EXAMINING ALGORITHMIC BIAS IN ONLINE MENTAL HEALTH RESOURCES

The virtual landscape is rapidly evolving to deliver mental health support. However, these systems often rely algorithms that can propagate existing societal biases. This presents a serious issue as users seeking help may encounter prejudiced outcomes based on their ethnicity, gender, or other personal traits. It is vital to unpack these inequaliti

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