EXAMINING ALGORITHMIC BIAS IN ONLINE MENTAL HEALTH RESOURCES

The online landscape is rapidly evolving to provide mental health assistance. However, these platforms often depend on algorithms that can reinforce existing societal biases. This poses a serious concern as users seeking help may encounter unfair outcomes based on their ethnicity, sex, or other protected characteristics. It is crucial to unpack the

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