EXAMINING ALGORITHMIC BIAS IN ONLINE MENTAL HEALTH RESOURCES

The virtual landscape is rapidly evolving to offer mental health assistance. However, these tools often rely algorithms that can propagate existing societal biases. This raises a serious concern as individuals seeking aid may encounter discriminatory outcomes based on their ethnicity, sex, or other personal traits. It is crucial to unpack these ine

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