Microsoft Azure AI Fundamentals AI-900 Practice Question

A company is developing an AI-driven mobile application that collects user data to provide personalized recommendations.

To address concerns about privacy and security, which practice should the company adopt?

Collecting as many data points as possible to improve recommendations
Implementing robust encryption techniques for data at rest and in transit
Giving developers access to user data for debugging purposes
Storing user data on shared servers to reduce costs

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Answer Description

Implementing robust encryption techniques for data at rest and in transit - This is the correct answer. To address concerns about privacy and security, the company should implement strong encryption techniques to protect user data both when it is stored at rest and when it is transmitted in transit. This ensures that sensitive data is secure and reduces the risk of unauthorized access.

Collecting as many data points as possible to improve recommendations - While collecting data may help improve recommendations, it raises privacy concerns if personal data is not properly protected or managed. This approach does not directly address the need for secure handling of user data.

Giving developers access to user data for debugging purposes - Giving developers access to user data can create significant privacy and security risks. It is important to ensure that user data is only accessible to those who have a legitimate need and that proper safeguards are in place.

Storing user data on shared servers to reduce costs - Storing user data on shared servers without adequate security measures can expose the data to higher risks of breaches and unauthorized access. It is essential to store user data securely, even if it means higher costs for private or dedicated infrastructure.

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Microsoft Azure AI Fundamentals AI-900

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