Learn about data minimization as a privacy control when building AI systems. Understand how limiting sensitive data collection helps protect privacy in this IBM AI Fundamentals Exam practice question.
Table of Contents
Question
Rutherford is trying to implement a privacy control to fortify the AI system that he is working on. He decides to limit the amount of personal and sensitive data that is collected and takes steps to ensure that the data collected is only as granular as needed.
Which of the following privacy controls is Rutherford using?
A. Differential privacy
B. Data minimization
C. Data aggregation
D. Model anonymization
Answer
B. Data minimization
Explanation
Data minimization focuses on collecting and processing the minimum amount of personal information without adding random noise or anonymizing the data.
Data minimization is the practice of limiting the collection of personal data to only what is directly relevant and necessary to accomplish a specified purpose. The key aspects of data minimization are:
- Collect only the minimum amount of personal data required.
- Ensure the granularity of data collected is not excessive.
- Retain the data only for as long as necessary.
By deciding to limit the amount of personal and sensitive data collected and ensuring that the collected data is only as granular as needed, Rutherford is directly applying the principles of data minimization. This approach helps to protect individual privacy by reducing the risk of data breaches, misuse, or unauthorized access to sensitive information.
The other options mentioned are also privacy controls but do not accurately describe Rutherford’s actions:
- Differential privacy: A technique that adds noise to the data or the results of queries to prevent the identification of individuals.
- Data aggregation: Combining data from multiple sources to derive insights while protecting individual data points.
- Model anonymization: Removing personally identifiable information from a trained AI model to protect individual privacy.
In summary, data minimization is a crucial privacy control that involves collecting only the necessary personal data at an appropriate level of granularity. By implementing this control, Rutherford is taking a proactive step to fortify the AI system and protect the privacy of individuals whose data is being used.
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