WEBVTT

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Today, I'm going to show you how anyone -

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and yes, I mean anyone -

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can use computer science
to solve everyday problems

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and how I used it
to solve a problem in medicine.

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My story begins with my late grandfather.

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Anyone who knew him knew that he was
a very happy and very jolly man,

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always ready to go out and try something.

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Despite his excitement about most people
and most things, however,

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he was terrified of needles.

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Even though he was very particular
about his health,

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his enetophobia, or fear of needles,

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made him refuse
to get regular vaccinations.

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Now, my grandfather
is hardly alone in this regard.

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Many people, young and old,

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(Laughter)

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are terrified of needles.

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You guys know what I'm talking about.

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(Laughter)

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Clearly, this is a problem
that needed to be solved,

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and that's exactly what I was thinking

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when I was challenged to design something
for Canada's aging population

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at a summer program
I attended when I was 17.

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The world needed something
better than a hypodermic needle

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to deliver medicine.

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The problem was that I didn't know
how to develop medicine.

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My background and passion
lay in computers.

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But what if there was a way

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that I could use computer science
to solve this problem?

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Now, using computer science
to solve a medical problem

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might seem far-fetched at first,

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but computer science
is actually a great way

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to approach a problem
that may seem difficult to solve.

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So, what exactly is computer science?

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Well, computer science

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is the study of automatic,
algorithmic processes that scale.

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Now, that might sound like
something out of a science fiction novel,

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but it's really quite simple.

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Computer scientists study
how to manipulate large amounts of data

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effectively and efficiently
through algorithms,

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or more simply, through patterns
of instructions on that data.

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So, how can we use this field

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to solve problems
outside of the field of computing?

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Well, one of the best, 
biggest advantages of computer science

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is the problem-solving paradigm
that it teaches.

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Computer scientists are taught

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how to look at complicated problems
in a less complicated light.

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One of the strategies that I used

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in trying to solve this problem
of vaccinating people who hate needles

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was to boil the problem down into its base
variables and ignore all irrelevant data.

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In computer science,
this is called determining scope.

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If something is out of scope,

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then it often adds unnecessary confusion
and irrelevant data to the problem,

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making it harder to understand
how the problem can actually be solved.

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So, what were the specific factors

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that were stopping us
from using something other than a needle?

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I noticed that a lot of the people
that approached this problem

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tended to get really bogged down

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in trying to solve every, every question
to do with vaccinations,

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rather than the specific question of,
"How can we deliver this medicine better?"

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And that would be
like trying to study for an exam

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by rereading the entire textbook

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instead of just your highlighted
and summarized notes.

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So, by considering factors
that were relevant to the problem,

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I was able to understand the problem
in a much simpler light.

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Another strategy which I used
was the concept of "use cases."

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In computer science, use cases
are used to consider the problem

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from the perspective of different people 
who will be benefiting from the solution.

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So, for example, in my case,
I considered the case of my grandfather,

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who was terrified of needles and needed
an alternate solution for immunization.

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However, I also considered the case
of people in developing countries,

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who might not be so much
in need of a comfortable solution

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as they are a solution
that is convenient and cost-effective

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and easy to transport and deliver.

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Alternatively, I considered
the case of people with diabetes,

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who have to use needles
every day, with every meal,

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who might be in need
of a more convenient method.

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So by identifying
the factors that matter the most

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to the people that face the problem,

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you can come up with
a more tailored solution

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and perhaps even understand issues

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that you may not have
considered initially.

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One more strategy I used was
to boil the problem down into two parts:

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the physical perspective 
and the logical one.

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Some parts of a problem might be unlimited
in how you can tackle them,

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and some may have
some physical limitations.

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For example, in my case, developing
an oral vaccine delivery technique

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would have to be something
that a human can swallow,

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so that's a physical limitation.

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But how this system is to deliver
the payload to the bloodstream

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is something that is more susceptible
to creativity and imagination.

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So by identifying which parts
of the problem are limiting

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and which are limitless,

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I was able to understand

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which parts of the problem
were more flexible and able to be changed.

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And in computer science,

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this is similar to a concept
called functional abstraction,

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and it's a great way to understand
which limitations are actual limits

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and which might be more self-imposed.

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So, by determining
the scope of the problem,

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or by understanding the factors that
were actually relevant to the problem,

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I was able to understand what the problem
I was solving actually was.

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By considering different use cases,

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I was able to understand that, not only
would my solution have to be convenient,

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but it would also
have to be cost-effective

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and easy to transport and deliver.

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And by abstracting the problem
into logical and physical factors,

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I was able to focus my creativity
onto the parts of the problem

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that were more susceptible
to out-of-the-box thinking.

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So, by using these
computer science principles

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on this non-technological problem,

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I was able to come up with a pill
for vaccines and other medicines

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which was safer, cheaper, 
easier to transport and deliver,

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and much less scary
than a hypodermic needle.

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I believe that this model can be used
to solve problems big and small.

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Like, wouldn't it be great if, 
using computer science,

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we could solve problems in medicine,

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in arts, in business,
or even just at home?

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If we are all courageous enough
to use these computer science principles

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to tackle our everyday challenges,

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we can solve problems faster
and reach ahead to a better future.

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Thank you.

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(Applause)