Description: Machine learning for anonymization refers to the use of advanced artificial intelligence techniques to enhance personal data protection processes. This approach allows algorithms to learn patterns and characteristics of data, facilitating the identification of sensitive information that needs to be anonymized. Through methods such as supervised and unsupervised learning, models can adapt and optimize to recognize and remove identifiable data, thus ensuring that information remains private and secure. The relevance of this technique lies in its ability to handle large volumes of data, where manual anonymization would be impractical. Additionally, machine learning can help maintain the utility of data, allowing it to be used for analysis and studies without compromising individuals’ privacy. In a world where data protection is increasingly critical, machine learning for anonymization emerges as an innovative and effective solution to comply with regulations such as GDPR and other privacy standards.
