AI-900 Describe Artificial Intelligence workloads and considerations Practice Test 4 — 15 Questions

Question 1

A bank is developing an AI system to automatically approve or reject small business loan applications. The bank wants to ensure that the system does not unfairly discriminate against applicants based on their age, gender, or ethnicity. Which Microsoft responsible AI principle should most directly guide the design and evaluation of this system?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

Fairness. The bank's goal is to prevent discrimination based on age, gender, or ethnicity in loan approvals. The Fairness principle directly addresses this by requiring AI systems to treat all groups equitably and to mitigate biases in training data and model predictions. This principle guides the design and evaluation of the system to ensure that outcomes are not skewed by protected attributes.

Answer

Reliability and safety

Answer

Privacy and security

Answer

Inclusiveness

Question 2

A bank deploys an AI system to approve personal loans. The system uses a complex deep learning model that produces a decision (approve or reject) without any explanation of why. Loan applicants who are rejected are not given any reason. According to Microsoft's responsible AI principles, which principle is most directly violated by this system?

Accepted Answer

Transparency. The system's inability to provide any explanation for its loan approval or rejection decisions directly violates the transparency principle. Microsoft's responsible AI principle of transparency requires that AI systems be understandable and that users be informed about how decisions are made, including the factors that influenced the outcome. A black-box deep learning model that gives no reasoning or feedback to rejected applicants fails this requirement.

Answer

Fairness

Answer

Reliability and safety

Answer

Privacy and security

Question 3

A hospital uses an AI system to analyze patient health records for research. The hospital must ensure that all patient data is stored securely and only authorized personnel can access it. Which Microsoft responsible AI principle is most directly relevant?

Accepted Answer

Privacy and security. The scenario explicitly focuses on secure storage and access control of patient data, which directly aligns with Microsoft's responsible AI principle of Privacy and security. This principle ensures that data is protected against unauthorized access and breaches, often implemented through encryption (e.g., AES-256 for data at rest, TLS 1.2+ for data in transit) and role-based access control (RBAC) in Azure services like Azure SQL Database or Azure Blob Storage.

Answer

Fairness

Answer

Transparency

Answer

Inclusiveness

Question 4

A self-driving car company develops an AI system that is highly accurate in testing but fails to consistently detect pedestrians during heavy rain. Which Microsoft responsible AI principle is most directly violated?

Accepted Answer

Reliability and safety. The system fails to consistently detect pedestrians during heavy rain, which is a failure of the AI to perform reliably under real-world conditions. Microsoft's 'Reliability and safety' principle requires AI systems to operate dependably and safely across all expected scenarios, including edge cases like adverse weather. This directly violates that principle because the system's accuracy drops in a common environmental condition, posing safety risks.

Answer

Fairness

Answer

Privacy and security

Answer

Transparency

Question 5

A company wants to implement an AI solution that treats all users fairly regardless of their background. Which Microsoft responsible AI principle does this requirement primarily address?

Accepted Answer

Fairness. The requirement to treat all users fairly regardless of background directly aligns with the Fairness principle, which mandates that AI systems should allocate outcomes, opportunities, or resources equitably and avoid discrimination based on sensitive attributes such as race, gender, or age. In Azure AI, this is operationalized through tools like Fairlearn and the Responsible AI dashboard, which assess and mitigate bias in model predictions. The other principles address different concerns: Privacy focuses on data protection, Inclusiveness on accessibility for diverse abilities, and Transparency on explainability of decisions.

Answer

Privacy

Answer

Inclusiveness

Answer

Transparency

Question 6

A company is developing an AI system to recommend movies to users. The team wants to ensure that the recommendations do not discriminate based on gender or ethnicity. Which Microsoft responsible AI principle is most directly related to this goal?

Accepted Answer

A) Fairness. Fairness is the Microsoft responsible AI principle that directly addresses the goal of preventing discrimination based on gender or ethnicity in AI recommendations. It requires that AI systems treat all people equitably, avoiding biases that could lead to unfair outcomes, such as recommending different movies to users based on protected attributes rather than their preferences.

Answer

B) Inclusiveness

Answer

C) Reliability and Safety

Answer

D) Transparency

Question 7

A global e-commerce company is designing an AI-powered chatbot to assist customers. They want to ensure the chatbot can be used by people with diverse abilities, including those who use screen readers or speak different languages. Which Microsoft responsible AI principle is most directly related to this requirement?

Accepted Answer

Inclusiveness. The requirement to support screen readers and multiple languages directly aligns with Microsoft's responsible AI principle of inclusiveness, which aims to design AI systems that empower everyone, including people with disabilities and diverse linguistic backgrounds. In the context of a chatbot, inclusiveness ensures features like screen reader compatibility (via ARIA labels and semantic HTML) and multilingual natural language processing (NLP) models that can handle different languages and dialects, making the technology accessible to a broader audience.

Answer

Fairness

Answer

Reliability and Safety

Answer

Transparency

Question 8

A healthcare company develops an AI system to recommend treatment plans. The system sometimes provides recommendations that contradict standard medical guidelines, leading to potential patient harm. Which Microsoft responsible AI principle is most directly violated?

