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AI-900: What Microsoft Principle of Responsible AI Ensures AI Systems Do Not Reflect Dataset Biases?

Discover which Microsoft principle of responsible AI ensures that AI systems do not reflect biases from their training data sets. Learn the key principles for the AI-900 certification exam.

Table of Contents

Question

According to which Microsoft’s principle of responsible AI, AI system should not reflect biases from the data sets that are used to train the systems. Select the correct option.

A. inclusiveness
B. privacy and security
C. fairness
D. accountability

Answer

According to Microsoft’s principles of responsible AI, the principle that states AI systems should not reflect biases from the data sets used to train them is:

C. Fairness

Explanation

Fairness is a crucial principle in responsible AI development. It ensures that AI systems treat all individuals equitably and do not discriminate based on factors such as race, gender, age, or other protected characteristics. When training AI models, it is essential to use diverse and representative data sets to prevent the introduction of biases into the system.

Biased data can lead to AI systems making unfair decisions or perpetuating societal biases. For example, if an AI system is trained on a dataset that predominantly features images of people with lighter skin tones, it may struggle to accurately recognize individuals with darker skin tones. This lack of fairness in the AI system can have severe consequences in real-world applications, such as facial recognition for law enforcement or hiring processes.

To mitigate biases, AI developers must carefully curate and preprocess training data, ensuring it is balanced and representative of the population the AI system will serve. Additionally, regular audits and testing should be conducted to identify and rectify any biases that may emerge during the development and deployment of AI systems.

By adhering to the principle of fairness, organizations can create AI systems that promote equality, avoid discrimination, and provide unbiased outcomes for all users. This commitment to fairness is essential for building trust in AI technologies and ensuring their responsible development and deployment.

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

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.