the
catalyst and making AI tools a part of the education
system permanently and ensuring that a new generation of kids
(03:24):
are fully immersed instead education. Welcome have you, It's good
to be here.
Speaker 2 (03:32):
Wow. I couldn't have written that. That's one of the
best introductions I've heard ever, So thank you so much.
Speaker 1 (03:39):
It wasn't from chat GPT either.
Speaker 2 (03:41):
I was about to say that, but well, I get
it up with those jokes already, being an AI professor.
Speaker 1 (03:47):
That's right, that's right. So I mean, I have a
son who's twelve and he's just started high school. You
started college at age twelve, and I can't imagine him
heading off to universe. So your early achievements are really remarkable.
What did that experience teach you about learning stem tools
at an early age and how has it shaped your
(04:09):
approach to teaching.
Speaker 2 (04:11):
So a small correction there, I was one year older.
I was thirteen when I started, okay, and I was
that's just, I know, not a big deal in terms
of age. So I was going into eighth grade, and
at the time, I always knew that I was going
to do some kind of engineering because my dad is
an electrical engineer, and I wanted to see if it
(04:35):
was possible to accelerate that process. I had no idea
what the college space would have been like and how
I would have came out on the other side of it,
but I knew that my dad worked there at Chandler
Gilbert Community College as well as my mom does as well.
She's an English faculty, and so I knew i'd be
in a safe place going to the community college, and
(04:56):
I'd be around family when I'm not in classes. So
I just ventured out into that big world. I didn't
really even realize that everyone around me was, you know,
five or six years older. I was so focused on
reaching that goal of becoming an engineer like my dad.
Speaker 1 (05:13):
And it was actually quite interesting that you said that
your father was an electrical engineer. My dad was an
electronic engineer, and I remember spending quite a bit of
time in his workshops at a young age. Perhaps tell
me a little bit more, I mean of his influence
on yourself going up.
Speaker 2 (05:30):
Well, it's an influence of his and as well as
the culture. My name's Habib, which is Lebanese. It's actually
my grandpa's name. And part of the Lebanese culture is
is that you become either a doctor, a lawyer, or
an engineer, right, and so I had to choose one
of those, and I wasn't too good with blood, and
so engineer definitely was that. On top of that, my
(05:55):
dad would give me little incentives growing up. So I
was super video games and he would say, okay, I'll
give you one dollar for every math sheet that you do.
So I would do these large multiplication tables just so
I can get like one dollar and save up for
that game I wanted.
Speaker 1 (06:15):
Ah, that's cool. I mean, I remember my dad giving
me sort of logic puzzles and numerical puzzles as well.
Going out. You didn't give you any money though, that's
crying shame. So yeah, so I'm quite interested in the
whole accelerated program that you went through. What sort of
challenges are there for students to get access to that
sort of program.
Speaker 2 (06:36):
We had found that if I went through homeschooling and
tested out of homeschooling, then that could get me admitted
into the community college. Once I started that process, all
I did was a placement test, which is very standard
across all community college goers. To do this placement test,
I tested into like the hundreds, so not even the
(06:57):
one hundred classes because again I'm thirteen. But within a
year I was able to begin my program similarly to
someone who had just got out of high school. From there,
my memory of the time was very normal, Like the
students around me were all pretty mature. I was able
to talk to the other nerds and play video games
(07:20):
with them, and so I had found myself in a
pretty fun community that was quite nice. And actually I
have people that I've talked to in my life that
have kids and they've had their own kids go through
that route as well.
Speaker 1 (07:38):
Despite spending most of his childhood becoming a scholar and STEM,
his passions lie in teaching and helping others. This education
is valuable to have even when you're not working in
a STEM field. In such a role as an engineer,
just having that sort of background can help others better
understand the technologies we engage with regularly. If you've ever
(07:59):
had to help a grandparent use a phone or printer,
you know the exact challenges of helping others become tech savvy.
In terms of the role now that you have at
the college, maybe you could give a little bit of
a summary. What are the courses, what are the programs
that you're teaching there?
