EXAMINING ALGORITHMIC BIAS IN ONLINE MENTAL HEALTH RESOURCES

The digital landscape is rapidly evolving to provide mental health assistance. However, these systems often depend on algorithms that can perpetuate existing societal biases. This poses a serious concern as users seeking aid may encounter prejudiced outcomes based on their race, identity, or other sensitive attributes. It is essential to unpack the

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