EXAMINING ALGORITHMIC BIAS IN ONLINE MENTAL HEALTH RESOURCES

The virtual landscape is rapidly evolving to offer mental health assistance. However, these platforms often depend on algorithms that can reinforce existing societal biases. This poses a serious concern as users seeking support may encounter discriminatory outcomes based on their race, sex, or other protected characteristics. It is crucial to unpac

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