Content Note: death, car accidents, drug overdose, murder, internalized homophobia, mentions of gun violence

 

I am simply not the kind of person who dies.

Even before the Monarch told me the truth, I knew it the way animals know to burrow into the earth before landslides, the way they taste storms on the wind and feel the eyes of hawks on their backs. I knew it because the car in front of mine was the one that got T-boned in the intersection when the light turned green. I knew it because the grocery store I always go to on Wednesdays was shot up with an AR-15 on a Thursday. And I knew it when I watched the casket close on my grandmother’s powdered gray face, watched them lower her into the ground, and could not comprehend an eternity of dreamless sleep or the quiet way everyone else just accepted it—it is a language I have never learned, it is a sleep I will never find. When the world ends in melting ice caps and forest fires and skies choked with smog, I will still be here, in this basement, in the dark.

Twenty-eight years old is probably too young to claim immortality, but most people my age have not felt death count their bones and map out their veins and cup their face in his hands and whisper not you, not yet. For whatever reason, he does not want me. This is the only conclusion I can come to as I sit in the darkness of my parents’ basement-turned-office, one hand deep inside a bag of Cheetos and the other scrolling through dubiously-obtained case files on my high school classmates, most of whom are now dead.

Their deaths might not be so strange if I lived at the foot of an active volcano, or on a fault line, or next to the Chernobyl plant. But Saglo, New York, is just a fishing town on Lake Ontario, a tourist trap with crumbling Victorian houses that look nice on Instagram but are full of mold inside, hand churned ice cream shops, thin-crust pizza, lake houses turned Airbnb’s. It is a Nice Place to Live. At least, it was.

After the first funeral, I swore to never come back. Yet here I am, ten years later, living in my parents’ basement to “save money for a house,” but that’s not the real reason, that’s just the reason my parents want to hear. All of my money goes—has always gone—into the Monarch. I may never buy a house, but I will have bought something infinitely more important: the truth.

Last month, I received a Facebook invitation to my ten-year high school reunion, complete with a photo of my twelfth-grade homeroom for last names Campbell through Czelusniak. Almost no one in the photo is smiling because our homeroom teacher couldn’t figure out how to use her phone camera and made all of us late to first period, but now the impatience on our faces reads like stark condemnation of anyone who dares to look at a blurry, overexposed picture of a dozen ghosts.

Somehow, I never imagined that I would be the last one left. I do not have the backbone of the final girls you see in movies. I never even honk while driving. Nor am I a picture of perfect health, though I do occasionally drop some mushrooms in my ramen and fast-walk to bus stops, which increases my heart rate more than it probably should.

If we had known, at the time, that one day our homeroom picture would look like the “before” picture of a sick elimination game, everyone would have bet that I’d be out in the first round. Elsie Chen does not sound like the name of a survivor.

But there is a reason that I’m still alive.

I just don’t know it yet, and I don’t need to. That’s what the Monarch is for.

Because, just as I designed and prayed for and inevitably came to regret, the Monarch is never wrong.

On the day that Harley Copeland died, I was eating pho at three in the morning, alone at a booth a mile from campus. There was a 24-hour Vietnamese restaurant near my school, and eating pho at 3 AM felt like an acceptable College Freshman thing to do, unlike trying to cry quietly enough that my roommate wouldn’t hear from the top bunk. I woke up too late the next day, bloated from all the sodium, and saw a flurry of sad Facebook posts about Harley. Pictures of her smiling in her track and field uniform, in her blue dress and fake tan at prom, in her oversized gray sweatshirt and Uggs in the bleachers during a football game.

Eight months after graduation, Harley’s car skidded on ice while driving to class and wrapped around a telephone pole. The headlines reduced her to “nineteen-year-old woman killed on the scene” and it was the first time I’d thought of her—of any of us—as women instead of girls.

