AI-900 Describe Artificial Intelligence workloads and considerations Practice Test 3 — 15 Questions

Question 1

A healthcare company deploys an AI system to assist doctors in diagnosing skin conditions from images. The system is a deep neural network that does not provide explanations for its predictions. The company implements a process where every AI recommendation is logged, and a medical team reviews any adverse outcomes to determine if the system or a human made an error. The company also clearly assigns responsibility for the system's outputs to a specific clinical oversight committee. Which Microsoft responsible AI principle is most directly being implemented by these actions?

Accepted Answer

Accountability. The actions described—logging AI recommendations, reviewing adverse outcomes to determine error source, and assigning a clinical oversight committee—directly implement the Accountability principle. Accountability requires that organizations clearly assign responsibility for AI system outputs and have processes to review and address impacts, which is exactly what the company does by creating a human review loop and a designated committee.

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Fairness

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Reliability and safety

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Transparency

Question 2

A company builds an AI system to filter job applications and rank candidates. The system is trained on historical hiring data. To reduce potential bias, the company removes protected attributes such as gender and ethnicity from the training data. However, after deployment, the system still shows a statistically significant bias against female candidates. Which Microsoft responsible AI principle most directly requires the company to investigate and address this remaining bias, even when protected attributes are removed?

Accepted Answer

Fairness. The Fairness principle requires AI systems to treat all people fairly and avoid creating or reinforcing discriminatory outcomes. Even when protected attributes like gender are removed from training data, bias can persist through proxy variables (e.g., zip code, education history) that correlate with protected attributes. The company must investigate and mitigate this remaining bias because Fairness mandates proactive assessment and correction of disparate impact, not just removal of obvious features.

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Inclusiveness

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Reliability and safety

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Transparency

Question 3

A hospital uses an AI system to analyze patient records for research. To protect patient identities, the system should not store or transmit any personally identifiable information (PII) outside the secure network. Which responsible AI principle is most directly addressed by this requirement?

Accepted Answer

Privacy and Security. The requirement to not store or transmit PII outside the secure network directly addresses the Privacy and Security principle. This principle ensures that individuals' data is protected from unauthorized access or exposure, which is critical in healthcare AI systems handling sensitive patient records. By restricting PII to the secure network, the system upholds data confidentiality and compliance with regulations like HIPAA.

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Fairness

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Inclusiveness

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Reliability and Safety

Question 4

A city deploys an AI-powered kiosk to help residents access government services. The kiosk uses a voice interface only, without any text or screen reader support. Which Microsoft responsible AI principle is most directly being ignored?

Accepted Answer

C. The kiosk uses only a voice interface without text or screen reader support, which directly violates the Microsoft responsible AI principle of Inclusiveness. Inclusiveness requires that AI systems are designed to empower everyone, including people with disabilities such as hearing impairments or those who rely on visual or text-based interfaces. By excluding non-verbal interaction methods, the system fails to accommodate diverse user needs, making it inaccessible.

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A

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B

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D

Question 5

An insurance company uses an AI system to automatically process and approve or reject claims. The system sometimes rejects valid claims because the uploaded documents are in slightly different formats (e.g., PDF vs. scanned images). The company wants to minimize these errors. Which Microsoft responsible AI principle is most directly relevant to addressing this issue?

Accepted Answer

Reliability and safety. The issue is that the AI system fails to process valid claims due to variations in document formats (PDF vs. scanned images), which is a reliability and safety problem. The system should be robust enough to handle input variations and consistently produce correct outcomes. Microsoft's Reliability and safety principle focuses on ensuring AI systems operate reliably, safely, and consistently under expected conditions, directly addressing the need to minimize such errors.

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Fairness

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Inclusiveness

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Transparency

Question 6

A company develops an AI system to screen job candidates based on their resumes. The system is trained on historical data. Analysis reveals that the model has an adverse impact against female candidates due to a proxy feature (e.g., 'years of continuous employment') that correlates with gender. The team removes the protected attribute 'gender' from the training data but the biased outcome persists. According to Microsoft's responsible AI principles, which additional step should the team take to address this unfairness?

Accepted Answer

Use a tool like Fairlearn to detect and mitigate the bias while maintaining model performance.. Option B is correct because Microsoft's responsible AI principle of fairness requires not just removing protected attributes but also detecting and mitigating proxy features that cause bias. Fairlearn is a Microsoft open-source toolkit specifically designed to assess and mitigate unfairness in AI systems, offering algorithms like 'Exponentiated Gradient Reduction' or 'Grid Search' to reduce disparity while preserving model performance. Simply removing the proxy feature (A) may not always be feasible if it carries predictive value, and Fairlearn provides a systematic way to balance fairness and accuracy.