Speaker 2 (08:17):
Yeah, So when I transitioned from working at Intel into
Chandler Gilbert, Intel approached us saying, we have a high
school program that we're using in I believe Singapore for
teaching AI. Is there any way we could take this
high school program and make it into like a two
year vocational program. And so my background was in computer
(08:41):
science and AI, and I had already been working at
Intel and I had family at Chandler Gilbert. Right, So
it's like this perfect marriage between the three. And so
the program I teach at Chandler Gilbert is in essence
that it's a two year vocational program for someone to
learn about artificial intelligence. Now, we started this in twenty nineteen.
(09:03):
This was before chat GPT and the boom a popularity
of AI. So what my focus has been since twenty
nineteen is how can I give my students marketable skills
while still keeping it accessible Because typically AI is a
graduate field right now you have to have a master's
(09:24):
or a PhD to learn about the topic. How can
I keep this field accessible to learn as well as
marketable with the skills that they do learn throughout the
two year program. And so we have six different classes
that we teach following that goal. Intro to AI is
one of them, intro to Machine Learning, intro to Natural
(09:46):
Language Processing, so this is, you know, how does SII
know what when you say Hey Siri? Or how can
chat GPT seem to understand the text that you write?
Then we have computer vision, where it's how do cars
driving on the road see other cars and pedestrians and
no one to stop. The last two classes are intro
(10:08):
to Business Solutions. We actually have an employee from Intel
teaching that class, giving students important aspects of what work
looks like in AI, like benchmarking and copyright issues that
come with data. And then we have a capstone class
where the students get a whole semester to explore an
(10:30):
AI project.
Speaker 1 (10:31):
Well that's all in two years. Two years, yes, Well
that's impressive. And in terms of getting into that sort
of program, what are the some of the prerequisites that
students have to have before joining in.
Speaker 2 (10:47):
So we're a community college and we want to keep
this as accessible as possible. So our first class, Intro
to AI, also named AIM one hundred. AIM stands for
AIM machine Learning and it was a funny, you know,
acronym to put there. But it's no prerequisites to join
(11:07):
our first course. Now, our next class, AIM one ten,
which is intro to Machine Learning, has a prerequisite of
statistics as well as intro to Python, so you'll need
to know a little bit of Python and statistics.
Speaker 1 (11:24):
Just for everyone's benefit. Python is a popular computing language
which actually has a lot of free resources for anyone
to look up and be able to code their own
AI machine learning programs. So, Habi, do you know if
this program is trying to be replicated in other community colleges.
Speaker 2 (11:41):
That's actually at the heart of AI for Workforce. So
I'm the lead faculty at Chandler Gilbert, but I played
a role in helping advise AI for Workforce and now
they're their own separate entity. So what we had at
our campus last week was a summit hosted are at
(12:02):
Channel Gilbert campus called the AI Teaching and Learning Summit,
So we had one hundred different folk faculty and administrators
from across the country and even Canada come to our
campus and try and learn about building their own AI
programs within their institutions. Well, one of the leaders of
AI for Workforce came and talked about I think they've
(12:26):
reached somewhere between thirty two to forty eight community colleges
in the country. They've almost hit every single state in
terms of a community college within the state. So they
have that many community colleges that have at least taken
the INTEL training that they have available now, which is
available for free, to build programs within their own college.
(12:50):
In terms of who I see that has full fledged programs,
think there's only like four or five colleges that I'm
aware of in the country that have an associates or
a certificate in AI at a community college level.
Speaker 1 (13:09):
We'll be right back after a quick break. Welcome back
to Technically Speaking, an Intel podcast. I'd like to get
your thoughts on any data or trends in the job
(13:32):
market around the significance of learning about AI, and is
that demand still there and do you see that growing
and in which areas and which industries do you see
the best potential for your students going through that program.
Speaker 2 (13:49):
It's a hard marker to pin on right now because
it's such an emerging field. There's different routes you could
see AI, this large field of AI going right now.