From then on, Harley lived in my head like a ghost on a perpetual loop—walking into homeroom with a large iced coffee from Dunkin’ even in the middle of winter, slamming her books down thirty seconds before the bell, draining her cup before the end of morning announcements, tossing it in the recycling bin from across the room, never missing.

It is strange to have known a dead person only in passing. After sitting next to her in homeroom every day for four years, it was hard to imagine a day that Harley wouldn’t storm into homeroom with an iced coffee. I could only count on a few things in life—waking up with my blankets crumpled on the floor after dreams so vivid they bled into reality, the dandelions in the sidewalk cracks on my way to school that would always grow back no matter how much weed killer my neighbor sprayed, the fat cat lying belly-up in the sunlight of the coffee shop window by the water, and Harley Copeland sitting next to me with her iced coffee.

My mind crawled with morbid thoughts—I wondered if anyone told the new class that one of them was sitting in a dead girl’s chair. I imagined myself traveling to the past, knowing what I know now, telling Harley that she has only eight months left to live, and I couldn’t decide if doing so would be cruel or kind, but feel certain it would have changed something. She had the right to know.

My mom asked if we were friends and I said no, because it was the truth, but her death wedged somewhere deep inside of me, like a robin building a nest between my ribs, itching.

I didn’t know what to study in college, so I took my gen ed requirements to buy some time while I made my own program. I named it the Monarch, after the Butterfly Effect, the flap of paper-thin wings that can start a hurricane across the world. I wanted to find those moments, as small and quiet as a butterfly’s wings beating against the sky, and learn what cities they’d destroyed, what tides they’d turned, what stories they’d ended. After all, there is a reason for everything, and I intended to peel back the skin of the world, look at its twitching innards.

The newest AIs were too expensive for a state college student, so I bought a first gen AI and decided to help it evolve on my own. How hard could it be?

I signed up for an intro coding class and spent too much time at my professor’s office hours asking questions unrelated to classwork. I told him I wanted to make a machine that determines the cause that comes before the effect, but Professor Pérez said it was impossible.

“AI predicts outcomes,” he said. “It doesn’t understand causality. There are too many factors to consider. It can identify correlation, but that’s not the same as proving causation.”

But he was talking about human limits. People can’t determine causality with 100% certainty, but wasn’t that the point of technology? To transcend our limits?

“Can’t you train it?” I said. “Even dogs understand cause and effect. Couldn’t you feed it enough data, enough examples of cause and effect, that it starts to understand?”

Professor Pérez looked at me oddly. “I don’t know if there’s enough data, or time, in the world for that. What exactly are you trying to make, Elsie?”

But he wouldn’t have understood it even if I told him. So I ignored his advice, and the Monarch was born as I fed it case files on lung cancer patients, dubiously obtained from a med school acquaintance desperate to pass Chinese 101 who had no qualms about letting me do his homework for him. I taught the Monarch, again and again, the cause and effect of that one singular process. Smoking causes hazy-looking lung x-rays. Hazy lung x-rays cause lung cancer. Lung cancer causes death. It took a long time and a lot of case files before my cheap AI started to understand, but I had all the time in the world.

Luca Clementi died during a heatwave in August towards the end of my second summer break in college. His family lived down the street from mine, so I found out when the fire trucks blocked our street at 2 AM, painting it blue and red. The ambulance loaded someone on and then drove away slowly, no sirens or lights.

The obituary on Facebook didn’t say the cause of death, but his sister posted a link to an overdose prevention charity, so it wasn’t hard to figure out what happened.

Luca was the second kid from my high school to die that way, but in the next ten years, there would be fifteen more. The police arrested someone they were absolutely certain was The Dealer, which was met with much fanfare and an award from the mayor, but were oddly quiet when people kept dying even after he was in jail. There were newspaper articles about my town, speeches about the opioid crisis, drug raids, public service announcements, a memorial bench outside my high school, and a lot of other things that I knew wouldn’t have mattered to Luca Clementi, wouldn’t have saved him.