Accepted Answer

Reliability and safety. The system's recommendations contradicting standard medical guidelines and causing potential patient harm directly violates the Reliability and safety principle. This principle requires AI systems to perform consistently, safely, and as intended, especially in high-stakes domains like healthcare where failures can lead to injury or death. The scenario describes a lack of robustness and failure to meet expected safety standards, which is the core concern of this principle.

Answer

Fairness

Answer

Privacy and security

Answer

Inclusiveness

Question 9

A healthcare organization plans to use AI to analyze patient records for medical research. They must ensure that patient data is protected from unauthorized access during storage and processing. Which Microsoft responsible AI principle is most directly relevant to this requirement?

Accepted Answer

Privacy and security. The requirement to protect patient data from unauthorized access during storage and processing directly aligns with the Privacy and security principle. This principle mandates that AI systems implement robust data protection mechanisms, such as encryption at rest (e.g., AES-256) and in transit (e.g., TLS 1.2/1.3), access controls (e.g., Azure RBAC), and compliance with regulations like HIPAA. It ensures that sensitive healthcare data remains confidential and secure throughout its lifecycle.

Answer

Fairness

Answer

Inclusiveness

Answer

Reliability and safety

Question 10

A hospital is developing an AI system to assist doctors in diagnosing diseases from medical images. The system's predictions can influence patient treatment. Which Microsoft responsible AI principle is most important to ensure the system's decisions are accurate and reliable?

Accepted Answer

Reliability and Safety. In a medical diagnosis system, accuracy and reliability are paramount because incorrect predictions can directly lead to patient harm. The Reliability and Safety principle ensures the AI system performs consistently under expected conditions, with appropriate fail-safes and validation, which is the core requirement for clinical decision support.

Answer

Fairness

Answer

Privacy and Security

Answer

Inclusiveness

Question 11

A bank is developing an AI system to automatically approve or reject small personal loans. To ensure the system treats applicants fairly regardless of race, gender, or age, which Microsoft responsible AI principle is most directly relevant?

Accepted Answer

Fairness. The Fairness principle is directly relevant because it requires AI systems to treat all individuals equitably, avoiding discrimination based on protected attributes like race, gender, or age. In this loan approval scenario, the system must be designed and tested to ensure its decisions do not systematically disadvantage any group, which is the core goal of fairness in AI.

Answer

Inclusiveness

Answer

Reliability and safety

Answer

Transparency

Question 12

A healthcare organization deploys an AI system that analyzes patient genetic data to recommend personalized treatments. To ensure patient data is protected from unauthorized access during use, which Microsoft responsible AI principle is most directly relevant?

Accepted Answer

Privacy and security. The scenario explicitly focuses on protecting patient genetic data from unauthorized access, which directly falls under the Privacy and security principle. This principle ensures that data is encrypted, access-controlled, and compliant with regulations like HIPAA or GDPR, preventing breaches during AI model inference or storage.

Answer

Fairness

Answer

Reliability and safety

Answer

Transparency

Question 13

A city government implements an AI system to analyze traffic camera feeds and predict congestion. The system is found to be less accurate for neighborhoods with lower-income populations because historical traffic data from those areas is sparse. Which Microsoft responsible AI principle is most directly relevant to address this issue?

Accepted Answer

Fairness. The system's reduced accuracy for lower-income neighborhoods due to sparse historical data is a direct fairness issue. Fairness in AI requires that systems perform equitably across different demographic groups, and this scenario describes a clear disparity in model performance based on socioeconomic factors. Addressing this would involve techniques like data augmentation, reweighting, or collecting more representative data to mitigate bias.

Answer

Transparency

Answer

Accountability

Answer

Privacy and security

Question 14

A company deploys an AI system to screen job applications. The system is a complex neural network that learns patterns from historical hiring data. A rejected candidate asks for an explanation, but the development team cannot describe how the decision was reached. Which Microsoft responsible AI principle is most directly violated?

Accepted Answer

Transparency. The system's inability to explain how it reached a decision violates the transparency principle, which requires AI systems to be understandable and interpretable. Complex neural networks often act as black boxes, making it impossible to provide meaningful explanations to users, directly contradicting Microsoft's responsible AI guideline that decisions should be explainable.

Answer

Fairness

Answer

Privacy and security

Answer

Reliability and safety

Question 15

A financial institution uses an AI model to assess creditworthiness for loan applications. After deployment, they discover that the model assigns higher risk scores to applicants from certain postal codes, which are predominantly low-income minority neighborhoods. The model's predictions are accurate according to historical data, but the bank is concerned about ethical implications. Which Microsoft responsible AI principle is most directly applicable to addressing this issue?

Accepted Answer

Fairness. The model's assignment of higher risk scores based on postal codes, which correlate with low-income minority neighborhoods, directly violates the Fairness principle. This principle requires AI systems to treat all groups equitably and avoid reinforcing societal biases, even if the model's predictions are statistically accurate according to historical data. The bank's ethical concern centers on disparate impact, which fairness assessments (e.g., demographic parity or equal opportunity metrics) are designed to detect and mitigate.

Answer

Inclusiveness

Answer

Reliability and Safety

Answer

Privacy and Security