Takeshi stared at the email on his screen. "You're asking the right questions. Be careful who you trust." The sender's address was an anonymous placeholder, nothing traceable. He resisted the urge to reply. If this was a prank, he didn't want to entertain it. If it was real, responding might be a mistake. Either way, it left an unsettling feeling in his gut.
He closed the email and turned back to his work. There were more pressing matters to focus on.
The next morning, Takeshi logged into the hospital's research database, only to find an unexpected notification: Access to certain datasets has been temporarily restricted.
He frowned. The algorithm's training files—the ones he had been analyzing—were no longer accessible. Instead, a generic message appeared: "Due to upcoming conference preparations, certain datasets are temporarily locked for security reasons."
Hiro, who was sitting nearby, leaned over. "You too?"
Takeshi nodded. "Yeah. You?"
Hiro pulled up his screen. "Nope. I can still access most of it."
Takeshi exhaled slowly. This wasn't a total lockout. It was subtle. Just enough to slow him down.
He decided to check with IT, keeping his tone neutral. A technician gave him a half-hearted explanation. "It's standard protocol before big presentations. We don't want people making last-minute changes that could cause inconsistencies."
That sounded logical, but Takeshi knew better. The restrictions were targeted—only affecting specific parts of the data. Someone didn't want additional scrutiny before the conference.
Back in the office, Dr. Saito didn't look surprised when he told her.
"This was bound to happen," she said, rubbing her temple. "They don't want distractions before the conference. We're days away, and they don't want any unnecessary 'complications'."
"You mean they don't want us uncovering more problems," Takeshi said.
Dr. Saito gave him a measured look. "You're not wrong. But the hospital sees it differently. In their eyes, the AI is functional. They want to present it with confidence. If they allow last-minute investigations, it could derail months of work."
Takeshi felt a flash of frustration. "So we just let it slide?"
"I didn't say that." She leaned forward. "I'm saying pick your battles. If you push too hard now, they'll sideline you entirely. Keep looking into it, but don't make it obvious."
Takeshi nodded, understanding. He wasn't being told to stop—just to be careful.
Without full database access, Takeshi and Hiro worked with older backups. It was slower, but it allowed them to keep investigating without raising alarms. As Takeshi sifted through older datasets, something caught his eye—a small discrepancy in the time stamps of certain data entries.
Hiro peered over his shoulder. "What are you seeing?"
"These changes," Takeshi said, pointing at a cluster of modified entries. "Look at the timing. These adjustments weren't made gradually—they happened all at once. Right before a major project review."
Hiro whistled. "So someone cleaned up the data before showing it to the hospital board?"
"Looks that way," Takeshi said. "But the question is—who?"
That evening, just as Takeshi was about to pack up, a report buried in the archives caught his attention. It was an old email thread from months ago—before he had even joined the project. Someone had flagged concerns about data inconsistencies before.
But their concerns had been dismissed.
He scrolled through the thread, his pulse quickening. The responses were vague, deflecting the issue. The person raising the concern was told that "the model's results remain statistically sound, and further scrutiny is unnecessary."
Takeshi frowned. Someone else saw this problem before him. And they were ignored.
He glanced around the empty office, feeling the weight of the discovery.
He wasn't the first one to question the algorithm.
But if the hospital had ignored it once, what were the chances they'd listen now?
YOU ARE READING
The Algorithm
Short StoryIn a cutting-edge hospital known for its advancements in medical research, Takeshi, a postdoc in data science, is given the responsibility of validating a groundbreaking AI algorithm designed to detect early-stage pancreatic cancer. The algorithm is...