Luca and I played in sprinklers at the end of the street when we were kids. We sat in the grass and ate pizza and drank apple juice out of paper cartons and he showed me his Pokémon cards. We fell asleep a couple hundred feet from each other for eighteen years and some change, in the same solidly middle class suburban street, and nothing about Luca had ever made me think he was destined to die in the back seat of a used Honda Civic, choking on his own vomit.

I didn’t even know where you could buy the kind of drugs that could kill you. I’d aced my DARE classes in elementary school and been so prepared to turn down hard drugs at parties, not realizing that no one would invite me to parties much less offer me their expensive drugs. Luca’s death was the first time I realized that even though the entirety of my life feels as big as a universe, there are a thousand universes all around me, only sometimes intersecting.

Somehow, when Luca died, he felt more real to me.

I was a quiet person, both inside and out. I did not burn with dreams, I did not surprise my parents. At times, I felt like I was on my back in a river, watching the clouds go by, waiting for my life to really truly begin, only to find as I got older that this is it, this cold numbness on my back, this unrelenting pull towards the end, this is all there is.

I imagined Luca dying alone, and I suspected it probably hurt at least a little bit, and I wondered if he knew what was coming, if he was scared, and the imagining of his pain was louder than his mother screaming as she kneeled on the sidewalk, and I saw myself choking for breath on my back, looking up at a sky that suddenly turned to a smoke-stained ceiling of a Honda Civic, moonlight through the tinted windows, and realized that this is it, this is all there will ever be.

After devouring all thirty-two seasons of America’s Funniest Home Videos, the Monarch began to recognize the exact wobbly stance that preceded someone falling, the velocity and angle at which bikes will not land safely on the ground, the number of people on a whitewater raft that will cause it to tip over on certain turns.

It made some incorrect correlations that I needed to painstakingly deprogram—the people on the toppled raft were all wearing life vests, but that doesn’t mean life vests cause rafts to flip. And the laugh track in the background does not mean that laughter is an indicator of imminent danger.

That sort of weeding process took longer than actually feeding the Monarch datasets, but by the end of my junior year in college, I could input random movie clips and it could tell me without prompting that Hans Gruber fell to his death in Die Hard because John McClane unclasped the watch he was clinging to, and Gandalf fell on the bridge of Khazad-dûm because the Balrog’s fiery whip grabbed his ankle. I did have to teach the Monarch what a Balrog was, but wasn’t too concerned about the real-world implications of that particular lexical gap. 

But all I had made was an AI that told me things I already knew.

“You need a larger dataset if you want more insightful outputs,” Professor Pérez said, at this point my major advisor and used to my schoolwork-evading questions. “It would take years, if not lifetimes, Elsie.”

“What kind of dataset?” I said.

He shrugged. “It depends. What kind of question are you trying to answer with all of this?”

But I wanted to answer every question, everywhere, and I didn’t know how to explain this to myself, much less to Professor Pérez.

Two weeks later, the idea came to me.

It took some prodding to get the business school students to explain it to me, but by the end of the week I was in the process of setting up an LLC, was the owner of a company called Monarch, and had a meeting with a data broker. I put on a blazer and my only pair of heels and met him downtown, holding a briefcase with nothing inside it.

“I need data,” I said.

He gestured for me to sit down. “You’re in the right place. What kind of data?”

“Data about people and their lives.”

“You’ll have to be more specific than that,” he said, typing something into his computer.

“What do you have?” I said, afraid that I’d say something stupid, that I’d show him I wasn’t a business owner but a twenty-year-old way out of her league.

“Well, there’s the basics,” he said. “Everything from browser cookies and trackers from anyone who’s ever touched a computer. Any speech that smartphones overhear while apps are running in the background. We scrape publicly available information too and compile it into profiles. Those things combined can tell you everything from someone’s political party to what kind of armpit rash they’ve been Googling. Most advertisers are very satisfied.”

