Discover how to ensure AI solutions meet Microsoft’s Responsible AI principles of reliability and safety through rigorous testing and governance frameworks.
Table of Contents
Question
You are designing AI solutions for an automobile company. Which of the following requirements must you fulfil to ensure that your solutions adhere to the responsible AI principle of Reliability and Safety?
A. Making users fully aware of how the systems work
B. Strenuous testing and deployment management procedures
C. Working within a specified governance framework
D. Ensuring that the systems benefit people from all parts of society
Answer
B. Strenuous testing and deployment management procedures
Explanation
Strenuous testing and deployment management procedures can help fulfill the principle of Reliability and Safety for responsible AI. These directly address the need to ensure that the AI systems in cars function reliably and pose minimal risk to drivers and passengers. They involve rigorous testing under a variety of conditions and careful management of the deployment process to minimize the possibility of malfunctions and errors.
Working within a specified governance framework is related to Accountably, not Reliability and Safety. While important for ethical considerations, it does not directly address the technical aspect of ensuring reliability and safety in the specific context of automotive AI.
Making users fully aware of how the systems work is related to Transparency, not Reliability and Safety. It is crucial, but it does not guarantee the inherent reliability and safety of the AI systems themselves.
Ensuring that the systems benefit people from all parts of society falls under the principle of Inclusivity, not Reliability and Safety.
The six key principles of responsible AI include:
- Fairness: AI systems should treat all people fairly, avoiding biases based on factors such as gender and ethnicity.
- Reliability and Safety: AI systems should perform reliably and safely, with rigorous testing and deployment management to ensure expected functionality and minimize risks.
- Privacy and Security: AI systems should be secure and respect privacy, considering the privacy implications of the data used and decisions made by the system.
- Inclusiveness: AI systems should empower and engage everyone, bringing benefits to all parts of society without discrimination.
- Transparency: AI systems should be understandable, with users fully aware of the system’s purpose, functioning, and limitations.
- Accountability: People should be accountable for AI systems, working within a framework of governance and organizational principles to meet ethical and legal standards.
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