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The correct answer is C. This action ties directly into principles of data minimization, purpose limitation, and lawfulness of processing, which are central to privacy and AI governance.

From the AIGP Body of Knowledge, Section on Privacy Considerations:

“Personal data must only be processed for specified and lawful purposes. Organizations must consider whether they have a legal basis for processing such data under data protection laws like the GDPR or CCPA.”

Additionally, AI Governance in Practice Report 2024 emphasizes:

“One of the most significant challenges when designing and developing AI systems is ensuring the data used is appropriate for the intended purpose… Managing unnecessary data, especially data that may contain sensitive attributes, can increase risk.”

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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.

According to the EU AI Act, providers of high-risk AI systems are required to register with an EU oversight agency before these systems can be placed on the market. This requirement is part of the Act's framework to ensure that high-risk AI systems comply with stringent safety, transparency, and accountability standards. High-risk systems are those that pose significant risks to health, safety, or fundamental rights. Registration with oversight agencies helps facilitate ongoing monitoring and enforcement of compliance with the Act's provisions. Systems categorized under other criteria, such as those trained on sensitive personal data or exhibiting "strong" general intelligence, also fall under scrutiny but are primarily covered under different regulatory requirements or classifications.

The OECD's Ethical AI Governance Framework aims to ensure that AI development and deployment are carried out ethically while fostering innovation. The framework includes principles like transparency, accountability, and human rights protections to prevent societal harm. It does not focus solely on technical design or post-deployment monitoring (C), nor does it establish industry-specific requirements (B). While explainability is important, the primary goal is to balance innovation with ethical considerations (D).