AI-900 Practice Question: Describe Artificial Intelligence workloads and considerations
A city government is planning to deploy an AI system that analyzes security camera footage to detect potential crimes in real-time. Citizens express concerns about privacy and potential misuse. Which Microsoft responsible AI principle should the government prioritize to address these concerns?
⚠ Common exam trap
Candidates often confuse 'Privacy and security' with 'Fairness' or 'Reliability and safety' because they all sound like ethical safeguards, but only Privacy and security directly addresses data protection and misuse concerns in surveillance systems.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Privacy and security
The citizens' concerns center on unauthorized access to sensitive video data and potential misuse of surveillance footage. Microsoft's Privacy and security principle directly addresses these issues by mandating data protection, transparency in data collection, and user control over personal information. Prioritizing this principle ensures the AI system complies with regulations like GDPR and implements encryption, access controls, and data minimization to safeguard citizen privacy.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Fairness
Why it's wrong here
Fairness in AI specifically addresses algorithmic bias and equitable outcomes across demographic groups, such as ensuring a facial-recognition model has comparable false-positive rates for all races and genders. The city's concern, however, is about unauthorized surveillance and misuse of footage — a data-governance and consent issue, not a model-bias issue. Even a perfectly fair model would still violate privacy if its outputs are retained or repurposed without safeguards.
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Reliability and safety
Why it's wrong here
Reliability and safety focus on whether the AI system performs consistently and fails without causing physical or operational harm, such as avoiding false alerts or system crashes that could endanger public safety. In this scenario, the worry is not that the system might malfunction, but that the collected surveillance video and metadata could be accessed or used in privacy-violating ways, including unauthorized tracking or data leakage. A system can be technically reliable and safe yet still be privacy-invasive if the data lifecycle is not properly governed.
- ✓
Privacy and security
Why this is correct
Privacy and security is the correct principle because it directly governs how data is collected, stored, and used — exactly the issue with a city deploying AI to analyze surveillance footage. Key requirements include data minimization (collecting only necessary data), purpose limitation (using footage only for its stated civic function), and robust security controls such as encryption and role-based access to prevent unauthorized viewing. This principle addresses concerns about misuse by mandating both policy guardrails and technical safeguards over who can access the footage and for what purpose.
- ✗
Inclusiveness
Why it's wrong here
Inclusiveness is about ensuring the AI system is designed to be accessible and usable by everyone, including people with disabilities and those from diverse cultural or language backgrounds, often by engaging diverse communities in the design process. The privacy issue raised by the city government does not center on how users interact with the system or how accessible it is, but on the collection and potential misuse of surveillance footage. Therefore, inclusiveness is a valuable principle but is not the relevant one for this data-handling and consent problem.
Go deeper
Related to this question
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Responsible AI Principles
Key term
Transparency
Transparency in AI means that the inner workings, decision-making processes, and data used by an AI system are open, understandable, and auditable by humans.
Key term
Responsible AI
A framework of ethical principles and practices that ensure artificial intelligence systems are developed and deployed in a transparent, fair, accountable, and safe manner.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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