Of course, this man thought I wanted data so I could sell products through targeted ads. The truth was much worse.

“What if I want more information?”

The man stopped typing. “What kind of information?”

“Medical,” I said.

“Like mortality tables?” he said. “For health insurance?”

“Sure, but not just that,” I said. “Recent death certificates. CCTV footage. All of it.”

“Ah.” The man shut his computer and leaned across the desk. “Officially, that would be illegal.”

But I was good at hearing unsaid things. “And unofficially?”

The man smiled. “How much are you willing to pay?”

Sabrina Choi texted me six months after high school graduation, a few weeks before winter break. She wanted to get pizza in the square, which was a strange request because she’d never wanted to be seen with me in public before. She sat behind me in homeroom and ate Lucky Charms out of a gallon sized bag and doodled with a 100-pack of colored pencils. But we never talked for long at school, and though she was too nice to say it, I was sure it was because Sabrina was the good kind of Asian—the kind who wore cute skirts and lip gloss and went to church and played Rachmaninoff Piano Concerto No. 2 by the time she was twelve. I was the kind who had no boobs and unflattering glasses and hadn’t figured out what to do with her lack of eyebrows and played video games on the weekends. When guys said they liked Asian girls, they meant people like Sabrina.

I didn’t answer her because I didn’t know how.

A week later, Sabrina was a “nineteen-year-old female victim” in the New York Times. A man she’d never met stabbed her in the throat eleven times with a combat blade at the train station and threw her body on the tracks, where the incoming train made certain she was dead. There was a candlelit vigil outside the local Korean church, but I didn’t go because somehow I didn’t feel I was allowed.

Her death got a lot more news coverage than the other deaths from my high school. People liked to hear about pretty Asian girls getting chopped up. NYU made a scholarship in her name, and people from my high school tried to do the same but no one really donated much because no one had much to give and the idea died quietly.

When the press coverage died down a bit, I visited her grave, dropping a bouquet on it. Petals burst and scattered, and the wind picked them up.

“What did you want?” I said.

Maybe she wanted to pick my brain about my CS major. Maybe she had an ugly Asian guy friend who was hitting on her relentlessly and she wanted to pawn him off onto someone more in his league.

Or maybe she got to her fancy private college and realized that she was alone, that everyone was so focused on their own dreams and finding their own friend group and replacing their high school boyfriends that it was hard to find someone to just sit next to and not feel like a black hole eating up space, like you would have been better off being literally anyone else but you. Maybe she knew that I was no one too, that I would understand.

A car pulled up and I hurried away, irrationally afraid that they were here to see Sabrina too, that I would be caught in the terrible crime of leaving flowers at the grave of someone I couldn’t honestly call a friend. The feeling that swelled in my chest as I walked away with my unanswered question was not quite sadness, because I was not allowed to be sad about Sabrina Choi. But inside, everything felt sharp, like my lungs expanded into a cage of spikes. I was sure that anything I touched would start to bleed, because my hands were cold and shaky and wanted desperately to sink into something solid, to dig my nails in and not let go.

It has been ten years since graduation, since I started working on the Monarch, and today, it will answer my question.

It took about five years to feed the Monarch my new datasets, to edit down the incorrect assumptions, to proofread its new causality algorithms. But I quickly realized that with every new batch of data, it needed my help less and less.

It started reaching farther back in time to find causation. Everyone knew that a banana peel on the floor causes the next passerby to slip and fall, but the Monarch started pointing the finger at the person who dropped the banana peel, the person who ate the banana, the person who bought it, the person who packed it into a crate to ship it from Costa Rica. With access to all CCTV and constant surveillance through microphones on smartphones, there were very few blind spots in the path from banana tree seed to passerby slipping on a banana peel and slamming their face into the sidewalk. After year three, I started feeding the Monarch data from historical archives, and it started painting its own pictures of the past. Sure, there was no CCTV back then, but the Monarch knew enough about human behavior that it could fill in the blanks.

