The Far Out Guide To AIGP Preparation Exams

NEW QUESTION 1

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.
Which of the following steps can best mitigate the possibility of discrimination prior to training and testing the Al solution?

• A. Procure more data from clinical research partners.
• B. Engage a third party to perform an audit.
• C. Perform an impact assessment.
• D. Create a bias bounty program.

Answer: C

Explanation:
Performing an impact assessment is the best step to mitigate the possibility of discrimination before training and testing the AI solution. An impact assessment, such as a Data Protection Impact Assessment (DPIA) or Algorithmic Impact Assessment (AIA), helps identify potential biases and discriminatory outcomes that could arise from the AI system. This process involves evaluating the data and the algorithm for fairness, accountability, and transparency. It ensures that any biases in the data are detected and addressed, thus preventing discriminatory practices and promoting ethical AI deployment. Reference: AIGP Body of Knowledge on Ethical AI and Impact Assessments.

NEW QUESTION 2

Pursuant to the White House Executive Order of November 2023, who is responsible for creating guidelines to conduct red-teaming tests of Al systems?

• A. National Institute of Standards and Technology (NIST).
• B. National Science and Technology Council (NSTC).
• C. Office of Science and Technology Policy (OSTP).
• D. Department of Homeland Security (DHS).

Answer: A

Explanation:
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.

NEW QUESTION 3

Which of the following is NOT a common type of machine learning?

• A. Deep learning.
• B. Cognitive learning.
• C. Unsupervised learning.
• D. Reinforcement learning.

Answer: B

Explanation:
The common types of machine learning include supervised learning, unsupervised learning, reinforcement learning, and deep learning. Cognitive learning is not a type of machine learning; rather, it is a term often associated with the broader field of cognitive science and psychology. Reference: AIGP BODY OF KNOWLEDGE and standard AI/ML literature.

NEW QUESTION 4

Which of the following deployments of generative Al best respects intellectual property rights?

• A. The system produces content that is modified to closely resemble copyrightedwork.
• B. The system categorizes and applies filters to content based on licensing terms.
• C. The system provides attribution to creators of publicly available information.
• D. The system produces content that includes trademarks and copyrights.

Answer: B

Explanation:
Respecting intellectual property rights means adhering to licensing terms and ensuring that generated content complies with these terms. A system that categorizes and applies filters based on licensing terms ensures that content is used legally and ethically, respecting the rights of content creators. While providing attribution is important, categorization and application of filters based on licensing terms are more directly tied to compliance with intellectual property laws. This principle is elaborated in the IAPP AIGP Body of Knowledge sections on intellectual property and compliance.

NEW QUESTION 5

All of the following are elements of establishing a global Al governance infrastructure EXCEPT?

• A. Providing training to foster a culture that promotes ethical behavior.
• B. Creating policies and procedures to manage third-partyrisk.
• C. Understanding differences in norms across countries.
• D. Publicly disclosing ethical principles.

Answer: D

Explanation:
Establishing a global AI governance infrastructure involves several key elements, including providing training to foster a culture that promotes ethical behavior, creating policies and procedures to manage third-party risk, and understanding differences in norms across countries. While publicly disclosing ethical principles can enhance transparency and trust, it is not a core element necessary for the establishment of a governance infrastructure. The focus is more on internal processes and structures rather than public disclosure. Reference: AIGP Body of Knowledge on AI Governance and Infrastructure.

NEW QUESTION 6

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?

• A. Purpose Limitation and Data Minimization.
• B. Accountability and Lawfulness.
• C. Transparency and Accuracy.
• D. Integrity and Confidentiality.

Answer: A

Explanation:
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.

NEW QUESTION 7

All of the following are penalties and enforcements outlined in the EU Al Act EXCEPT?

• A. Fines for SMEs and startups will be proportionally capped.
• B. Rules on General Purpose Al will apply after 6 months as a specific provision.
• C. The Al Pact will act as a transitional bridge until the Regulations are fully enacted.
• D. Fines for violations of banned Al applications will be €35 million or 7% global annual turnover (whichever is higher).

