EXAMINING ALGORITHMIC BIAS IN ONLINE MENTAL HEALTH RESOURCES

The online landscape is rapidly evolving to provide mental health support. However, these tools often depend on algorithms that can reinforce existing societal biases. This poses a serious threat as people seeking aid may encounter unfair outcomes based on their background, gender, or other personal traits. It is crucial to analyze these inequaliti

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