But the connections became more dubious the farther back you went. I had to teach the Monarch when to stop, or else every single event could be blamed on the birth of the universe. 

I programmed it to stop backtracking at the Point of No Return, the action that locked the probability of the origin event at 99.99% or higher. Before that, individual choices and external factors had a lot more weight—the grocery store could miss their banana pickup shipment, or the bananas could be delivered too late and the offender could pick up an apple instead—but for every event, there was a certain threshold at which the possibility of other reasonable factors influencing the outcome became negligibly small. Certain actions just locked in certain outcomes, full throttle ahead, no turning back.

Usually, this came five or six steps before the origin event:

JFK died because of a missed phone call.

Edgar Allen Poe died because he forgot his coat.

The Space Shuttle Challenger exploded because of a piece of gum on the sidewalk. 

I didn’t believe it at first. Especially when Professor Pérez dropped dead from a heart attack a week before graduation and the Monarch insisted he died from a pulmonary embolism brought on by drinking a spinach smoothie that interfered with his anticoagulant medication. I tried to correct it, but the Monarch buried my screen in error messages until my eyes crossed. 

I found myself crossing campus and going to Professor Pérez’s office, grabbing the key he kept above the doorframe because he always let me borrow his books after hours, and finding the bottle for a spinach smoothie in the trash and a prescription container of warfarin in his drawer.

After that, I couldn’t escape the creeping sensation that the Monarch understood humans better than we understood ourselves.

It’s analyzed millions of hours of human behavior, but unlike us, the Monarch doesn’t look away in discomfort. It just tells us, point blank and unflinching, where we went wrong. 

Some people turn to gods they can’t see to answer their questions.

I built my own god.

So today, coming up on my high school’s ten-year reunion, I open up Sabrina Choi’s case file, pull up her obituary, and feed it into the input section of the Monarch.

Once, and only once, Professor Pérez asked me why.

“I’ve never seen someone so invested in other people’s deaths,” he said. I was sitting in his office, the last month of my junior year, my laptop overheating on my jeans. The room had started to feel smaller and smaller over the years as his bookshelves filled up with new texts and his desk grew crowded with trinkets from his travels.

But I didn’t want to answer because the question was unfair. He wouldn’t have asked me this if I was obsessed with video games or football or anime. Death was the most important thing in the world, but because I wanted to dissect it instead of leaving it a sacred mystery, I was strange.

“I don’t have an answer that would satisfy you,” I said.

Professor Pérez fell quiet for so long it began to feel like a judgment.

“Fear of death is universal,” he said at last, “but most people don’t—”

“I’m not afraid,” I said, frowning. “I can’t be afraid of something that will never happen.”

“I don’t follow,” he said.

I bit back a sigh, typed a few lines into my program, then spun around my laptop and set it on Professor Pérez’s desk.

The Monarch had a sandbox that I rarely used, because what would be the point in speculating about what could have been? But, as Professor Pérez said, AI were first made to predict outcomes. That was never the Monarch’s purpose, but it was the Monarch’s first language.

“When I go to the sandbox and ask it to predict my own death,” I said, “all I get is an error message.”

“Elsie,” Professor Pérez said, recoiling, “you shouldn’t try to predict something like that.”

“I already did,” I said, shrugging.

“Then there must be a bug in your program,” he said. “I can check it over again for you if you—”

“No,” I said, the word firm, a door swinging shut.

Professor Pérez withered back into his chair, and for the first time, I noticed how much older he looked than when we first met. Maybe he had always looked the same, but only now, when he was looking at me so sadly, did I realize it. “AI predictions are not absolute,” he said. “Any algorithm is just an extension of its creator. You are the Monarch, Elsie.”

But he was talking about human limitations again, a barrier I had long since surpassed. Like most people, he was afraid of the truth and projected his fears onto me. People who were afraid did not build gods in inside their computers.

