Sensitive data is confidential, private, or protected by regulations. This may include personal information, financial information, medical information, and other types of data that must be protected from unauthorized access or misuse.
Examples of sensitive data include
- Personal information such as names, addresses, government id numbers, and date of birth.
- Financial information such as bank account numbers and credit card numbers.
- Behavioral data such as internet search history and purchasing patterns.
- Medical data that contains diagnoses and test results.
The handling and protection of sensitive data is a key issue in the development and deployment of AI systems because any unauthorized access or misuse of this information can have catastrophic consequences, such as identity theft, financial fraud, and loss of privacy.To protect sensitive data, AI practitioners employ techniques such as Stained Glass Transformation™, data anonymization, data perturbation, or other methods to reduce the risk of unauthorized use. They may also implement strict data access controls and monitor the use of sensitive data to ensure that it is being used responsibly in accordance with legal requirements.