DISSECTING ALGORITHMIC BIAS IN ONLINE MENTAL HEALTH RESOURCES

The online landscape is rapidly evolving to offer mental health resources. However, these platforms often rely algorithms that can propagate existing societal biases. This raises a serious issue as users seeking aid may encounter prejudiced outcomes based on their ethnicity, identity, or other protected characteristics. It is essential to analyze t

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