I looked at Professor Pérez and realized all at once that this moment, like everything else, was a Point of No Return. This world inside his office of trinkets and books and code felt like forever, but one day, inevitably, he would die, and I would be the only one who remembered this tiny universe we had occupied. But still, the feeling crashing over me was not quite fear, but a kind of nostalgia for a time that had yet to pass, a mourning for who I would become when, at the end of all things, I would sit alone in the dark.

In 0.2 seconds, the Monarch gives me the answer I’ve been waiting for for a decade.

I close my eyes, take a deep breath, wipe my glasses on my shirt, and at long last, turn to the words that will change everything.

One [1] broken umbrella rib.

For a long moment, I stare at the screen.

Usually, it is easy to forget that English isn’t my first language. But these words somehow reach my eyes but not my brain, as if they are words I’ve never learned, sounds I can pronounce but not understand.

My hands feel oddly heavy as I type another line, prompting the Monarch to break down the preceding chain of events.

One [1] broken umbrella rib —> Sabrina Choi throws away an umbrella in a public garbage receptacle -> Sabrina Choi runs to train station in the rain —> Sabrina Choi arrives at 125th street at 11:43:54 AM —> Sabrina Choi walks in front of Darren Glover -> Sabrina Choi is stabbed eleven [11] times in the throat by Darren Glover -> Sabrina Choi dies of acute exsanguination

The Monarch is never wrong, I tell myself. It doesn’t matter if you don’t like the answer. No one ever likes the answer.

But somehow, this particular Point of No Return is unacceptable.

It is so offensively simple. It is something that happens to millions of people every day without leading to death. It is unrelated to anything of importance in her life, any decision she made, any person she knew, any belief she held. In everyone else’s story, it’s meaningless. 

It can’t be the answer.

There is no way that the only difference between me and Sabrina Choi is one [1] broken umbrella rib. There is no way that so many of my classmates were the 0.001% of middle class teenagers who die young, the percentage so small that no one ever thinks it will be them. Maybe some mold growing in our classroom had ravaged our brains, made us more likely to crash cars and do drugs and…attract serial killers? Or maybe something our homeroom teacher said had subliminally planted itself in our minds and had a ripple effect. And whatever it was, something about my diet or body wash or the tint of my glasses had made me immune?

Maybe Sabrina’s case file was too sparse. She was only nineteen, so maybe the Monarch didn’t have enough information about her. Yes, that must be it. Professor Pérez had half a century’s worth of data to mine, so it was no wonder the Monarch understood him. But how could a machine truly understand Sabrina Choi? Even her parents hadn’t understood her. Not her friends, not her sisters, not her pastor.

I didn’t understand her at all. Not when she wordlessly held out her bag of Lucky Charms to me in homeroom, as if I was just going to grab a handful of Styrofoam marshmallows to eat dry. Not when she slipped notes of things she would never say out loud in my locker. Not when we sat three rows apart in a movie theater and she didn’t so much as turn around so no one would know we’d arrived together. Not when she pulled me into her car after the movie and kissed me with lips that tasted like salt and cola and whispered that she was sorry. Not even when she sat in my room and cried about how she had no dreams, that she didn’t want to go to college, that she felt like an old boat hitched to the back of the pickup truck being dragged along a jagged stretch of highway, not knowing where she was going. And not when she looked at me from two seats down at graduation and didn’t smile, didn’t speak, just turned back to her family and I never saw her again.

I turn back to my other monitor, clicking rapidly through the mess of folders on my desktop until I find the files on my other classmates. I feed Harley Copeland’s file into the Monarch and the result pops up even faster than Sabrina’s:

One [1] papercut on knuckle of right index finger

My hands begin to sweat. Harley’s file was the most sparse of the bunch, so probably the least accurate. I feed Luca’s file in next, and the extra 0.2 seconds of loading time gives me hope, but then his Point of No Return pops up as well:

Shoelaces on left shoe untied

I refresh again and again, but there is no error. My skin burns, and the basement room that normally brings winter air shivering through the insulation is suddenly sweltering as I pull up the files of everyone in my homeroom class and feed them into the Monarch, one by one.

