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NEW QUESTION # 49
MULTI-SELECT
Please select 3 of the 5 options below. No partial credit will be given.
What are the roles and responsibilities of deployers of a proprietary model?
- A. Ethical design.
- B. Technical performance.
- C. System documentation.
- D. Regulatory compliance.
- E. Ethical testing.
Answer: B,D,E
Explanation:
Deployers of proprietary models arenot responsible for design, but they are accountable for how the system performsin their context of use, including ensuring ethical behavior, performance, and legal compliance.
From theAI Governance in Practice Report 2024:
"Deployers of AI systems must take reasonable steps to ensure that systems are used ethically, perform safely, and align with applicable laws and standards." (p. 11-12)
"Operational governance... includes performance monitoring protocols, incident management plans, and regulatory oversight." (p. 12) Thus:
* #A. Ethical testing- Required to mitigate misuse and unintended harms.
* #B. Ethical design- Belongs todevelopers/providers, not deployers.
* #C. Technical performance- Deployers must ensure that AI performs as expected.
* #D. System documentation- This is theprovider'sobligation.
* #E. Regulatory compliance- Deployers must ensure system use complies with applicable laws.
NEW QUESTION # 50
What is the primary purpose of conducting ethical red-teaming on an Al system?
- A. To identify security vulnerabilities.
- B. To improve the model's accuracy.
- C. To ensure compliance with applicable law.
- D. To simulate model risk scenarios.
Answer: D
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 # 51
An Al system that maintains its level of performance within defined acceptable limits despite real world or adversarial conditions would be described as?
- A. Robust.
- B. Resilient.
- C. Reinforced.
- D. Reliable.
Answer: B
Explanation:
An AI system that maintains its level of performance within defined acceptable limits despite real-world or adversarial conditions is described as resilient. Resilience in AI refers to the system's ability to withstand and recover from unexpected challenges, such as cyber-attacks, hardware failures, or unusual input data. This characteristic ensures that the AI system can continue to function effectively and reliably in various conditions, maintaining performance and integrity. Robustness, on the other hand, focuses on the system's strength against errors, while reliability ensures consistent performance over time. Resilience combines these aspects with the capacity to adapt and recover.
NEW QUESTION # 52
During the first month when the company monitors the model for bias, it is most important to?
- A. Continue disparity testing.
- B. Provide regular awareness training.
- C. Document the results of final decisions made by the human underwriter.
- D. Analyze the quality of the training and testing data.
Answer: A
Explanation:
Theinitial deployment phaseof an AI model is critical forpost-deployment monitoring. When tracking for bias, the most important task is tocontinue disparity testingto determine whether outputs differ across protected groups.
From theAI Governance in Practice Report 2024:
"Performance monitoring protocols... should include mechanisms to assess and measure disparities in outcomes across different demographic groups." (p. 12)
"Bias may not be evident during pre-deployment testing but can emerge in real-world use." (p. 41)
* B. Awareness trainingis helpful, but not a technical bias mitigation activity.
* C. Analyzing training datais apre-deploymenttask.
* D. Documenting human decisionsmay support auditability but doesn't detect bias in AI outputs.
NEW QUESTION # 53
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. Impose a ban on the use of generative Al in agencies that protect national security.
- D. Limit access of generative Al to engineers and developers.
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 # 54
What is the primary purpose of an Al impact assessment?
- A. To identify and measure the benefits of an Al system.
- B. To define and document the roles and responsibilities of Al stakeholders.
- C. To define and evaluate the legal risks associated with developing an Al system.
- D. Anticipate and manage the potential risks and harms of an Al system.
Answer: D
Explanation:
The primary purpose of an AI impact assessment is to anticipate and manage the potential risks and harms of an AI system. This includes identifying the possible negative outcomes and implementing measures to mitigate these risks. This process helps ensure that AI systems are developed and deployed in a manner that is ethically and socially responsible, addressing concerns such as bias, fairness, transparency, and accountability.
The assessment often involves a thorough evaluation of the AI system's design, data inputs, outputs, and the potential impact on various stakeholders. This approach is crucial for maintaining public trust and adherence to regulatory requirements.
NEW QUESTION # 55
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.
What is the best reason the police department should continue to perform investigations even if the Al system scores an individual's likelihood of criminal activity at or above 90%?
- A. Because investigations may uncover information relevant to sentencing.
- B. Because Al systems that affect fundamental civil rights should not be fully automated.
- C. Because the department did not perform an impact assessment for this intended use.
- D. Because investigations may identify additional individuals involved in the crime.
Answer: B
Explanation:
The best reason for the police department to continue performing investigations even if the AI system scores an individual's likelihood of criminal activity at or above 90% is that AI systems affecting fundamental civil rights should not be fully automated. Human oversight is essential to ensure that decisions impacting civil liberties are made with due consideration of context and mitigating factors that an AI might not fully appreciate. This approach ensures fairness, accountability, and adherence to legal standards. Reference: AIGP Body of Knowledge on AI Ethics and Human Oversight.
NEW QUESTION # 56
What is the technique to remove the effects of improperly used data from an ML system?
- A. Data cleansing.
- B. Model inversion.
- C. Model disgorgement.
- D. Data de-duplication.
Answer: C
Explanation:
Model disgorgement is the technique used to remove the effects of improperly used data from an ML system.
This process involves retraining or adjusting the model to eliminate any biases or inaccuracies introduced by the inappropriate data. It ensures that the model's outputs are not influenced by data that was not meant to be used or was used incorrectly. Reference: AIGP Body of Knowledge on Data Management and Model Integrity.
