I got paid minimum wage to solve an impossible problem.

A computer science student turned a supermarket floor sweeping job into an optimization problem using simulated annealing and the traveling salesman problem. The initial solution minimized distance but created an impractical path with excessive turns. Adding a turn penalty to the cost function produced a more realistic, human-friendly route. This experiment illustrates how optimizing for easily measurable metrics (distance, engagement, profit) instead of actual goals (usability, wellbeing, sustainability) leads to technically correct but practically useless or harmful outcomes in algorithms, social media, AI, and business.