Answer: C

Explanation:
The EU AI Act outlines specific penalties and enforcement mechanisms to ensure compliance with its regulations. Among these, fines for violations of banned AI applications can be as high as €35 million or 7% of the global annual turnover of the offending organization, whichever is higher. Proportional caps on fines are applied to SMEs and startups to ensure fairness. General Purpose AI rules are to apply after a 6-month period as a specific provision to ensure that stakeholders have adequate time to comply. However, there is no provision for an "AI Pact" acting as a transitional bridge until the regulations are fully enacted, making option C the correct answer.

NEW QUESTION 8

According to November 2023 White House Executive Order, which of the following best describes the guidance given to governmental agencies on the use of generative Al as a workplace tool?

• A. Limit access to specific uses of generative Al.
• B. Impose a general ban on the use of generative Al.
• C. Limit access of generative Al to engineers and developers.
• D. Impose a ban on the use of generative Al in agencies that protect national security.

Answer: A

Explanation:
The November 2023 White House Executive Order provides guidance that governmental agencies should limit access to specific uses of generative AI. This means that generative AI tools should be used in a controlled manner, where their applications are restricted to well-defined, approved use cases that ensure the security, privacy, and ethical considerations are adequately addressed. This approach allows for the benefits of generative AI to be harnessed while mitigating potential risks and abuses.
Reference: AIGP BODY OF KNOWLEDGE, sections on AI governance and risk
management, and the White House Executive Order of November 2023.

NEW QUESTION 9

Machine learning is best described as a type of algorithm by which?

• A. Systems can mimic human intelligence with the goal of replacing humans.
• B. Systems can automatically improve from experience through predictive patterns.
• C. Statistical inferences are drawn from a sample with the goal of predicting human intelligence.
• D. Previously unknown properties are discovered in data and used to predict and make improvements in the data.

Answer: B

Explanation:
Machine learning (ML) is a subset of artificial intelligence (AI) where systems use data to learn and improve over time without being explicitly programmed. Option B accurately describes machine learning by stating that systems can automatically improve from
experience through predictive patterns. This aligns with the fundamental concept of ML where algorithms analyze data, recognize patterns, and make decisions with minimal human intervention. Reference: AIGP BODY OF KNOWLEDGE, which covers the basics of AI and machine learning concepts.

NEW QUESTION 10

An EU bank intends to launch a multi-modal Al platform for customer engagement and automated decision-making assist with the opening of bank accounts. The platform has been subject to thorough risk assessments and testing, where it proves to be effective in not discriminating against any individual on the basis of a protected class.
What additional obligations must the bank fulfill prior to deployment?

• A. The bank must obtain explicit consent from users under the privacy Directive.
• B. The bank must disclose how the Al system works under the Ell Digital Services Act.
• C. The bank must subject the Al system an adequacy decision and publish its appropriate safeguards.
• D. The bank must disclose the use of the Al system and implement suitable measures for users to contest automated decision-making.

Answer: D

Explanation:
Under the EU regulations, particularly the GDPR, banks using AI for decision-making must inform users about the use of AI and provide mechanisms for users to contest decisions. This is part of ensuring transparency and accountability in automated processing. Explicit consent under the privacy directive (A) and disclosing under the Digital Services Act (B) are not specifically required in this context. An adequacy decision is related to data transfers outside the EU (C).

NEW QUESTION 11

Which of the following best defines an "Al model"?

• A. A system that applies defined rules to execute tasks.
• B. A system of controls that is used to govern an Al algorithm.
• C. A corpus of data which an Al algorithm analyzes to make predictions.
• D. A program that has been trained on a set of data to find patterns within the data.

Answer: D

Explanation:
An AI model is best defined as a program that has been trained on a set of data to find patterns within that data. This definition captures the essence of machine learning, where the model learns from the data to make predictions or decisions. Reference: AIGP BODY OF KNOWLEDGE, which provides a detailed explanation of AI models and their training processes.

