EXAMINING ALGORITHMIC BIAS IN ONLINE MENTAL HEALTH RESOURCES

The virtual landscape is rapidly evolving to deliver mental health support. However, these tools often rely algorithms that can propagate existing societal biases. This presents a serious issue as users seeking aid may encounter prejudiced outcomes based on their race, identity, or other protected characteristics. It is vital to unpack these biases

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