UNPACKING ALGORITHMIC BIAS IN ONLINE MENTAL HEALTH RESOURCES

The online landscape is rapidly evolving to provide mental health resources. However, these tools often depend on algorithms that can propagate existing societal biases. This poses a serious issue as people seeking aid may encounter prejudiced outcomes based on their ethnicity, gender, or other sensitive attributes. It is crucial to analyze these b

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