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IAPP AIGP Exam Syllabus Topics:

Topic	Details
Topic 1	Understanding How Current Laws Apply to AI Systems: It focuses on laws that govern the use of artificial intelligence.
Topic 2	Understanding the Existing and Emerging AI Laws and Standards: This topic discusses global AI-specific laws such as the EU AI Act and Canada’s Bill C-27.
Topic 3	Contemplating Ongoing Issues and Concerns: The topic focuses on issues around AI governance.
Topic 4	Understanding the AI Development Life Cycle: The topic outlines the context in which AI risks are managed.
Topic 5	Understanding the Foundations of Artificial Intelligence: This topic defines AI and machine learning. It also provides an overview of the different types of AI systems and their use cases.

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IAPP Certified Artificial Intelligence Governance Professional Sample Questions (Q77-Q82):

NEW QUESTION # 77
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?

A. Consider the Al recommendation as part of the criminal investigation.
B. Confirm the Al recommendation prior to sentencing.
C. Ensure an accused is given notice that the Al system was used.
D. Explain to the accused how the Al system works.

Answer: A

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 # 78
According to the Singapore Model Al Governance Framework, all of the following are recommended measures to promote the responsible use of Al EXCEPT?

A. Adapting the existing governance structure algorithmic decision-making.
B. Employing human-over-the-loop protocols for high-risk systems.
C. Determining the level of human involvement in algorithmic decision-making.
D. Establishing communications and collaboration among stakeholders.

Answer: B

Explanation:
The Singapore Model AI Governance Framework recommends several measures to promote the responsible use of AI, such as determining the level of human involvement in decision-making, adapting governance structures, and establishing communications and collaboration among stakeholders. However, employing human-over-the-loop protocols is not specifically mentioned in this framework. The focus is more on integrating human oversight appropriately within the decision-making process rather than exclusively employing such protocols. Reference: AIGP Body of Knowledge, section on AI governance frameworks.

NEW QUESTION # 79
A company plans on procuring a tool from an Al provider for its employees to use for certain business purposes.
Which contractual provision would best protect the company's intellectual property in the tool, including training and testing data?

A. The provider willdefend and indemnify the company against infringement claims.
B. The provider willwarrant that the tool will work as intended.
C. The provider willgive privacy notice to individuals before using their personal data to train or test the tool.
D. The provider willobtain and maintain insurance to cover potential claims.

Answer: A

Explanation:
To protect the company's intellectual property, the most pertinent contractual provision is ensuring that the AI provider will defend and indemnify the company against infringement claims. This clause means the provider will take responsibility for any intellectual property disputes that arise, thereby safeguarding the company from potential legal and financial repercussions related to the use of the tool. Other options, while beneficial, do not directly address the protection of intellectual property. This concept is detailed in the contractual best practices section of the IAPP AIGP Body of Knowledge.

NEW QUESTION # 80
Under the NIST Al Risk Management Framework, all of the following are defined as characteristics of trustworthy Al EXCEPT?

A. Explainable and Interpretable.
B. Accountable and Transparent.
C. Tested and Effective.
D. Secure and Resilient.

Answer: C

Explanation:
The NIST AI Risk Management Framework outlines several characteristics of trustworthy AI, including being secure and resilient, explainable and interpretable, and accountable and transparent. While being tested and effective is important, it is not explicitly listed as a characteristic of trustworthy AI in the NIST framework.
The focus is more on the system's ability to function safely, securely, and transparently in a way that stakeholders can understand and trust. Reference: AIGP Body of Knowledge, NIST AI RMF section.

NEW QUESTION # 81
CASE STUDY
Please use the following answer the next question:
A mid-size US healthcare network has decided to develop an Al solution to detect a type of cancer that is most likely arise in adults. Specifically, the healthcare network intends to create a recognition algorithm that will perform an initial review of all imaging and then route records a radiologist for secondary review pursuant agreed-upon criteria (e.g., a confidence score below a threshold).
To date, the healthcare network has taken the following steps: defined its Al ethical principles: conducted discovery to identify the intended uses and success criteria for the system: established an Al governance committee; assembled a broad, crossfunctional team with clear roles and responsibilities; and created policies and procedures to document standards, workflows, timelines and risk thresholds during the project.
The healthcare network intends to retain a cloud provider to host the solution and a consulting firm to help develop the algorithm using the healthcare network's existing data and de-identified data that is licensed from a large US clinical research partner.
In the design phase, what is the most important step for the healthcare network to take when mapping its existing data to the clinical research partner data?

A. Ensure the data is labeled and formatted.
B. Identify fits and gaps in the combined data.
C. Evaluate the country of origin of the data.
D. Apply privacy-enhancing technologies to the data.

Answer: B

Explanation:
In the design phase of integrating data from different sources, identifying fits and gaps is crucial. This process involves understanding how well the data from the clinical research partner aligns with the healthcare network's existing data. It ensures that the combined data set is coherent and can be effectively used for training the AI algorithm. This step helps in spotting any discrepancies, inconsistencies, or missing data that might affect the performance and accuracy of the AI model. It directly addresses the integrity and compatibility of the data, which is foundational before applying any privacy-enhancing technologies, labeling, or evaluating the origin of the data. Reference: AIGP Body of Knowledge on Data Integration and Quality.

NEW QUESTION # 82
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