EXAMINING ALGORITHMIC BIAS IN ONLINE MENTAL HEALTH RESOURCES

The virtual landscape is rapidly evolving to deliver mental health resources. However, these systems often rely algorithms that can propagate existing societal biases. This presents a serious threat as people seeking support may encounter discriminatory outcomes based on their race, gender, or other personal traits. It is essential to unpack these

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