UNPACKING ALGORITHMIC BIAS IN ONLINE MENTAL HEALTH RESOURCES

The online landscape is rapidly evolving to deliver mental health resources. However, these tools often rely algorithms that can propagate existing societal biases. This poses a serious concern as users seeking help may encounter prejudiced outcomes based on their race, gender, or other protected characteristics. It is crucial to analyze these disp

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