EXAMINING ALGORITHMIC BIAS IN ONLINE MENTAL HEALTH RESOURCES

The online landscape is rapidly evolving to offer mental health resources. However, these tools often rely algorithms that can perpetuate existing societal biases. This presents a serious threat as people seeking aid may encounter unfair outcomes based on their background, identity, or other sensitive attributes. It is vital to analyze these biases

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