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質問 # 14
What is the main purpose of accountability structures under the Govern function of the NIST Al Risk Management Framework?
正解：A
解説：
The NIST AI Risk Management Framework's Govern function emphasizes the importance of establishing accountability structures that empower and train cross-functional teams. This is crucial because cross-functional teams bring diverse perspectives and expertise, which are essential for effective AI governance and risk management. Training these teams ensures that they are well-equipped to handle their responsibilities and can make informed decisions that align with the organization's AI principles and ethical standards. Reference: NIST AI Risk Management Framework documentation, Govern function section.
質問 # 15
A company is creating a mobile app to enable individuals to upload images and videos, and analyze this data using ML to provide lifestyle improvement recommendations. The signup form has the following data fields:
1.First name
2.Last name
3.Mobile number
4.Email ID
5.New password
6.Date of birth
7.Gender
In addition, the app obtains a device's IP address and location information while in use.
What GDPR privacy principles does this violate?
正解：B
解説：
The GDPR privacy principles that this scenario violates are Purpose Limitation and Data Minimization.
Purpose Limitation requires that personal data be collected for specified, explicit, and legitimate purposes and not further processed in a manner that is incompatible with those purposes. Data Minimization mandates that personal data collected should be adequate, relevant, and limited to what is necessary in relation to the purposes for which they are processed. In this case, collecting extensive personal information (e.g., IP address, location, gender) and potentially using it beyond the necessary scope for the app's functionality could violate these principles by collecting more data than needed and possibly using it for purposes not originally intended.
質問 # 16
What is the primary purpose of an AI impact assessment?
正解：A
解説：
The correct answer is D. AI Impact Assessments are primarily used to identify and manage risks and harms associated with AI systems.
From the AIGP Body of Knowledge:
"The goal of an AI impact assessment is to ensure that risks are identified, evaluated, and mitigated prior to or during development and deployment." As further confirmed in the AI Governance in Practice Report 2024 (Part III):
"Risk-based tools like DPIAs and Algorithmic Impact Assessments help identify potential risks to individuals and society, enabling organizations to implement mitigation plans and safeguards." While benefits may be noted in such assessments, the core objective is to manage risks and promote responsible AI.
質問 # 17
Pursuant to the White House Executive Order of November 2023, who is responsible for creating guidelines to conduct red-teaming tests of Al systems?
正解：A
解説：
The White House Executive Order of November 2023 designates the National Institute of Standards and Technology (NIST) as the responsible body for creating guidelines to conduct red-teaming tests of AI systems. NIST is tasked with developing and providing standards and frameworks to ensure the security, reliability, and ethical deployment of AI systems, including conducting rigorous red-teaming exercises to identify vulnerabilities and assess risks in AI systems.
Reference: AIGP BODY OF KNOWLEDGE, sections on AI governance and regulatory frameworks, and the White House Executive Order of November 2023.
質問 # 18
All of the following are unique characteristics of AI that require a comprehensive approach to governance EXCEPT?
正解：E
解説：
The correct answer is E - Superintelligence.
While the other options (Autonomy, Automation, Adaptability, Speed and Scale) are commonly cited as real- world characteristics that affect governance today, superintelligence remains a theoretical concept.
From the AIGP ILT Guide and AI Governance in Practice Report 2024:
"Core AI characteristics-such as automation, adaptability, speed, and autonomy-require active governance due to their impact on decision-making, legal liability, and risk." However, superintelligence is speculative and not a current feature of AI systems under governance frameworks like the EU AI Act or NIST RMF.
Thus, it's not a current characteristic requiring governance in real-world enterprise settings.
質問 # 19
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