UNPACKING ALGORITHMIC BIAS IN ONLINE MENTAL HEALTH RESOURCES

The online landscape is rapidly evolving to provide mental health support. However, these platforms often utilize algorithms that can reinforce existing societal biases. This poses a serious issue as users seeking support may encounter prejudiced outcomes based on their race, sex, or other sensitive attributes. It is essential to analyze these bias

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