EXAMINING ALGORITHMIC BIAS IN ONLINE MENTAL HEALTH RESOURCES

The online landscape is rapidly evolving to provide mental health support. However, these systems often rely algorithms that can propagate existing societal biases. This presents a serious concern as people seeking support may encounter unfair outcomes based on their background, gender, or other protected characteristics. It is essential to unpack

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