UNPACKING ALGORITHMIC BIAS IN ONLINE MENTAL HEALTH RESOURCES

The online landscape is rapidly evolving to provide mental health support. However, these systems often rely algorithms that can perpetuate existing societal biases. This poses a serious threat as users seeking help may encounter discriminatory outcomes based on their race, gender, or other protected characteristics. It is essential to analyze thes

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