The Algorithm

Chapter 4: A Chain of Choices

Takeshi stood in Dr. Saito's office, the printout of mislabeled data resting between them. The weight of his discovery sat heavy on his shoulders, but Dr. Saito's expression was unreadable. She flipped through the pages, scanning the figures with sharp, practiced eyes. When she finally spoke, her voice was measured.

"This is serious," she said, setting the papers down. "But Takeshi, do you realize what this means?"

Takeshi straightened. "It means the algorithm's results aren't entirely reliable. If we don't address this, we could be sending out an AI that's flawed at its core."

Dr. Saito exhaled slowly, pinching the bridge of her nose. "I'm not saying you're wrong. But we're days away from the conference. If we push forward with this investigation now, we risk missing our submission deadline entirely."

Takeshi hesitated. He had been so focused on uncovering the truth that he hadn't fully considered the timing. The conference was critical—not just for the hospital's reputation but for funding, future projects, and the careers of everyone on the team. A delay could mean years of setbacks.

"But if we present it as is," Takeshi countered, "we're putting out a flawed system. We're telling the world it's ready when it isn't."

Dr. Saito sighed. "I agree with you. But this isn't just about ethics—it's about strategy. If we delay now, it might not just be the conference we miss. The funding associated with it could disappear too. And if that happens, there might not be a next phase to fix anything."

Takeshi felt a tight knot in his chest. She wasn't wrong. The hospital's research grants were often tied to milestone-based achievements. No milestone, no funding.

"So what do we do?" Takeshi asked, frustration creeping into his voice. "Just ignore the issue?"

Dr. Saito shook her head. "Not necessarily. There may be a middle ground."

Takeshi folded his arms. "Such as?"

"We present the algorithm at the conference as planned but acknowledge its limitations," she said. "We highlight what it does well and be transparent about the areas that need further improvement. That way, we maintain credibility and don't risk losing momentum."

Takeshi frowned. "And then what? Do we actually fix it, or does it just become another 'we'll handle it later' situation?"

Dr. Saito met his gaze. "That depends on us."

Takeshi left the office with his mind racing. He had thought his job was simply to validate the model, but now he was being pulled into the larger realities of academia and funding—where compromises were sometimes necessary for survival.

He returned to his desk, staring at the lines of code and patient records on his screen. His gut told him the issue wasn't just a minor flaw—it was significant enough that rushing ahead could put real patients at risk.

But if he pushed too hard, if he insisted they stop everything, what would happen to the research? Would the hospital really choose integrity over funding? And if they didn't present at the conference, would this algorithm ever get the improvements it needed, or would the entire project be shelved?

The thought sent a chill down his spine.

"Still here?" a familiar voice broke his thoughts. Takeshi turned to see Hiro, one of the senior engineers, leaning against the cubicle wall. "Saito told me you found something big."

Takeshi nodded, rubbing the back of his neck. "Yeah. But it's complicated. If we fix it now, we might miss the conference."

Hiro whistled. "That's a tough one. The hospital's been banking on this presentation. But if the data's bad..." he shrugged. "You sure we can't patch it up in time?"

Takeshi hesitated. Could he? The idea had been floating in the back of his mind since leaving Saito's office. Maybe there was a way to make rapid adjustments, at least enough to mitigate the most egregious issues before the conference.

"I need to run one last test," Takeshi said, feeling a renewed urgency. "If I can prove whether the flaws are fixable in time, we'll know what to do."

Hiro nodded. "I'll stay and help. Let's figure this out."

Hours later, as the office grew quieter and the night deepened, Takeshi ran his final test. The algorithm processed the dataset, numbers flashing across the screen. The results took longer than usual. He and Hiro watched in silence, waiting.

Then, finally, the numbers settled. Takeshi leaned in, scanning the output. His breath caught.

The error rates weren't just worse than before—they were catastrophic.

Something deeper was wrong with the model, something they hadn't yet uncovered. The flaws weren't just a byproduct of bad training data. The algorithm itself had fundamental issues.

Takeshi stared at the screen, Hiro muttering a quiet curse beside him.

Missing the conference might be the least of their problems.