One [1] superfluous ounce of mozzarella cheese in casserole
One [1] stray kitten crosses the road
27% tinted car windows
Jammed gumball machine in Panda Express
One [1] lost pickleball

I turn around, facing the blank wall because I can’t look at the Monarch anymore. You’re not supposed to question your god, that’s bad practice in any religion, and because my deity is made of science, disagreeing is only lying to myself.

But I cannot live in a world in which a single umbrella rib determines your fate. 

Because if that is really the only thing that bridges the thin line between life and death, then I myself am only one footstep away from a thousand terrible endings, and I know that’s impossible because I cannot die.

Death is for distant acquaintances, for newspaper headlines that make you shake your head and quietly say “how sad,” for gossip at high school reunions over margaritas. It is for elderly people whose days have stretched out so long and thin that at last they call for him and he answers. Other people die, but not me. My world is too vivid, too complex, too loud, a kaleidoscope of memories, and there is too much of it for death to hold in his hands. It would be like turning out the lights on an entire universe all at once. I cannot end. I have barely even begun.

I take a breath and it goes deeper this time, brings feeling back into my fingertips and toes. The Monarch, or maybe God, or the universe (maybe they’re all one in the same) has made a mistake. But I built this god, so I can fix it.

I sit back down at my desk and open up a new tab.

I copy Sabrina’s profile into the sandbox, crack my neck, and rewrite the past.

First, I delete the line where Sabrina’s umbrella has one broken rib.

Instantly, the screen explodes with error messages. The umbrella rib had to break, because that in and of itself was its own inevitable conclusion, preceded by a thousand other events that had already steered fate in that direction. I hit cancel, ignore, proceed until all the messages are gone, and the fans in my computer start whirring with the great effort of changing the past.

It takes much longer this time. My computer grows alarmingly warm, my basement-turned-office like a windstorm with all the fans spinning furiously. I wait and wait and after ten minutes I’m pulled back by the quiet ding of the Monarch completing its task.

But I didn’t specify a time period. So, faster than I can stop it, the Monarch begins to predict the rest of Sabrina Choi’s life.

Sabrina Choi walks to the train station in the rain —> The station is shut down because of an accident at the station, so she takes a taxi to work —> Sabrina Choi works for 4.5 hours at Clement’s Coffee —> Sabrina Choi eats lunch on a park bench—> Sabrina Choi works for 3.5 hours at Clement’s Coffee —> Sabrina Choi takes the train home.

With that one broken umbrella rib gone, that day forever altered, the life of Sabrina Choi begins to change. She goes to her gen ed classes and memorizes the answers for her tests and gets good grades but doesn’t care about any of it, doesn’t see why anything matters at all. She takes a semester off and comes back home to Saglo, buys a keyboard and plays it in her room with headphones on, and her parents hate the sound of keys slamming down all night, and they fight about it and Sabrina cries but they love her so they let it be.

She runs into Elsie Chen at a coffee shop in the summer, and they sit on the pier and talk about college even though Sabrina knows she’s never going back, even though Elsie doesn’t want to but knows she will anyway. It is the first time they spend time together in public.

Sabrina gets a job at the local ice cream shop and goes to therapy, and her parents let her get a dog—a Shiba Inu mix named Button, and Sabrina buys a pair of roller skates and runs with her dog around the town, feeds him blueberries by the shore.

And the next summer, Elsie comes back and they walk Button together along the docks, and Sabrina holds Elsie’s hand and she doesn’t know why at first, but she doesn’t want to let go, all she knows is that being with Elsie makes the TV static in her mind quieter, lets her hear the sounds of waves on the dock, birds overhead.

