EXAMINING ALGORITHMIC BIAS IN ONLINE MENTAL HEALTH RESOURCES

The online landscape is rapidly evolving to offer mental health assistance. However, these platforms often rely algorithms that can perpetuate existing societal biases. This presents a serious issue as users seeking aid may encounter unfair outcomes based on their ethnicity, gender, or other personal traits. It is essential to deconstruct these ine

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