EXAMINING ALGORITHMIC BIAS IN ONLINE MENTAL HEALTH RESOURCES

The digital landscape is rapidly evolving to offer mental health resources. However, these systems often depend on algorithms that can reinforce existing societal biases. This presents a serious threat as users seeking aid may encounter prejudiced outcomes based on their background, identity, or other protected characteristics. It is vital to unpac

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