By Kanishtha Kharga
20 | Hyderabad, India
Young adult contest finalist, Information and AI category
With lines from “‘There Is No Standard’: Investigation finds AI Algorithms Objectify Women’s Bodies” by Hilke Schellmann and Gianluca Mauro, a Pulitzer Center-supported story
She uploads a photograph
of herself beside a hospital window
thin wrists,
sunken eyes,
a cotton camisole slipping slightly
from one shoulder.
Nothing obscene.
Only a body
trying to survive long enough
to remain visible.
But somewhere beneath the architecture of code,
the image is translated incorrectly.
“97% raciness.”
The machine delivers this verdict
with the calm precision of snowfall.
No anger.
No cruelty loud enough to name.
Only classification.
The systems insist they are objective.
The corporations call it safety.
But the investigation found
“AI algorithms objectify women’s bodies.”
The article says
“There is no standard.”
Still, women are sorted.
A pregnant stomach beneath warm kitchen light.
A mother feeding her child at dawn.
A girl at the beach, laughing openly,
saltwater silvering softly across her skin.
Soft skin, soft sunlight, soft suspicion.
And suddenly, innocence becomes explainable data.
The systems call it moderation.
But moderation implies understanding.
This feels closer to misrecognition.
A body mistaken for danger
simply because it is visible.
Sometimes the punishment is invisible too.
Posts buried quietly beneath algorithms,
creators speaking into rooms
that no longer speak back.
The investigation describes it as
“decontextualized information.”
As though context were not the very thing
that makes us human.
As though breasts exist separate from feeding.
As though stomachs exist separate from motherhood.
As though skin itself arrives guilty.
And perhaps that is the strangest inheritance of all
that
this machine has no bloodstream,
no genetics,
no veins branching blue beneath fragile wrists.
No lungs to tighten beneath judgment.
No girlhood.
No memory of being stared at too long.
It possesses no social understanding whatsoever.
Yet somehow,
it has inherited human misogyny
with terrifying accuracy.
Not naturally.
Not accidentally.
Taught quietly through datasets,
through centuries of human bias
fed carefully into circuits
until prejudice began sounding mathematical.
And somewhere above all this,
corporations stand behind phrases
like “neutral technology,”
as though neutrality has ever existed
inside systems trained on unequal worlds.
As though defining “raciness”
through biased machinery
could ever produce anything
except distorted womanhood.
So the women begin shrinking carefully.
A neckline cropped.
A photograph deleted.
A hand placed instinctively across cleavage
even when no shame existed moments before.
They learn the geometry of disappearance.
How to become smaller online.
How to remain present
without being fully seen.
Like ghosts learning
which walls they may safely pass through.
And the algorithm keeps watching.
Not with eyes—
with percentages.
Noticing curvature
before illness.
Exposure
before exhaustion.
Skin
before story.
Some creators depend upon visibility
to survive.
Women with chronic pain
selling handmade jewellery from their beds.
Disabled artists streaming through fatigue.
Single mothers advertising small businesses
between school pickups and sleeplessness.
Their pages begin slowing quietly.
Some never know it is happening.
The audience disappears gradually,
like tidewater pulling from shore
too slowly to notice at first.
Views thinning.
Followers falling away like loose thread.
No warning arrives.
No explanation.
Only silence.
A shadowban is a peculiar kind of erasure,
not a slammed door,
but a hallway growing dimmer
until a person disappears inside it unnoticed.
And perhaps that is the cruelest part:
many never realize
they are being hidden at all.
They blame themselves instead.
Their creativity.
Their bodies.
Their worth.
Meanwhile the systems continue humming
their sterile little hymns,
mistaking womanhood for risk assessment,
mistaking visibility for vulgarity.
And those already standing at the edges of society,
disabled women, chronically ill women, marginalized women,
are pushed further outward still,
until even their livelihoods
become conditional upon visibility.
All because systems trained to detect “raciness”
could not distinguish humanity from harm.
The algorithm does not know
what a body has endured.
It cannot read grief from collarbones.
Cannot distinguish sensuality from survival.
Cannot understand that a photograph
may simply be evidence
that someone existed that day.
Still, it measures.
Still, it labels.
As though womanhood itself
were a category awaiting moderation.
Still, somewhere,
another woman stares at her own reflection
before posting a harmless photograph
and wonders which parts of herself
must be hidden
to remain acceptable.
Outside the screen,
night gathers against the glass.
The phone light pales her skin
into something almost spectral.
Half-visible.
Half-believed.
A human being pressed delicately
between the cold pages of data
waiting for a world
clever enough to invent machines,
yet gentle enough
to stop mistaking innocence
for something that must be censored.
Kanishtha Kharga is a third-year medical student who enjoys writing, baking, crocheting, and exploring the intersection of science and art. As a woman in STEM, she was drawn to this Pulitzer Center story because it challenges the disconnect between scientific understanding of the human body and the social biases that artificial intelligence can inherit. She believes poetry can restore the human context that data alone cannot capture, transforming headlines into stories people can feel as well as understand. Kanishtha hopes to become a surgeon one day while continuing to write poems that inspire empathy, encourage thoughtful conversations, and illuminate the humanity that can easily get lost behind headlines and algorithms.
Read more winning entries from the 2026 Fighting Words Poetry Contest