DISSECTING ALGORITHMIC BIAS IN ONLINE MENTAL HEALTH RESOURCES

The virtual landscape is rapidly evolving to deliver mental health assistance. However, these platforms often depend on algorithms that can propagate existing societal biases. This poses a serious issue as users seeking support may encounter prejudiced outcomes based on their ethnicity, sex, or other sensitive attributes. It is vital to unpack thes

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