They move in together after Elsie graduates, one town over from Saglo, a small apartment with windows facing south, drinking up sunlight. Elsie cycles through jobs, changes careers twice, and Sabrina teaches piano, and at night she plays songs that only Elsie is allowed to hear, songs just for her.

And slowly, they start to build a dream. It is not a destination, a fixed point on the horizon that so many people chase after. It is a series of moments that slowly bring the dream into being—the way the dew smells through the kitchen window on summer mornings, the way Sabrina’s face creases with a smile when she watches TV and forgets that she’s a part of the world, the way Elsie has learned over a series of months and then years to make coffee at exactly the right temperature, the perfect mix of cream and sugar, and that first sip is always the beginning of a good day. And if you asked them what their dreams were, they couldn’t tell you, but slowly they begin to feel as though they’re already there.

It is a nice story, but it will never happen.

Because of one broken umbrella rib.

My desk is sticky from spilled coffee and my socks have holes in them and I’m a twenty-eight-year-old with no money in her mom’s basement and Sabrina Choi is dead. The Monarch is still writing our story, so I slam the space bar and it grinds to a halt when we reach the age of seventy-four.

I stand up even though my legs feel like they won’t hold me. I walk up the stairs, past my mom who asks me a question I don’t hear, out the door.

I am walking through this town where I have always lived, to the cemetery I only visit in secret, and then I’m standing at her grave. It feels rude to show up here empty handed, but I have nothing to give her, nothing that would matter.

“You should have told me,” I whisper. “You should have just fucking told me what you wanted.”

And I don’t miss her, not really, but I miss everything she could have been. I miss something that never happened because of a broken umbrella rib, and everything that hurts me now is nothing but a daydream of an AI too smart for its own good.

The last time I ever spoke to him, Professor Pérez warned me that this might happen. 

“I worry you’re seeking an answer that doesn’t exist,” he said. And even then, I sensed from the darkness under his eyes, the delicate way he held the handle of his empty coffee cup, that this was a goodbye. Maybe I’d been around the Monarch so long that we’d started to become one, and I’d started to sense the inevitable truth of everything. Algorithms are extensions of their creators, after all.

“I know that it’s unfair,” he said. “I know that it’s unlikely. But there are eight billion people on this planet, and this isn’t even the only universe. In all the histories of every world, there are some high school classes where every student dies, and some where all of them live forever. It’s a statistical inevitability.”

“Do you really believe that?” I said. “That we’re just the sentient equivalent of flimsy plastic straws? That all of us are truly that worthless?”

“Worthless?” Professor Pérez echoed, as if he’d never heard the word before. One of his overhead lights flickered and died, but he seemed not to notice. “On the contrary. All of us exist, against all odds, even if only briefly. I think that makes us extraordinary.”

I leave the cemetery an hour later. The afternoon is unfairly beautiful, the sky impossibly clear. I think that maybe I’ll go home and sell the Monarch. I’m sure it can be monetized in some way, used to sell people sunset lamps or everything bagel spice or something equally meaningless.

Or maybe I’ll just stop updating it, let it rot as corpses do, grow old and obsolete, die just like Sabrina. I know that I can’t look at it anymore, because it sees me here, at Sabrina’s grave, and it will log another event into my file, just another data point that can never be changed:

On March 11th, 2025, Elsie Chen dreamed about a life she would never have with a girl that she never could have saved. The Monarch could tell her the inevitable conclusion of such a pointless act, but Elsie would not ask it. Because even that dream was just the product of another inevitable conclusion, spawned by another Point of No Return that had long since been decided for her. In thirty-five days she would, inevitably, discover the bug in her program that prevented it from predicting her own death, but she would not fix it, would not run the simulation. Because she knew that her life—all of their lives—were only kites ripped away by the wind, tails lashing their hands, spiraling up and up towards a distant sun.

 

(Editors’ Note: Kylie Lee Baker is interviewed by Caroline M. Yoachim in this issue.)

© 2023 Kylie Lee Baker