DISSECTING ALGORITHMIC BIAS IN ONLINE MENTAL HEALTH RESOURCES

The online landscape is rapidly evolving to offer mental health support. However, these systems often rely algorithms that can perpetuate existing societal biases. This poses a serious issue as users seeking support may encounter prejudiced outcomes based on their ethnicity, gender, or other personal traits. It is essential to analyze these dispari

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