EXAMINING ALGORITHMIC BIAS IN ONLINE MENTAL HEALTH RESOURCES

The virtual landscape is rapidly evolving to provide mental health resources. However, these tools often rely algorithms that can perpetuate existing societal biases. This raises a serious concern as users seeking help may encounter discriminatory outcomes based on their ethnicity, identity, or other protected characteristics. It is crucial to unpa

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