The race to develop advanced humanoid robots has quietly created a new class of precarious digital workers. In Nigeria and other developing nations, gig workers like Zeus, a medical student juggling hospital shifts with remote work, are training AI systems by recording themselves performing physical movements and actions. Using nothing more than a smartphone mounted to their forehead and a ring light, these workers provide the motion data and behavioral examples that teach humanoid robots how to move and interact in the real world. This distributed training model allows companies to rapidly scale data collection while minimizing direct employment relationships and associated labor protections.