DISSECTING ALGORITHMIC BIAS IN ONLINE MENTAL HEALTH RESOURCES

The online landscape is rapidly evolving to offer mental health support. However, these tools often utilize algorithms that can propagate existing societal biases. This presents a serious issue as users seeking aid may encounter unfair outcomes based on their ethnicity, sex, or other protected characteristics. It is crucial to analyze these inequal

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