UNPACKING ALGORITHMIC BIAS IN ONLINE MENTAL HEALTH RESOURCES

The digital landscape is rapidly evolving to deliver mental health assistance. However, these systems often utilize algorithms that can propagate existing societal biases. This presents a serious threat as users seeking help may encounter unfair outcomes based on their ethnicity, gender, or other sensitive attributes. It is crucial to analyze these

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