NEW QUESTION 12

Which of the following steps occurs in the design phase of the Al life cycle?

• A. Data augmentation.
• B. Model explainability.
• C. Risk impact estimation.
• D. Performance evaluation.

Answer: C

Explanation:
Risk impact estimation occurs in the design phase of the AI life cycle. This step involves evaluating potential risks associated with the AI system and estimating their impacts to ensure that appropriate mitigation strategies are in place. It helps in identifying and addressing potential issues early in the design process, ensuring the development of a robust and reliable AI system. Reference: AIGP Body of Knowledge on AI Design and Risk Management.

NEW QUESTION 13

CASE STUDY
Please use the following answer the next question:
ABC Corp, is a leading insurance provider offering a range of coverage options to individuals. ABC has decided to utilize artificial intelligence to streamline and improve its customer acquisition and underwriting process, including the accuracy and efficiency of pricing policies.
ABC has engaged a cloud provider to utilize and fine-tune its pre-trained, general purpose large language model (“LLM”). In particular, ABC intends to use its historical customer data—including applications, policies, and claims—and proprietary pricing and risk strategies to provide an initial qualification assessment of potential customers, which would then be routed a human underwriter for final review.
ABC and the cloud provider have completed training and testing the LLM, performed a readiness assessment, and made the decision to deploy the LLM into production. ABC has designated an internal compliance team to monitor the model during the first month, specifically to evaluate the accuracy, fairness, and reliability of its output. After the first
month in production, ABC realizes that the LLM declines a higher percentage of women's loan applications due primarily to women historically receiving lower salaries than men.
Which of the following is the most important reason to train the underwriters on the model prior to deployment?

• A. Toprovide a reminder of a right appeal.
• B. Tosolicit on-going feedback on model performance.
• C. Toapply their own judgment to the initial assessment.
• D. Toensure they provide transparency applicants on the model.

Answer: C

Explanation:
Training underwriters on the model prior to deployment is crucial so they can apply their own judgment to the initial assessment. While AI models can streamline the process, human judgment is still essential to catch nuances that the model might miss or to account for any biases or errors in the model's decision-making process.
Reference: The AIGP Body of Knowledge emphasizes the importance of human oversight
in AI systems, particularly in high-stakes areas such as underwriting and loan approvals. Human underwriters can provide a critical review and ensure that the model's assessments are accurate and fair, integrating their expertise and understanding of complex cases.

NEW QUESTION 14

A company initially intended to use a large data set containing personal information to train an Al model. After consideration, the company determined that it can derive enough value from the data set without any personal information and permanently obfuscated all personal data elements before training the model.
This is an example of applying which privacy-enhancing technique (PET)?

• A. Anonymization.
• B. Pseudonymization.
• C. Differential privacy.
• D. Federated learning.

Answer: A

Explanation:
Anonymization is a privacy-enhancing technique that involves removing or permanently altering personal data elements to prevent the identification of individuals. In this case, the company obfuscated all personal data elements before training the model, which aligns with the definition of anonymization. This ensures that the data cannot be traced back to individuals, thereby protecting their privacy while still allowing the company to derive value from the dataset. Reference: AIGP Body of Knowledge, privacy-enhancing techniques section.

NEW QUESTION 15

The framework set forth in the White House Blueprint for an Al Bill of Rights addresses all of the following EXCEPT?

• A. Human alternatives, consideration and fallback.
• B. High-risk mitigation standards.
• C. Safe and effective systems.
• D. Data privacy.

Answer: B

Explanation:
The White House Blueprint for an AI Bill of Rights focuses on protecting civil rights, privacy, and ensuring AI systems are safe and effective. It includes principles like data privacy (D), human alternatives (A), and safe and effective systems (C). However, it does not specifically address high-risk mitigation standards as a distinct category (B).

NEW QUESTION 16

To maintain fairness in a deployed system, it is most important to?

