DISSECTING ALGORITHMIC BIAS IN ONLINE MENTAL HEALTH RESOURCES

The online landscape is rapidly evolving to provide mental health support. However, these systems often rely algorithms that can propagate existing societal biases. This poses a serious concern as people seeking support may encounter prejudiced outcomes based on their ethnicity, sex, or other personal traits. It is essential to analyze these inequa

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