DISSECTING ALGORITHMIC BIAS IN ONLINE MENTAL HEALTH RESOURCES

The digital landscape is rapidly evolving to provide mental health assistance. However, these tools often depend on algorithms that can reinforce existing societal biases. This poses a serious issue as individuals seeking support may encounter prejudiced outcomes based on their ethnicity, gender, or other protected characteristics. It is crucial to

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