• A. Protect against loss of personal data in the model.
• B. Monitor for data drift that may affect performance and accuracy.
• C. Detect anomalies outside established metrics that require new training data.
• D. Optimize computational resources and data to ensure efficiency and scalability.

Answer: B

Explanation:
To maintain fairness in a deployed system, it is crucial to monitor for data drift that may affect performance and accuracy. Data drift occurs when the statistical properties of the input data change over time, which can lead to a decline in model performance. Continuous monitoring and updating of the model with new data ensure that it remains fair and accurate, adapting to any changes in the data distribution. Reference: AIGP Body of Knowledge on Post-Deployment Monitoring and Model Maintenance.

NEW QUESTION 17

Which type of existing assessment could best be leveraged to create an Al impact assessment?

• A. A safety impact assessment.
• B. A privacy impact assessment.
• C. A security impact assessment.
• D. An environmental impact assessment.

Answer: B

Explanation:
A privacy impact assessment (PIA) can be effectively leveraged to create an AI impact assessment. A PIA evaluates the potential privacy risks associated with the use of personal data and helps in implementing measures to mitigate those risks. Since AI systems often involve processing large amounts of personal data, the principles and methodologies of a PIA are highly applicable and can be extended to assess broader impacts, including ethical, social, and legal implications of AI. Reference: AIGP Body of Knowledge on Impact Assessments.

NEW QUESTION 18

Under the Canadian Artificial Intelligence and Data Act, when must the Minister of Innovation, Science and Industry be notified about a high-impact Al system?

• A. When use of the system causes or is likely to cause material harm.
• B. When the algorithmic impact assessment has been completed.
• C. Upon release of a new version of the system.
• D. Upon initial deployment of the system.

Answer: D

Explanation:
According to the Canadian Artificial Intelligence and Data Act, high-impact AI systems must notify the Minister of Innovation, Science and Industry upon initial deployment. This requirement ensures that the authorities are aware of the deployment of significant AI systems and can monitor their impacts and compliance with regulatory standards from the outset. This initial notification is crucial for maintaining oversight and ensuring the responsible use of AI technologies. Reference: AIGP Body of Knowledge, domain on AI laws and standards.

NEW QUESTION 19

What is the primary purpose of conducting ethical red-teaming on an Al system?

• A. To improve the model's accuracy.
• B. To simulate model risk scenarios.
• C. To identify security vulnerabilities.
• D. To ensure compliance with applicable law.

Answer: B

Explanation:
The primary purpose of conducting ethical red-teaming on an AI system is to simulate model risk scenarios. Ethical red-teaming involves rigorously testing the AI system to identify potential weaknesses, biases, and vulnerabilities by simulating real-world attack or failure scenarios. This helps in proactively addressing issues that could compromise the system's reliability, fairness, and security. Reference: AIGP Body of Knowledge on AI Risk Management and Ethical AI Practices.

NEW QUESTION 20

Which of the following Al uses is best described as human-centric?

• A. Pattern recognition algorithms are used to improve the accuracy of weather predictions, which benefits many industries and everyday life.
• B. Autonomous robots are used to move products within a warehouse, allowing human workers to reduce physical strain and alleviate monotony.
• C. Machine learning is used for demand forecasting and inventory management, ensuring that consumers can find products they want when they want them.
• D. Virtual assistants are used adapt educational content and teaching methods to individuals, offering personalized recommendations based on ability and needs.

Answer: D

Explanation:
Human-centric AI focuses on improving the human experience by addressing individual needs and enhancing human capabilities. Option D exemplifies this by using virtual assistants to tailor educational content to each student's unique abilities and needs, thereby supporting personalized learning and improving educational outcomes. This use case directly benefits individuals by providing customized assistance and adapting to their learning pace and style, aligning with the principles of human-centric AI.
Reference: AIGP BODY OF KNOWLEDGE, sections on trustworthy AI and human-centric AI principles.

NEW QUESTION 21
......