VOICES
Interview
find a different angle and that usually
leads me to the next thing.”
When Gerard bought her second brain
sensor, it was entirely open source,
exposing her to a lot of raw data. She
realised she couldn’t really do anything
with it until she knew more about
machine learning and so that has become
her focus over the last year. She’s
currently looking into different kinds of
data that can be used for machine
learning. For her Beat Saber experiment,
she used camera data, while her Street
Fighter demo used accelerometer and
gyroscope data. Now she’s exploring
sound. “If you build a spectrogram out
of sound data, you can see the difference
in patterns between when you’re
speaking, knocking on a door or chopping
carrots. As microphones are all around
us, in laptops, phones and smartwatches,
you can build software to recognise these
patterns without changing your hardware
and buying expensive smart devices for
your home. So you could automatically
pause your TV when your phone is ringing
or pause a video on your iPad when you’re
cooking and the system hears the sound
of chopping.”As usual when tinkering with new
technology, Gerard not only notes the
opportunities but also the limitations. For
example, to work with machine learning
data, you need lots of samples and it’s
important that you check their quality.
“When you train your algorithm,
remember it’s just a piece of code,” Gerard
advises. “It’s not actually smart. It’s going
to find patterns but you might not always
understand why it’s predicted something.
There is a lot of trial and error. Sometimes
you may have to go back and, for example,
check your data is labelled correctly to
reguide the algorithm.”
The more Gerard looks into new types
of human-computer interaction, the more
she finds keyboards and phones to be
quite restrictive. “There are so many ways
that you could make your house adapt
more to the way you live your life,” she
points out. “You could make your
environment a lot more playful and a lot
smarter than it is now. I’m endlessly
fascinated by coming up with creative
ways of doing things that we didn’t know
we could do. Making a device work for you
is so much more exciting than just
learning how to use it.”It was one of the best decisions of her life.
“Initially, I tried to learn to code by myself
after work,” she remembers. “But when
you don’t know anything about an area,
you don’t even know what to Google. I
knew what HTML was but I didn’t know
how to add JavaScript to a website. I
thought if the bootcamp didn’t work out,
I could always go back to my job as a
project manager. At least I would better
understand what my developers were
doing. But I really liked that feeling of
writing a piece of code and it does
something in front of you. I still feel that
with hardware now. I loved it and never
went back.”
While the problems Gerard solves in
her side projects are often harder than
the ones at work, whenever she writes a
blog post or speaks at conferences, her
goal is to demonstrate that nothing is
inaccessible. “I’m really excited about
that,” she explains. “The research papers
I read to inspire me to build something
are really hard to understand. They’re
written in a very scientific way but they’re
needlessly complicated. You could break
it down and make it so much easier.
Anybody can come up with a good idea
and build something interesting if they
know that a certain technology is
accessible. Otherwise you just feel blocked
by thinking it’s too hard and you’re not
even going to try.”
And so there’s seemingly no limit to
Gerard’s side projects. There’s always
something new to discover. She maintains
a list of potential prototypes she wants to
work on (for example, interacting with
the electrical signals in plants) and
researches a wide range of topics. “I like
to mix more than just tech, so I don’t only
read news about front-end development
and JavaScript. I follow what research
centres like the MIT Media Lab or Disney’s
labs do. I spend a lot of time exploring
their projects and if they’re not open
source, they at least give me an idea of
what researchers are looking into. I then
think about a way to make it happen with
web technologies. If there’s a project
about interactive textiles, I think about
how to build something that’s a bit more
helpful to people with motion
impairments, for example. I always try toPhoto: JSConf.Asia 2019