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AI-900: Key Principles for Building Responsible and Ethical AI

Companies like Microsoft provide guiding principles for developing AI responsibly. Learn about core tenets like inclusiveness, fairness, and reliability that ensure ethical, trustworthy AI systems.

Question

What are three Microsoft guiding principles for responsible AI?
Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.

A. knowledgeability
B. decisiveness
C. inclusiveness
D. fairness
E. opinionatedness
F. reliability and safety

Answer

C. inclusiveness
D. fairness
F. reliability and safety

Explanation

The correct answer is C, D, and F. Three Microsoft guiding principles for responsible AI are inclusiveness, fairness, and reliability and safety.

Inclusiveness means that AI systems should empower everyone and engage people. This principle involves designing AI systems that are accessible, respectful, and understandable to diverse users, and that can address the needs and expectations of different groups and communities. Inclusiveness also means involving diverse stakeholders in the development and deployment of AI systems, and ensuring that they can participate in the benefits and opportunities of AI.

Fairness means that AI systems should treat all people fairly. This principle involves identifying and mitigating potential biases in the data, models, and algorithms that underlie AI systems, and ensuring that they do not discriminate or harm any individuals or groups. Fairness also means providing mechanisms for feedback and redress for those who are affected by the outcomes of AI systems, and promoting equal access and opportunity for all.

Reliability and safety means that AI systems should perform reliably and safely. This principle involves designing AI systems that are robust, secure, and resilient to errors, attacks, and changes in the environment, and that can handle uncertainty and ambiguity. Reliability and safety also means testing and validating AI systems before and after deployment, and monitoring and updating them as needed to ensure their quality and performance.

The other options are not Microsoft guiding principles for responsible AI. Knowledgeability, decisiveness, and opinionatedness are not among the six principles that Microsoft has defined for building AI systems responsibly and in ways that warrant people’s trust. The other three principles are privacy and security, transparency, and accountability.

Reference

Microsoft Learn > Training > Browse > Identify guiding principles for responsible AI

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

Alex Lim is a certified IT Technical Support Architect with over 15 years of experience in designing, implementing, and troubleshooting complex IT systems and networks. He has worked for leading IT companies, such as Microsoft, IBM, and Cisco, providing technical support and solutions to clients across various industries and sectors. Alex has a bachelor’s degree in computer science from the National University of Singapore and a master’s degree in information security from the Massachusetts Institute of Technology. He is also the author of several best-selling books on IT technical support, such as The IT Technical Support Handbook and Troubleshooting IT Systems and Networks. Alex lives in Bandar, Johore, Malaysia with his wife and two chilrdren. You can reach him at [email protected] or follow him on Website | Twitter | Facebook

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