EXAMINING ALGORITHMIC BIAS IN ONLINE MENTAL HEALTH RESOURCES

The online landscape is rapidly evolving to provide mental health assistance. However, these tools often rely algorithms that can perpetuate existing societal biases. This poses a serious issue as users seeking support may encounter prejudiced outcomes based on their background, gender, or other personal traits. It is essential to deconstruct these

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