So I'll start from the most beginner level. You have
people who are like prompt engineers who use something like
chat GPT, these very industry wide models and are able
(14:12):
to interface with that system such that they get autonomous outputs,
automatic outputs that increase productivity and reduce the amount of
work that someone would need to do. Right That prompt
engineer is a great field for someone who's entry into
the AI space. Right It doesn't need nearly as much
math or programming even and there's actually a lot of
(14:35):
drag and drop interface to perform AI modeling platforms where
you can kind of input data, drag and drop what
you need and then get some meaningful output. I can't
say that I target that too much right now because
there's not a lot of stability there just yet. Chat
(14:56):
GPT is still relatively new, no code tools, it's very specified,
So I focus more on level two. I would say,
you can hear my video games speak come out. Level
two is they have some coding. They're like a software developer,
(15:17):
but more equipped to tackle problems that could evolve automation
of let's say text and images, have some of the
data analytics background as well to analyze and process data,
come up with systems that automatically process that data and
give meaningful output. So they have to have a little
(15:40):
bit of math to understand how that data is being
inputed and what the story is behind the data is
what I typically say. And then they have to have
some programming, because if you stick with only no code tools,
you're very limited to what those no code tools can offer.
With programming, it opens the doors. So that's level two
(16:00):
and that's where I try and keep my students. These
concepts in AI can get very sticky mathematically very quickly,
and I can't expect a two year student to be
at that level of foundation. So then level three is
that they have a very solid mathematical foundation to where
(16:24):
pretty much any AI algorithm I throw at them they
can at least orient themselves to quite quickly. Someone with
a master's background or a bachelor's background can do this, right.
You come into a new class and it's like, oh,
that's just the formula I've seen before kind of but
just in a different way.
Speaker 1 (16:41):
Ye gotcha.
Speaker 2 (16:43):
And then the programming expertise of let's say, Okay, we're
not going to do this in Python, now we're going
to do this in R. They know so many programming
languages at that point that they can kind of easily
switch between the two for a quick prototype. So I
see that as level three three, So right now, I
target that level too.
Speaker 1 (17:02):
Okay, just previously, you talked a little bit about some
of the student projects that can be quite exciting for
both the teachers and the students, a like, is there
just one that is top of your brain right now
that is quite exciting that you're working on with your students.
Speaker 2 (17:18):
So the one I do is I have them create
an automatic bubble sheet scanner. So they take a photo
with their phone and they should be able to grade
a bubble sheet just based off of a photo. So
I teach them all about things like how to detect
the bubbles on a sheet, how to know which position
(17:40):
is where on the sheet. It doesn't automatically tell you
where it is, so you have to do that and
then sort them in a list that the top left
is zero and then go on from there all the
way down. Gotcha, And then to know whether or not
it's filled. So that's about an eight week process, not
that one project, but what leads up to that project.
(18:03):
So then let's jump into I guess the capstone projects
where my students are out in the wild West, right.
I have students who do stock market prediction brain tumor
detection based off of MRI or CT scans. One of
my students is a musician, so he likes to handwrite
his musical notes and he wants to be able to
take a picture and have it be electronically printed. I've
(18:28):
had a student who won actually an Intel competition taking
brain wave EEG data and trying to detect if there
is an epileptic seizure occurring within that data. I think
what I find is is that I'm always amazed that
I give them these little seedlings of knowledge and then
(18:50):
that capstone project comes around and they just grow without
me even being there.
Speaker 1 (18:55):
Yeah, Habib, you mentioned a lot of people need graduate
level degrees to work in AI. Right now, what path
have you seen your students go through after these courses?
Have they said it's opened any doors for them?
Speaker 2 (19:09):
So one of the big challenges we're trying to tackle
on the community college AI education side is pathways for
students upon graduation. Right it's pretty bleak in terms of
having a two year degree and meeting minimum jow brecks.
Our college actually is beginning to offer or developing a
bachelor's degree in AI to alleviate that issue. But I'm
(19:32):
seeing that they're still finding positions because of how marketable
AI skills are. Right now, it may not be, you know,
an engineer, but it could be, Hey, here's an entry
level role at a company, but it's easier for them
to get through the door because they have these marketable skills.
