Adding voice to language models doesn't just extend text capabilities—it introduces new bias mechanisms tied to speaker identity cues that amplify discrimination beyond text-only versions, requiring fairness safeguards alongside accessibility improvements.
Voice interfaces on AI chatbots amplify gender discrimination more than text-based versions because speech reveals speaker identity through tone and accent. The research shows these models shift toward gender-stereotyped responses based on voice alone, and surveys reveal users worry about hidden attribute inference.