Empowering Workers through AI

1. Culturally – Aware Work Tools

This project draws directly on culture theory and chronemics (studying how different cultures treat time) to build an AI tool that adapts to workers’ cultural and temporal work-styles. It follows the model presented in our CSCW paper which distinguished “monochronic” vs “polychronic” work preferences and found that tailoring interfaces accordingly can boost earnings by over 250% for polychronic workers.
Key features

• The system asks workers about their cultural time-preferences (e.g., do they prefer individual focus, structured schedules, or simultaneous multitasking and social interaction?).
• The AI then customises notifications, work-recommendations, and task timing to match those preferences. For example:
  • For “monochronic” workers (who prefer sequential, scheduled tasks) the tool sends alerts only when they are ready and minimizes multi-tasking distractions. 
  • For “polychronic” workers (who prefer multitasking, interleaved tasks and social engagement) the tool sends opportunistic notifications while they are engaged in other activities, supports flexible scheduling and context-switching. 
• By shifting adaptation burdens from the worker to the interface, the tool helps workers from diverse cultural backgrounds to succeed without forced assimilation into a one-size-fits-all model.
• The design is participatory: workers from different cultural communities co-design the interface, define metrics of success (beyond wage to include well-being, schedule control, work-life fit) and help train the AI on diverse work-style signals.

The goal is to build a culturally aware recommendation and scheduling AI system that adapts to lived experience, not just skills or language—so that cultural resources and time-styles become part of how workers are supported and matched.