Speaker 1 (19:50):
And in your view, how do you see the future
of AI in the workplace And what's your number one
reason that you tell the younger generation and students why
AI tools are so important to learn.
Speaker 2 (20:07):
You know, when AI was first emerging, let's say chat
GPT right into popularity, everyone was like, AI is going
to replace jobs, and actually there's been a new keynote
I guess that people have been saying, which is people
who have AI skills will be better equipped than those without.
(20:27):
I completely agree on that note, because we work so
much with technology. If we're better to interface with that technology,
we're going to be that much more productive. We can
tackle much more complex problems in a shorter amount of time,
and so I see the future workforce being able to
be once again more productive utilizing these tools. I mean
(20:50):
when you're typing an email and gmails like hey, here's
the rest of that sentence. Yeah right, it's just so
convenient and it helps ease the amount of hand to
paper work we have to do. And we can now
be more creative with that time and solve more nuanced,
more complex problems because we have these systems better ready
(21:10):
to assist us. So someone like me and you can
do a lot more with this lifespan that we have.
We can develop, create ID eight more things because we
have more time to do so.
Speaker 1 (21:25):
The way Habib looks at AI as a tool in
assisting the workflow reminds me of the invention of the spreadsheet.
My grandfather worked at the bank for forty years in
the same desk, the same chair, pouring over bank ledges
with paper and pencil, ensuring all figures balanced exactly to
the scent. With the invention of computerized adding machines and
(21:45):
then later spreadsheets on personal computers, there's laborious efforts that
my grandfather previously undertook had now become so quick and accurate.
He retired before the advent of these technologies, but I
often think how helpful those tools would have been for him.
AI in the workplace empowers everyone to focus on what
they do best. Learning these AI tools, like learning how
(22:08):
to use a spreadsheet, gives employees an added edge in
how they work as individuals and within their teams. I'd
just like to get your thoughts about the AI tools
for the non engineers and non tech people.
Speaker 2 (22:24):
Well, I think I've been giving this rose colored glasses
look onto AI right where AI is always beneficial and
always used in the right way. But we know that's
not the case. I think that it's important to know
what algorithms and what AI can do because our number
one interface with AI every day is things like the
(22:47):
Internet and social media. And so I have students who
may be dealing with some kind of addictive behavior and
they don't realize that AI recommendation systems that are used
in sol social media are constantly feeding them content that
may make them feel stuck in that frame of mind
and that addictive cycle. And so I think it's important
(23:10):
for the general public to know what AI thinked imagery
looks like, what algorithms are out there, and how they
use your preferences to feed you more content that you like,
just for our own mental wellbeing. So I see my
class AA in one hundred as a place where people
(23:30):
can come and learn about these technologies so that they're
better equipped to personally manage their interface with them right
mentally manage it.
Speaker 1 (23:38):
Yeah, and are there any ethical considerations you try and
emphasize when teaching your course to your students.
Speaker 2 (23:46):
So I try to give my students a broad overview
of AI ethics, because again, you could dig into one
quite a bit and there's still a ton of content
left there. So I started talking about, like what topics
there are in AI ethics. There's privacy and surveillance, there's
manipulation of behavior, there's jobs and autonomy. So those are
(24:11):
all like separate topics that I go over. Then I
can take a step further and I talk about frameworks.
So what frameworks are out there in terms of AI ethics,
Like the European AI Act came out and they have
a framework for how they want to regulate this technology.
Now we're seeing policy on the America side on AI.
(24:33):
My last little tidbit in the AI ethics realm is
trying to dispel some of the fear. I am personally
of the belief that there's not some looming AI monster
coming to eat us, and if there would be, we
would see the development of it, Like we've seen the
development of this technology all along chat GPT wasn't grown
(24:55):
in a lab and everyone was like, oh, I've never
seen this before. We had GPT one, GPT two, GPT three. Yes,
we saw the progress of that technology.
