The emergence of humanoid robots in the workplace has raised critical questions about AI bias and discrimination. Tesla's Optimus robot, designed to perform various tasks alongside humans, has come under scrutiny for potentially exhibiting gender-biased behaviors in its interactions and task assignments.

This investigation examines the evidence behind these claims, exploring how machine learning algorithms can inadvertently perpetuate societal biases present in their training data. As companies like Tesla push forward with AI-powered robotics, the importance of addressing algorithmic fairness becomes paramount to ensure equitable treatment across all demographics in future automated workplaces.