UNPACKING ALGORITHMIC BIAS IN ONLINE MENTAL HEALTH RESOURCES

The digital landscape is rapidly evolving to offer mental health assistance. However, these tools often rely algorithms that can propagate existing societal biases. This raises a serious issue as users seeking aid may encounter unfair outcomes based on their background, gender, or other sensitive attributes. It is crucial to deconstruct these biase

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