UNPACKING ALGORITHMIC BIAS IN ONLINE MENTAL HEALTH RESOURCES

The virtual landscape is rapidly evolving to provide mental health resources. However, these platforms often rely algorithms that can perpetuate existing societal biases. This presents a serious threat as individuals seeking support may encounter prejudiced outcomes based on their race, sex, or other sensitive attributes. It is essential to analyze

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