EXAMINING ALGORITHMIC BIAS IN ONLINE MENTAL HEALTH RESOURCES

The virtual landscape is rapidly evolving to deliver mental health resources. However, these platforms often depend on algorithms that can propagate existing societal biases. This poses a serious concern as users seeking aid may encounter discriminatory outcomes based on their ethnicity, gender, or other sensitive attributes. It is crucial to decon

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