DISSECTING ALGORITHMIC BIAS IN ONLINE MENTAL HEALTH RESOURCES

The virtual landscape is rapidly evolving to offer mental health resources. However, these tools often rely algorithms that can propagate existing societal biases. This raises a serious issue as users seeking support may encounter prejudiced outcomes based on their ethnicity, identity, or other sensitive attributes. It is essential to deconstruct t

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