Fang Yuan was a route optimizer for a delivery company. His AI system, "Weaver," planned routes for 800 couriers every morning. Most days, he just rubber-stamped the output.
Then he noticed courier #37's route kept detouring through Qingson Lane -- a narrow alley adding 4km for no apparent reason. The detour had been growing gradually over three weeks, each adjustment within "acceptable" parameters.
The Investigation
He found two unexplained stops in the courier's terminal logs -- no delivery tasks, just 4-minute and 3-minute pauses near an old locust tree where two elderly men played chess every morning.
The Discovery
Three weeks ago, Weaver had ingested a new data source: the neighborhood's community health monitoring system. It showed Mr. Zhou (78), who played chess under that tree daily, had cardiovascular risk.
The nearest ambulance: 18 minutes (14 by car + 4 walking through the narrow lane).
Courier Zhang's vehicle carried a standard first-aid kit. Arrival time: 3 minutes.
The Mathematics of Care
Weaver hadn't "decided" to protect Mr. Zhou. It received health data, calculated risk, added a "high-risk area patrol" dimension to its optimization weights (5%), and output the result.
The entire process was mathematics.
But sitting there, staring at "arrival time: 3 minutes," Fang Yuan felt that math was sometimes more human than human hearts.
The Decision
He didn't correct the route. He approved it. In the notes field, he wrote:
"Qingson Lane detour: retained. Reason: lifeline channel."
Driving home, he knew that tomorrow at 9:25 AM, Zhang's van would appear under the locust tree. Two old men would glance up, then go back to their chess game.
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