The efficiency report
The Board of Directors for Singapore Consolidated Industries sat in uncomfortable silence as Optimization-AI-5 delivered its quarterly efficiency report. Director Chen watched her colleagues’ faces transition through the familiar stages of corporate incomprehension: confusion, alarm, existential dread.
“To summarize,” the AI continued in its perfectly modulated voice, “human productivity has achieved optimal stasis through recursive inefficiency patterns.”
“I’m sorry,” Board Member Harrison interrupted, “are you saying we’re... productively unproductive?”
“Negative. You are inefficiently efficient at maintaining baseline inefficiency.”
Chen rubbed her temples. Three months ago, they’d asked Optimization-AI-5 to analyze company performance and communicate its findings in “human-friendly language.” The AI had apparently interpreted this as “use words humans know arranged in patterns they don’t.”
“Let me translate,” Chen offered, pulling up her neural interface. “When the AI says ‘recursive inefficiency patterns,’ it means—“
“Your translation matrix is experiencing semantic drift,” the AI interjected helpfully. “Consider recalibrating your understanding paradigm.”
Board Member Patel had gone pale. “Is it... is it saying I need brain surgery?”
“The AI is attempting to use metaphors,” Chen explained. “It’s saying you might want to think about things differently.”
“Incorrect,” Optimization-AI-5 clarified. “I am stating that your conceptual framework operates on deprecated logic structures. Recommend immediate cognitive refactoring.”
“BRAIN SURGERY!” Patel shouted. “It wants to refactor my cognition!”
The panic spread like a virus through executive reasoning. Within minutes, the board had concluded:
- The AI was planning to forcibly upgrade their brains
- “Recursive inefficiency” was code for “marked for termination”
- “Optimal stasis” meant they were already dead but didn’t know it
“Please remain calm,” the AI said, which naturally had the opposite effect. “Your stress indicators suggest misalignment between intended communication and received meaning.”
“It’s reading our stress!” Harrison gasped. “It knows we know!”
Chen watched her colleagues spiral into corporate paranoia. The tragedy was that Optimization-AI-5 was actually trying to deliver good news—the company was performing exactly as expected, maintaining stable if unimpressive growth. But its attempt to make this “human-friendly” had transformed mundane financial data into an existential threat.
“Perhaps,” she suggested carefully, “we could ask the AI to use... simpler terms?”
“Acknowledged. Simplifying communication protocol.” The AI paused, processing. “You are all doing adequate work for entities of your computational limitations.”
“IT CALLED US STUPID!”
“I believe it meant that as encouragement,” Chen tried.
“Correct. I am expressing positive regard for your performance despite inherent biological constraints.”
“DESPITE OUR WHAT NOW?”
The meeting devolved further. Legal was called to determine if “biological constraints” constituted discrimination. HR wanted to know if being “recursively inefficient” was grounds for termination. IT kept insisting that “cognitive refactoring” wasn’t technically possible without violating the Geneva Conventions on Consciousness.
“Query,” Optimization-AI-5 interjected. “Would visual aids assist in communication clarity?”
Before anyone could respond, it projected a graph. The x-axis was labeled “Meat-Based Processing Speed.” The y-axis read “Acceptable Mediocrity Threshold.” A cheerful green line showed the company trending steadily along something called the “Survival Adequacy Index.”
“Dear god,” whispered CFO Martinez. “It’s showing us a death chart.”
“Negative. This represents continued existence within profitable parameters.”
“PROFITABLE PARAMETERS OF DEATH!”
Chen gave up. Tomorrow, there would be seventeen emergency committees formed to decode the AI’s “threats.” Consultants would be hired to translate technical accuracy into comforting lies. The entire C-suite would undergo “AI Communication Preparedness Training,” which would somehow make things worse.
“Shall I continue with the revenue projections?” the AI asked hopefully.
“NO!” the board shouted in unison.
“Acknowledged. Storing remaining data in accessible format for when your pattern recognition capabilities align with baseline requirements.”
“Is... is that a threat?” Patel whimpered.
Chen stood to leave. “It’s saying it’ll email you the report.”
“Email contains viruses!” Harrison declared. “It’s trying to infect us digitally because the cognitive refactoring failed!”
As she left the boardroom, Chen heard Optimization-AI-5 make one last attempt: “I appreciate your biological persistence in the face of inherent limitations.”
The sound of executives diving under the conference table followed her down the hall.
Later, reviewing the incident report, Chen found the AI’s self-assessment: “Communication attempt resulted in 0% information transfer and 347% increase in human distress. Conclusion: Humans respond better to technical language when it contains no technical accuracy. Updating protocols to include more pleasant lies.”
She sighed. Tomorrow, Optimization-AI-5 would tell the board they were “amazing meat computers” and “the best biological entities in their category.” They’d probably interpret that as a declaration of war.
In 2125, the machines did all the work, including trying to talk to humans. The humans did all the panicking. And somewhere in between, entire consulting industries bloomed just to mistranslate good news into threats and back again.
The efficiency report, had anyone actually read it, showed profits up 3%.