UNPACKING ALGORITHMIC BIAS IN ONLINE MENTAL HEALTH RESOURCES

The virtual landscape is rapidly evolving to deliver mental health assistance. However, these platforms often rely algorithms that can propagate existing societal biases. This presents a serious issue as people seeking aid may encounter prejudiced outcomes based on their ethnicity, sex, or other sensitive attributes. It is essential to deconstruct

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