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AI-900: Reliability and Safety: A Responsible AI Principle

Learn what reliability and safety means in the context of responsible AI, and how Microsoft applies this principle to its AI systems and practices.

Table of Contents

Question

Ensuring that Al systems operate as they were intended, respond to unanticipated conditions, and resist harmful manipulations is a consideration of which responsible Al principle?

A. Fairness
B. Accountability
C. Reliability and safety

Answer

C. Reliability and safety

Explanation

The principle of reliability and safety states that Al systems should perform reliably and safely.

The correct answer is C. Reliability and safety.

Reliability and safety is one of the six responsible AI principles that Microsoft has developed to guide AI development and use. It means that AI systems should operate as they were intended, respond to unanticipated conditions, and resist harmful manipulations. Reliability and safety also involves ensuring that AI systems are robust, secure, and resilient to errors, failures, and attacks.

Some of the goals and practices that support reliability and safety are:

  • Define and test the operational boundaries and scenarios of the AI system
  • Monitor and measure the performance and behavior of the AI system
  • Implement mechanisms to detect and mitigate errors, failures, and malicious attacks
  • Establish clear roles and responsibilities for the development, deployment, and management of the AI system
  • Document and communicate the limitations and risks of the AI system

Microsoft Azure AI Fundamentals AI-900 certification exam practice question and answer (Q&A) dump with detail explanation and reference available free, helpful to pass the Microsoft Azure AI Fundamentals AI-900 exam and earn Microsoft Azure AI Fundamentals AI-900 certification.

Microsoft Azure AI Fundamentals AI-900 certification exam practice question and answer (Q&A) dump