After she leaves, I sit with that truth. Three years of perfect grades in every technical class.
Three years of building toward Jenkins' lab, toward proving I belong in AI research despite what Miles made me believe about my emotional limitations.
All of it hanging on learning how to tell a stupid story.
Forty-five minutes later,I’m at Buddha Bowl with Riya and Declan, stabbing at my pad Thai like it personally offended me. The restaurant hums with student chatter, but I barely hear it over the algorithm spinning in my head.
“You’re doing the thing,” Riya observes, dipping a spring roll. “The scary focused face.”
“I’m eating.”
“You’re plotting,” Declan corrects. He’s visiting from Boston again—MIT’s spring break started early. With his wire-rimmed glasses and band t-shirt, he looks like every CS major’s final evolution. “She gets the same look when she’s coding.”
“Speaking of.” Riya steals a piece of my tofu. “How’s Match-y coming?”
“ClearMatch,” I correct automatically. “And it’s... coming.”
Declan leans forward, genuinely interested. He’s good like that—actually listens when people talk about their work. “Remind me how it works? You’re claiming this algorithm can find perfect romantic matches?”
“Not claiming. Proving.” I set down my chopsticks, warming to the topic. “Humans are statistically terrible at choosing partners. You know what percentage of marriages end in divorce?”
“I dunno, twenty-something percent?”
“Forty-one to fifty, depending on demographics. And that’s just the ones that actually end. Doesn’t count the miserable ones that limp along.” I pull out my phone, show him the stats I keep bookmarked. “We let emotions override logic. Get distracted by chemistry, ignore fundamental incompatibilities.”
“Romance is dead,” Riya says dryly.
“Romance is inefficient,” I counter. “We see someone attractive, our brains flood with dopamine and norepinephrine, and suddenly we’re ignoring red flags because they smell nice or laugh at our jokes.”
Declan grins. “You’re really selling the human experience here.”
“I’m being realistic. Computers don’t have hormones. They can analyze compatibility metrics without bias—shared values, communication styles, life goals, behavioral patterns.” I tick them off on my fingers. “Remove emotion from the equation and you get better outcomes.”
“So you’re saying feelings are the problem?”
“Feelings are like…noise in the data. They distract us, stop us from seeing the full picture.”
Riya and Declan exchange a look—one of those couple telepathy moments that I’ve never experienced.
“Okay,” Declan says slowly. “So run us through the app. Hypothetically.”
I light up. “Users input baseline data—age, location, education. Then deeper metrics—career goals, lifestyle preferences, conflict resolution styles. The algorithm weighs compatible traits against complementary ones?—”
“Wait.” He holds up a hand. “Test it on us.”
“What?”
“Me and Riya. According to your algorithm, are we a good match?”
Riya snorts. “This should be good.”
I don’t reveal that I have actually used them previously asa case study for my own testing. I had to guess a couple of answers but I think I got pretty close.
“Alright.” I hand Declan my phone. “Input your answers first, then Riya would do the same. This is still the BETA version so ignore the ugly UI. We’ll do the quick version. I’m also creating an in-depth version which takes much longer to fill out but this will give you a vague idea of what the app thinks.”
After a couple minutes of them selecting answers, the compatibility is revealed.
“Only 87?” Riya looks mock-offended.
