DISSECTING ALGORITHMIC BIAS IN ONLINE MENTAL HEALTH RESOURCES

The virtual landscape is rapidly evolving to provide mental health assistance. However, these tools often rely algorithms that can reinforce existing societal biases. This raises a serious threat as users seeking support may encounter discriminatory outcomes based on their ethnicity, gender, or other protected characteristics. It is vital to unpack

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