EXAMINING ALGORITHMIC BIAS IN ONLINE MENTAL HEALTH RESOURCES

The online landscape is rapidly evolving to offer mental health resources. However, these systems often depend on algorithms that can reinforce existing societal biases. This presents a serious threat as users seeking support may encounter discriminatory outcomes based on their race, sex, or other personal traits. It is vital to analyze these biase

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