Speaker 1 (25:06):
Yeah, and I generally agree with that that there's going
to be a net positive to the AI growth that
we're seeing. But I think it's incumbent upon people like
you to actually teach and guide students around at least
understanding some of that, as you said, the ethical frameworks
around it, because they're the ones that are going to
(25:26):
be producing these things. Right. So I have three kids,
two of them are now in high school. What advice
would you give to parents and educators who are looking
to introduce AI and STAM related concepts to children at
an early age.
Speaker 2 (25:42):
Man, that's a great question. I've never been asked that.
I've done so many interviews that I've never announced that.
What advice would I give them? You know, I'm a
family oriented person, right, I'm twenty six. I'm hoping to
have a family someday, So I kind of think about
this a lot. One thing I find my classroom is
is if you make it fun, the students get involved
(26:04):
and they get interested. Right. It's like if you have
dessert after your salad. Right, people are just more willing
to eat the salad so that they can have that
dessert and feel okay about it. So, getting your kids
involved in things like Legos Mindstorm, which is a subsect
(26:26):
like a robotic subsect of Legos, even like video games
that are less so dopamine addiction for them and more
so building and creating things using their intelligence in their mind.
I think making the space more fun for them to access,
and then on top of that, making it social, having
(26:47):
them find a friend group where they can relate to
other people about these kinds of things. I think loneliness
epidemic is pretty bad in today's world, and there's ways
you can alleviate that early on in their lives by
getting them involved in a community of other kids who
are open to doing those kinds of things.
Speaker 1 (27:04):
Yeah, what do you envision as the future of AI
and education And what's the number one thing that excites
you most about the role of AI in shaping the
learning experiences?
Speaker 2 (27:16):
I think the way we're interfacing what technology is changing
and being spurred on by AI, that's what we've named this,
and so I'm really excited for the shift that will
come in how we interface with technology. On the education side, right,
we teach people how to use technology, So now we're
going to teach them how to better their use of
(27:38):
technology by including AI education. So I'm really excited that
this new workforce that's coming will be better equipped again
to tackle more complex problems, and who knows, maybe some
of the problems that we've been trying to tackle for
so long will seem simplistic in the next twenty to
thirty years, and I'm really excited for or this emergence
(28:01):
of that, and I hope that we use it in
the right way to better society.
Speaker 1 (28:07):
Awesome. Thanks very much, Havib, Well.
Speaker 2 (28:09):
Thank you. I appreciate your time. It's been fun.
Speaker 1 (28:17):
Thanks to Habib Mata for joining me on this episode
of Technically Speaking, an Intel podcast. Chatting with Habib was
really an eye opener. Being a dad of three, I'm
always on the hunt for ways to help my kids
flourish in their future careers. What grabs me about the
course that Intel and Habib created is that it's not
(28:37):
just your run of the mill four year degree. It's
like they threw open the doors for people from all
walks of life, no matter where they are in their career,
to jump in and really get their hands dirty in
the emerging fields of AI and STEM. The way Habib
gets his students fired up is pretty cool. He dives
into real world applications right from the get go, sparking
(28:57):
that curiosity bug in his students. This style gets them
hooked early on, and then they dig deeper into the
nitty gritty theory behind those AI projects. It's a far
cry for my old engineering days. It's all about slogging
through thick theory books before getting onto the hands on
fun projects. And now, with the solid backing from Intel
and Habib's relentless effort, this program is rolling out to
(29:20):
more campuses across the US, and who knows, soon it
might be a movement that spans the world. That's something
to be excited about, not just for my kids, but
for anyone ready to ride the AI and STEM wave.
Thank you all for listening. Join us again in two
weeks in December twenty sixth for the season finale of
(29:41):
Technically Speaking, an Intel podcast. There's been a real journey
learning about all these new technologies, and our final episode
will explore the challenges it takes to make them all possible.
You definitely do not want to miss its. Technically Speaking
was produced by Ruby Studios from IHET Radio in partnership
with Intel and hosted by me Graham Class. Our executive
(30:05):
producer is Molly Sosha, our EP of Post Production is
James Foster, and our Supervising producer is Nikir Swinton. This
episode was edited by Sierra Spreen and written and produced
by Tyree Rush,
Host
Graeme Klass
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