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Remove the offending proxy feature 'years of continuous employment' from the training data.

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Train a separate model for each gender group to ensure equal outcomes.

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Collect more training data from underrepresented groups.

Question 7

A hospital deploys an AI system to assist in diagnosing diseases from medical images. The system is a complex deep learning model that provides a diagnosis without any explanation. Doctors are skeptical and want to understand why the system made a particular recommendation. The hospital decides to deploy the system without providing any interpretability. Which Microsoft responsible AI principle is most directly being violated?

Accepted Answer

Transparency. The system provides a diagnosis without any explanation of how it reached its conclusion, and the hospital decides to deploy it without interpretability. This directly violates the transparency principle, which requires AI systems to be understandable and for their decisions to be explainable to users, especially in high-stakes domains like healthcare.

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Fairness

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Reliability & Safety

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Inclusiveness

Question 8

A hospital uses an AI system to prioritize patient appointments based on urgency. The system is trained on historical data. The team wants to ensure that the system does not discriminate against patients based on age or disability. Which Microsoft responsible AI principle should most directly guide the design of this system?

Accepted Answer

Inclusiveness. The Inclusiveness principle directly guides the design of this system because it requires AI systems to empower everyone and avoid discrimination, including on the basis of age or disability. By proactively identifying and mitigating bias in the training data and model predictions, the hospital can ensure that appointment prioritization does not unfairly disadvantage any patient group. This principle is specifically about fairness and accessibility, making it the most relevant for preventing discriminatory outcomes.

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Privacy and security

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Reliability and safety

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Transparency

Question 9

A company develops an AI system to recommend personalized news articles to users. The system uses collaborative filtering, suggesting articles that similar users have read. Which type of machine learning does this approach primarily rely on?

Accepted Answer

Unsupervised learning. Collaborative filtering identifies patterns in user-item interactions without labeled outcomes, grouping users or items based on similarity. This is a classic unsupervised learning task because the system discovers hidden structures (e.g., user clusters) from unlabeled data, rather than being trained on explicit input-output pairs.

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Supervised learning

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Reinforcement learning

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Semi-supervised learning

Question 10

A hospital uses an AI system to prioritize emergency room patients based on severity. The system was trained on historical data that may contain biases against certain demographic groups. The hospital wants to ensure the system does not disproportionately disadvantage any group. According to Microsoft's responsible AI principles, which practice should the hospital implement during the design phase?

Accepted Answer

Conduct an impact assessment and involve diverse stakeholders during design. Option B is correct because Microsoft's responsible AI principles emphasize the importance of conducting impact assessments and involving diverse stakeholders during the design phase to identify and mitigate potential biases before deployment. This proactive approach aligns with the fairness principle, ensuring that the AI system does not disproportionately disadvantage any demographic group. Simply removing features or relying on post-deployment monitoring is insufficient to address systemic biases embedded in historical data.

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Remove all demographic features from the training data to achieve fairness through unawareness

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Use a complex, uninterpretable model to avoid scrutiny of predictions

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Deploy the system and rely on post-deployment monitoring to catch unfair outcomes

Question 11

A retail store wants to use an AI solution to automatically monitor security camera feeds and detect when a shelf is empty or if a person is in a restricted area. Which type of AI workload is best suited for this task?

Accepted Answer

Computer Vision. Computer Vision is the correct AI workload because it enables the system to analyze video frames from security cameras to detect visual patterns such as empty shelves (object absence) or unauthorized persons in restricted areas (object presence and location). This workload uses image classification, object detection, and semantic segmentation to interpret visual data in real time.

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Natural Language Processing

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Speech Recognition

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Anomaly Detection

Question 12

A hospital deploys an AI system to assist doctors in interpreting MRI scans. The system highlights the regions of interest and provides a numeric confidence score for its findings, along with a list of the image features that contributed to the diagnosis. Which responsible AI principle is being applied?

Accepted Answer

Transparency. The system provides a numeric confidence score and a list of image features that contributed to the diagnosis, which directly supports the principle of Transparency. Transparency in responsible AI requires that AI systems are understandable and that their decisions can be explained to users, enabling clinicians to interpret and trust the output.

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Fairness

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Privacy

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Accountability

Question 13

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?

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.

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Reliability and safety

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Privacy and security

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Inclusiveness

Question 14

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.

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Fairness

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Reliability and safety

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Privacy and security

Question 15

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. Option C is correct because 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.

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Fairness

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Transparency

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Inclusiveness