AI and machine learning models have drastically improved predictive abilities and personalized services but often at the cost of user privacy. These systems rely on vast amounts of data, including sensitive personal information, leading to potential privacy breaches. Enhancements in anonymization techniques and differential privacy can provide stronger safeguards, ensuring data utility while protecting individual anonymity.
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