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| Section | Weight | Objectives |
|---|---|---|
| Governance of AI Deployment and Use | 21โ25% | - Incident response, accountability and audit - Selection, procurement and third-party management - Lifecycle maintenance, decommissioning and updates - Implementation, monitoring and ongoing oversight |
| Foundational Concepts of AI Governance | 24โ28% | - Fundamental AI definitions, types and characteristics - Impacts, risks and benefits of AI systems - Principles of responsible, ethical and trustworthy AI - Governance frameworks and core concepts |
| Laws, Regulations, Standards and Frameworks | 24โ28% | - International standards (ISO 42001, NIST AI RMF, etc.) - Alignment with data protection and privacy laws - Sector-specific requirements and compliance obligations - Global and regional regulations (EU AI Act, US, etc.) |
| Governance of AI Development | 21โ25% | - Testing, validation, documentation and transparency - Governance through design and lifecycle management - Model management, version control and quality assurance - Requirements gathering, risk assessment and mitigation |
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NEW QUESTION # 140
Testing data is defined as a subset of data that is used to:
Answer: B
Explanation:
Testing data is used to provide an unbiased evaluation of the final model's performance before deployment.
NEW QUESTION # 141
All of the following are examples of biometric data in the US EXCEPT?
Answer: D
Explanation:
Biometric data in the U.S. refers to data that relates to measurable biological and behavioral characteristics that can be used to identify an individual. Examples include fingerprints, facial recognition, iris scans, and behavior-based data like gait or keystrokes.
According to definitions and discussions from theAI Governance in Practice Report 2024and U.S. privacy frameworks:
"Biometric data includes physical and behavioral human characteristics that can be used to digitally identify a person to grant access to systems, devices, or data. Examples include facial images, iris patterns, gait analysis, and voice recognition." (Report context based on common frameworks in U.S. AI law and the use of biometrics in AI governance.) Here's how the options relate:
* A. Iris scans- These are physical biometric identifiers.
* B. Walking gait- Behavioral biometric used increasingly in surveillance and identification.
* C. Keystroke dynamics- Behavioral biometric based on typing patterns.
* D. GPS location of a user's fitness watch- This isnotbiometric data. It islocation data, which may be sensitive or personal, but not biometric.
NEW QUESTION # 142
Which of the following elements of feature engineering is most important to mitigate the potential bias in an Al system?
Answer: B
Explanation:
Feature selection is the most important element of feature engineering to mitigate potential bias in an AI system. This process involves choosing the most relevant and representative features from the data set, which directly affects the model's performance and fairness. By carefully selecting features, data scientists can reduce the influence of biased or irrelevant attributes, ensuring that the AI system is more accurate and equitable. Proper feature selection helps in eliminating biases that might stem from socio-demographic factors or other sensitive variables, leading to a more balanced and fair AI model. Reference: AIGP Body of Knowledge on Fairness in AI and Feature Engineering.
NEW QUESTION # 143
CASE STUDY
A company is considering the procurement of an AI system designed to enhance the security of IT infrastructure. The AI system analyzes how users type on their laptops, including typing speed, rhythm and pressure, to create a unique user profile. This data is then used to authenticate users and ensure that only authorized personnel can access sensitive resources.
All of the following are obligations of the company as a data controller when implementing its AI system EXCEPT?
Answer: C
Explanation:
The correct answer is A. While location of processors may have implications (such as for data transfers under GDPR), there is no absolute requirement that third-party processors be based in the same country.
From the AI Governance in Practice Report 2024 and ILT Guide:
"Data controllers are responsible for ensuring that third-party processors have adequate protections, but not necessarily that they reside in the same jurisdiction. What is required is legal safeguards (e.g., SCCs) for international transfers, not same-country location." In contrast, DPIAs, DSARs, and implementation of technical/organizational safeguards are explicitly required under GDPR and responsible AI frameworks.
NEW QUESTION # 144
A company has developed a proprietary AI model that analyzes consumer online behavior and predicts what prices consumers would be willing to pay for certain products, so that retailers may modify pricing accordingly. To test the model, the company has:
Performed an impact assessment
Conducted repeatability tests
Exposed the model to edge cases and potential malicious input
Conducted adversarial testing to identify security threats
Assessed and mitigated discrimination risks
Which additional responsible AI principle has the company failed to assess?
Answer: D
Explanation:
The correct answer is D because the company has already addressed several key responsible AI principles, including fairness through discrimination risk mitigation, robustness through adversarial and edge-case testing, and reliability via repeatability testing. However, there is no indication that the company has addressed transparency, which involves providing clear information about how the model operates, how pricing decisions are made, and how outputs may affect consumers. Transparency is a critical AI governance principle, especially in consumer-facing applications like dynamic pricing, where decisions can significantly impact individuals. Governance frameworks emphasize that users and stakeholders should be informed about AI-driven decisions and their implications. Without transparency, even technically sound and fair systems may lack trustworthiness and fail to meet regulatory or ethical expectations.
NEW QUESTION # 145
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