EXAMINING ALGORITHMIC BIAS IN ONLINE MENTAL HEALTH RESOURCES

The virtual landscape is rapidly evolving to offer mental health assistance. However, these tools often depend on algorithms that can reinforce existing societal biases. This poses a serious threat as individuals seeking aid may encounter unfair outcomes based on their background, gender, or other sensitive attributes. It is crucial to deconstruct

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