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AI-900: Upholding Integrity: Microsoft’s Anti-Bias Rule in Responsible AI

Delve into the core of responsible AI with Microsoft’s commitment to fairness. Uncover how the anti-bias principle shapes AI systems, preventing the reflection of biases from training datasets. Explore the pivotal role this principle plays in creating unbiased and equitable artificial intelligence solutions.


To complete the sentence, select the appropriate option in the answer area.
According to Microsoft’s _________________ principle of responsible AI, AI systems should NOT reflect biases from the data sets that are used to train the systems.

A. accountability
B. fairness
C. inclusiveness
D. transparency


B. fairness


The correct answer is B. fairness.

According to Microsoft’s fairness principle of responsible AI, AI systems should not reflect biases from the data sets that are used to train the systems. Bias is a systematic error that leads to unfair or inaccurate outcomes for some groups of people. For example, an AI system that predicts the likelihood of loan default based on demographic data might discriminate against certain ethnic groups or genders if the training data is skewed or unrepresentative. To avoid such bias, AI developers should use diverse and inclusive data sets, apply fairness metrics and techniques, and monitor and evaluate the performance of their systems across different groups. By doing so, they can ensure that their AI systems are fair and respectful of human dignity and rights.


Microsoft Docs > Azure > Cloud Adoption Framework > Adopt > Innovate > Responsible and trusted 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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