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| Section | Objectives |
|---|---|
| Regulatory and Legal Frameworks for AI | - Global AI governance regulations
|
| AI Lifecycle Governance Implementation | - Operational governance controls
|
| Foundations of AI Systems and Governance | - Governance principles and accountability
|
| AI Risk Management and Impact Assessment | - Risk identification and mitigation
|
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NEW QUESTION # 156
A company developing and deploying its own AI model would perform all of the following steps to monitor and evaluate the model's performance EXCEPT?
Answer: D
Explanation:
While transparency is encouraged,publicly disclosing forecasts of secondary harmsisnot a required or standard practicefor internal performance evaluation. Risk assessments and reporting typically remaininternal or shared with regulators.
From theAI Governance in Practice Report2025:
"Organizations must assess secondary risks... but disclosure is subject to context, regulatory requirements, and risk management discretion." (p. 30)
NEW QUESTION # 157
Scenario:
A company is using different types of AI systems to enhance consumer engagement. These include chatbots, recommendation engines, and automated content generation tools.
Which of the following situations would be least likely to raise concerns under existing consumer protection laws?
Answer: B
Explanation:
The correct answer is D. Personalized content and advertisements, as long as properly disclosed and non- deceptive, are not generally a consumer protection issue under current legal regimes.
From the AI Governance in Practice Report 2024 (Consumer Protection Section):
"Standard practices like targeted advertising and recommendations are widely accepted provided they comply with transparency and consent requirements." Meanwhile, credit decision-making and misleading AI performance claims (Answers A and B) have already led to regulatory enforcement.
The AIGP ILT Guide highlights:
"Deceptive claims, biased financial decisions, and unauthorized data use may violate consumer protection and privacy laws. Advertising personalization is routine but must be disclosed appropriately."
NEW QUESTION # 158
What is the best method to proactively train an LLM so that there is mathematical proof that no specific piece of training data has more than a negligible effect on the model or its output?
Answer: D
Explanation:
Differential privacy is a technique used to ensure that the inclusion or exclusion of a single data point does not significantly affect the outcome of any analysis, providing a way to mathematically prove that no specific piece of training data has more than a negligible effect on the model or its output. This is achieved by introducing randomness into the data or the algorithms processing the data. In the context of training large language models (LLMs), differential privacy helps in protecting individual data points while still enabling the model to learn effectively. By adding noise to the training process, differential privacy provides strong guarantees about the privacy of the training data.
NEW QUESTION # 159
CASE STUDY
Please use the following answer the next question:
A local police department in the United States procured an Al system to monitor and analyze social media feeds, online marketplaces and other sources of public information to detect evidence of illegal activities (e.g., sale of drugs or stolen goods). The Al system works by surveilling the public sites in order to identify individuals that are likely to have committed a crime. It cross-references the individuals against data maintained by law enforcement and then assigns a percentage score of the likelihood of criminal activity based on certain factors like previous criminal history, location, time, race and gender.
The police department retained a third-party consultant assist in the procurement process, specifically to evaluate two finalists. Each of the vendors provided information about their system's accuracy rates, the diversity of their training data and how their system works. The consultant determined that the first vendor's system has a higher accuracy rate and based on this information, recommended this vendor to the police department.
The police department chose the first vendor and implemented its Al system. As part of the implementation, the department and consultant created a usage policy for the system, which includes training police officers on how the system works and how to incorporate it into their investigation process.
The police department has now been using the Al system for a year. An internal review has found that every time the system scored a likelihood of criminal activity at or above 90%, the police investigation subsequently confirmed that the individual had, in fact, committed a crime. Based on these results, the police department wants to forego investigations for cases where the Al system gives a score of at least 90% and proceed directly with an arrest.
The best human oversight mechanism for the police department to implement is that a police officer should?
Answer: C
Explanation:
The best human oversight mechanism for the police department to implement is for a police officer to consider the AI recommendation as part of the criminal investigation. This ensures that the AI system's output is used as a tool to aid human decision-making rather than replace it. The police officer should integrate the AI's insights with other evidence and contextual information to make informed decisions, maintaining a balance between technological aid and human judgment. Reference: AIGP Body of Knowledge on AI Integration and Human Oversight.
NEW QUESTION # 160
Scenario:
A global organization wants to align with international frameworks on AI governance. They are reviewing guidance from the OECD on how to incorporate broader governance tools into their AI program.
Codes of conductandcollective agreementsare what type of assessment tools as defined by theOrganization for Economic Cooperation and Development (OECD)?
Answer: C
Explanation:
The correct answer isB - Procedural. TheOECD Framework for Classifying AI Systemscategorizescodes of conduct and collective agreementsasprocedural toolsbecause they guide internal governance and decision-making processes.
From the AIGP ILT Participant Guide - Global Governance Models:
"Procedural tools include internal codes of conduct, collective agreements, and procedural audits that guide governance without necessarily involving technical measurement." AI Governance in Practice Report 2025 elaborates:
"These procedural tools support internal accountability mechanisms and ethics compliance frameworks... they are part of soft governance." These toolsdo not measure or analyze technical performance, hence they arenot technical or analytic.
NEW QUESTION # 161
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