DISSECTING ALGORITHMIC BIAS IN ONLINE MENTAL HEALTH RESOURCES

The virtual landscape is rapidly evolving to deliver mental health assistance. However, these systems often rely algorithms that can reinforce existing societal biases. This poses a serious concern as users seeking support may encounter unfair outcomes based on their ethnicity, sex, or other sensitive attributes. It is crucial to unpack these biase

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