EXAMINING ALGORITHMIC BIAS IN ONLINE MENTAL HEALTH RESOURCES

The online landscape is rapidly evolving to deliver mental health support. However, these systems often rely algorithms that can perpetuate existing societal biases. This poses a serious issue as people seeking support may encounter prejudiced outcomes based on their ethnicity, gender, or other protected characteristics. It is crucial to unpack the

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