DISSECTING ALGORITHMIC BIAS IN ONLINE MENTAL HEALTH RESOURCES

The online landscape is rapidly evolving to deliver mental health assistance. However, these systems often utilize algorithms that can propagate existing societal biases. This raises a serious threat as users seeking help may encounter prejudiced outcomes based on their ethnicity, sex, or other sensitive attributes. It is essential to deconstruct t

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