DISSECTING ALGORITHMIC BIAS IN ONLINE MENTAL HEALTH RESOURCES

The virtual landscape is rapidly evolving to deliver mental health assistance. However, these platforms often depend on algorithms that can propagate existing societal biases. This raises a serious threat as people seeking help may encounter prejudiced outcomes based on their race, sex, or other protected characteristics. It is essential to analyze

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