Sketchy Imbalances In Data Training Are Distorting AI-Generated Mental Health Guidance
Generative AI models, particularly those used for mental health advice, suffer from significant data imbalances during training. These models are trained on vast internet datasets that are disproportionately skewed towards common topics, leading to an underrepresentation of rarer or more nuanced information. Consequently, the AI may provide advice that is ill-suited or even harmful, as users are often unaware of these inherent biases and assume the AI's guidance is comprehensive and authoritative. AI
IMPACT Skewed training data in AI models could lead to inappropriate or harmful mental health advice, highlighting the need for better data curation and user awareness.