How I went from protruding in pc technological know-how to
defining, for myself, what an engineer looks as if.
The hyperlink among statistics and garb changed into now not
immediately apparent to me.
There were two truths in my life at one time; matters I knew for certain: One, I become at
college completing a degree in Computer Science. Two, in my unfastened time, I
loved flipping through pages of Harper’s Bazaar.
These truths seemed independent from each different, and as
though they stemmed from two, completely specific corners of my likes and
hobbies. After all, what does an potential to code recursive algorithms should
do with the colors in Prada’s new collection?
I quickly learned: lots.
It changed into my second 12 months at Harvard that I
decided to pursue laptop technological know-how as a diploma and, if I became
good enough, a profession. It became then that I knew — as I walked into a
lecture corridor of 100 students, just a handful of which have been women,
feeling strongly juxtaposed against a sea of graphic tee-shirts in a summer
dress and cardigan — that I did no longer match in nicely.
I recollect so vividly looking at, in actual-time, and
unfolding proper in the front of me: apparel can imply some thing.
There are numbers to back this up, you realize. 86% of
software engineering experts are men. And, though numbers are just numbers,
it's miles frequently difficult to look past them; to remember the fact that
fields ruled by sturdy, male-orientated stereotypes don’t ought to remain that
way.
Since garb is so carefully tied to our identities; how we
present ourselves to others; what others consider us upon first-glance,
clothing turned into a large purpose why I so strongly stood out.
While working one in every of my first software program
engineering jobs summers in the past,
proud to expose up in clothing that so strongly juxtaposed against the opposite
engineers’ — summer time dresses in blue satin; black, flowing skirts with
kitten heels — I become advised by a female older than me who, at this point,
I’d closely favorite —
‘I used to get dressed such as you, however it made me
honestly uncomfortable.’
There became nothing else I idea to say. Maybe, I added —
‘Yeah, it makes me uncomfortable too,’ as it did. It
doesn’t, anymore.
The phrases she said to me felt like they shouldn’t had been
spoken; as though she had said to me the elements of myself that made me
exclusive were standing in my manner or need to, in time, be changed. I decided
to maintain dressing as I wanted.
I spent the rest of my internship learning about new,
innovative technologies. I was in particular attracted to image recognition, as
it regarded, to me, just like the magical part of laptop engineering. You can
display a computer an photograph, and it can let you know what’s in it? I’ll
believe it after I see it.
I favored searching at photos — in reality, I spent a
exceptional deal of time flipping through Harper’s Bazaar editorials; Vogue
Runway’s collections — so, perhaps, I thought, I ought to train a computer to
discover things in them, too. Things that were vital to come across: midi
versus maxi period hemlines; monochromatic colour palettes; pointed versus open
toe shoes…
There is a lot lovely creativity, artistry, and subjectivity
in fashion; in what, or who, evokes what we pick out to wear. However, ought to
there likely be a manner to make feel of all this artistry — to mixture
quantitative data about designs, so one can, in time, higher apprehend them?
By mastering to tie numbers to garb — studying what
probabilities of a set, or outfit, exhibited which traits — I started out to
better understand fashion; the staple silhouettes and designs used frequently
across designers versus the problematic, creative, micro-developments
particular to every series
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