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| Section | Objectives |
|---|---|
| Topic 1: Regulatory and Legal Frameworks for AI | - Global AI governance regulations
|
| Topic 2: AI Risk Management and Impact Assessment | - Risk identification and mitigation
|
| Topic 3: AI Lifecycle Governance Implementation | - Operational governance controls
|
| Topic 4: Foundations of AI Systems and Governance | - AI system concepts, lifecycle, and terminology
|
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NEW QUESTION # 183
A bank is aiming to comply with ISO/IEC 42005:2025, and is studying how to adopt the standard in light of a new AI customer service system that it would like to implement.
In addition to the risk management process the bank already has in place to assess the risks of any potential new systems, which of the following actions is the most effective in adopting the ISO/IEC 42005:2025 standard?
Answer: B
Explanation:
The correct answer is B because ISO/IEC 42005 emphasizes integrating AI risk management into existing enterprise risk management frameworks rather than creating siloed or duplicative processes. Effective AI governance requires embedding AI-specific risks into established governance structures such as risk registers, controls, and monitoring systems. This ensures consistency, scalability, and alignment with organizational risk practices. Options C and D introduce parallel or fragmented processes, which contradict the principle of integrated governance and may create inefficiencies or gaps. Option A focuses only on data collection and does not address governance integration. The AI Governance in Practice Report highlights that organizations should incorporate AI risks into broader enterprise risk management and maintain unified risk registers to ensure visibility, accountability, and coordinated mitigation across the organization.
NEW QUESTION # 184
Your management consulting firm is planning to use an AI system to support its employees.
Which category of operator applies to the firm in this context?
Answer: D
Explanation:
Under the EU AI Act, a deployer is a natural or legal person, public authority, agency, or other body that uses an AI system under its authority, except where the system is used in a personal, non-professional activity. The consulting firm is using an existing AI system to support its employees and is therefore acting as a deployer. It is not a provider because the scenario does not state that the firm develops the AI system, has it developed, or places it on the market under its own name or trademark. It is not a distributor because it is not making the system available in the supply chain. An authorized representative acts on behalf of a provider established outside the EU. Consequently, D correctly describes the firm ' s role.
NEW QUESTION # 185
Which of the following most encourages accountability over Al systems?
Answer: D
Explanation:
Defining the roles and responsibilities of AI stakeholders is crucial for encouraging accountability over AI systems. Clear delineation of who is responsible for different aspects of the AI lifecycle ensures that there is a person or team accountable for monitoring, maintaining, and addressing issues that arise. This accountability framework helps in ensuring that ethical standards and regulatory requirements are met, and it facilitates transparency and traceability in AI operations. By assigning specific roles, organizations can better manage and mitigate risks associated with AI deployment and use.
NEW QUESTION # 186
What is the most important reason for documenting risks when developing an AI system?
Answer: B
Explanation:
The most critical reason for documenting AI-related risks is toreduce exposure to legal, regulatory, and reputational liabilities. Clear documentation demonstrates thatrisks were identified, assessed, and addressed, which is essential for accountability and defensibility in the face of audits, litigation, or enforcement actions.
From theAI Governance in Practice Report2025:
"An effective AI governance model is about collective responsibility... which should encompass oversight mechanisms such as privacy, accountability, compliance." (p. 13)
"Accountability... is based on the idea that there should be a person or entity that is ultimately responsible for any harm resulting from the use of the data, algorithm and AI system's underlying processes." (p. 28) While transparency, alignment with standards, and knowledge sharing are all secondary benefits,risk documentation's primary role is liability mitigation.
NEW QUESTION # 187
CASE STUDY
Please use the following to answer the next question:
A small local flower delivery company operates a few stores and has a limited IT budget. To reduce the time spent on customer service, which is a major drain on employee time, the company plans to implement a simple but high-performance generative AI chatbot on its website. The chatbot will provide real-time, fact- based responses to customer inquiries and assist with order processing, helping to reduce incoming phone calls.
The company currently uses a single on-premises server for its order database and email system and has not yet partnered with a cloud provider.
An internal data privacy policy governs the use of customer data. This policy, written before the adoption of AI, allows the use or transfer of customer data beyond name and contact information but requires that all such data be deleted after the order is completed. The company prefers to maintain this policy without changes.
What deployment option is the simplest, quickest, and most cost-effective option across the various potential AI models for this particular company?
Answer: C
Explanation:
Software-as-a-Service accessed through an API is the most practical deployment approach for a small organization with limited IT infrastructure and budget. SaaS allows the company to consume a provider- managed application without purchasing and maintaining the substantial computing infrastructure normally needed for modern generative AI. Under NIST ' s cloud-computing model, SaaS consumers use provider applications while the provider manages the underlying network, servers, operating systems, storage, and much of the supporting infrastructure. This makes implementation comparatively rapid and scalable. Running the model on the existing on-premises server could require hardware upgrades and specialized maintenance.
A private-cloud deployment introduces additional infrastructure and administrative complexity. Edge deployment on customers ' devices would also create substantial technical and compatibility challenges.
Therefore, considering the company ' s resources and desired speed of deployment, C is the strongest option.
NEW QUESTION # 188
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