Glossary

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Data anonymization is the process of removing or altering personally identifiable information (PII) from a dataset so that individuals cannot be readily identified from the data. 
Data augmentation is generating new data samples by modifying existing data.
Data labeling is tagging or annotating raw data—such as images.
Data leakage refers to the unintended or unauthorized exposure of sensitive or confidential information to individuals or systems that should not have access.
Data obfuscation is a data masking technique that transforms sensitive data into a different format or representation to prevent unauthorized access while keeping its structure usable for development, testing, or analytics.
Data privacy in artificial intelligence refers to protecting personal.
Data redaction is the process of removing or obscuring sensitive or confidential information from a document or dataset to protect privacy, security, and confidentiality.
Data transfer costs in cloud computing refer to the fees associated with moving data.
A Decision Policy refers to a strategy or rule that guides an AI system’s decision-making process. It defines how the system selects actions based on the current state of the environment, internal goals, and past experiences.