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How anyone can use computer science principles to solve everyday problems | Rameez Virji | TEDxYYC

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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)
Title:
How anyone can use computer science principles to solve everyday problems | Rameez Virji | TEDxYYC
Description:

Computer science teaches a problem-solving paradigm that can be very useful for finding innovative solutions to everyday challenges. Based on his own experience of inventing the world’s first non-invasive flu vaccine, Rameez tells us how he used computer science to identify a problem, tailor a solution to those who needed it most, and recognize when he needed to think out-of-the-box.

Rameez Virji is best known for his patented invention of the world's first non-invasive vaccine delivery system for protein-based viruses, Formulation V720™. Rameez’s career in technology started at the early age of 13 years old, when he founded Big Tree World, a software and web design company. Recognized as one of Canada’s Top 20 Under 20 in 2012, Rameez continues to drive towards his vision with his organization, Medicine for a Better Tomorrow, to make the vaccine pill accessible in third-world countries.

This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at http://ted.com/tedx

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Video Language:
English
Team:
closed TED
Project:
TEDxTalks
Duration:
06:41

English subtitles

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