Episode 32 of AI Ethics with Fexingo examines the unregulated world of AI-powered mental health chatbots. Lucas and Luna discuss a recent study finding that popular therapy AIs exhibit racial and socioeconomic bias in their responses. They dive into the case of a chatbot that recommended different coping strategies based on a user's implied income level, and explore why these systems lack clinical validation. The hosts question whether these tools could do more harm than good for vulnerable users, and what ethical obligations developers have. Specific examples include a 2025 analysis of five leading chatbots by the Digital Wellness Lab, which found that lower-income users were 40% more likely to receive advice to 'accept your situation' versus actionable steps. The episode calls for transparency and regulatory oversight before AI therapists scale further.

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