Robotic Bias and Its Dimensions

Bias in algorithmic systems is well documented, but the growing deployment of social robots in workplaces, homes, and public spaces poses a distinct challenge: their physical embodiment and social presence make bias visible in appearance, tangible in interaction, and consequential in everyday inclusion. This paper proposes a framework for understanding robotic bias across three dimensions - stereotypes, constraints, and treatments. The framework clarifies how different forms of bias emerge through embodiment and interaction, and highlights why they call for different strategies of intervention. In doing so, it provides a foundation for more systematic recognition and mitigation of bias in human-robot interaction.