NEW QUESTION # 57
Which of the following use cases would be best served by a non-AI solution?
- A. A customer service agency wants automate answers to common questions.
- B. A business analyst wants to forecast future cost overruns and underruns.
- C. A non-profit wants to develop a social media presence.
OB. An e-commerce provider wants to make personalized recommendations.
Answer: C
Explanation:
Developing a social media presence for a non-profit is best served by non-AI solutions. This task primarily involves content creation, community engagement, and strategic planning, which are effectively managed by human expertise and traditional marketing tools. AI is more suitable for tasks requiring automation, large-scale data analysis, and personalized recommendations, such as e-commerce personalization, forecasting cost overruns, or automating customer service responses. Reference: AIGP Body of Knowledge on AI Use Cases and Applications.
NEW QUESTION # 58
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. Office of Science and Technology Policy (OSTP).
- B. Department of Homeland Security (DHS).
- C. National Science and Technology Council (NSTC).
- D. National Institute of Standards and Technology (NIST).
Answer: D
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 # 59
A US company has developed an Al system, CrimeBuster 9619, that collects information about incarcerated individuals to help parole boards predict whether someone is likely to commit another crime if released from prison.
When considering expanding to the EU market, this type of technology would?
- A. Require the company to register the tool with the EU database.
- B. Require a detailed conformity assessment.
- C. Be banned under the EU Al Act.
- D. Be subject approval by the relevant EU authority.
Answer: C
Explanation:
Under the EU AI Act, high-risk AI systems like CrimeBuster 9619 would require a detailed conformity assessment before being deployed in the EU market. This assessment ensures that the AI system complies with all relevant regulations and standards, addressing potential risks related to privacy, security, and discrimination. The company would not need to register the tool with the EU database (A), seek approval from an EU authority (B), or face a ban (D) as long as it meets the necessary conformity requirements.
NEW QUESTION # 60
The planning phase of the Al life cycle articulates all of the following EXCEPT the?
- A. Choice of the architecture.
- B. Approach to governance.
- C. Objective of the model.
- D. Context in which the model will operate.
Answer: B
Explanation:
The planning phase of the AI life cycle typically includes defining the objective of the model, choosing the appropriate architecture, and understanding the context in which the model will operate. However, the approach to governance is usually established as part of the overall AI governance framework, not specifically within the planning phase. Governance encompasses broader organizational policies and procedures that ensure AI development and deployment align with legal, ethical, and operational standards. Reference: AIGP Body of Knowledge, AI lifecycle planning phase section.
NEW QUESTION # 61
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. Office of Science and Technology Policy (OSTP).
- B. Department of Homeland Security (DHS).
- C. National Science and Technology Council (NSTC).
- D. National Institute of Standards and Technology (NIST).
Answer: D
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 # 62
Which risk management framework/guide/standard focuses on value-based engineering methodology?
- A. IEEE 7000-2021 Standard Model Process for Addressing Ethical Concerns during System Design.
- B. ISO 31000 Guidelines (Risk Management).
- C. ISO/IEC Guide 51 (Safety).
- D. Council of Europe Human Rights, Democracy, and the Rule of Law Assurance Framework (HUDERIA) for Al Systems.
Answer: A
Explanation:
The IEEE 7000-2021 Standard focuses on a value-based engineering methodology for addressing ethical concerns during system design. This standard guides engineers and organizations in integrating ethical considerations into the design and development processes of AI systems, ensuring that these technologies are developed responsibly and align with human values. Reference: AIGP Study Material, section on risk management frameworks and standards.
NEW QUESTION # 63
Which of the following is NOT a common type of machine learning?
- A. Reinforcement learning.
- B. Unsupervised learning.
- C. Cognitive learning.
- D. Deep learning.
Answer: C
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 # 64
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.
The most significant risk from combining the healthcare network's existing data with the clinical research partner data is?
- A. Security risk.
- B. Privacy risk.
- C. Reputational risk.
- D. Operational risk.
Answer: B
Explanation:
The most significant risk from combining the healthcare network's existing data with the clinical research partner data is privacy risk. Combining data sets, especially in healthcare, often involves handling sensitive information that could lead to privacy breaches if not managed properly. De-identified data can still pose re-identification risks when combined with other data sets. Ensuring privacy involves implementing robust data protection measures, maintaining compliance with privacy regulations such as HIPAA, and conducting thorough privacy impact assessments. Reference: AIGP Body of Knowledge on Data Privacy and Security.
NEW QUESTION # 65
A leading software development company wants to integrate AI-powered chatbots into their customer service platform. After researching various AI models in the market which have been developed by third-party developers, they're considering two options:
Option A - an open-source language model trained on a vast corpus of text data and capable of being trained to respond to natural language inputs.
Option B - a proprietary, generative AI model pre-trained on large data sets, which uses transformer-based architectures to generate human-like responses based on multimodal user input.
Option A would be the best choice for the company because?
- A. It is less expensive to run
- B. It can handle voice commands and is more suitable for phone-based customer support.
- C. It may be better suited for applications requiring customization.
- D. It is built for large-scale, complex dialogues and would be more effective in handling high-volume customer inquiries.
Answer: C
Explanation:
Open-source modelsoffer morecustomization flexibility, allowing organizations to fine-tune or adapt the model tofit their own workflows, branding, or compliance needs- making it preferable when deep control is needed.
From theAI Governance in Practice Report 2024:
"Open-source AI allows organizations to review, adapt, and control model behavior in line with organizational needs and policies." (p. 39)
NEW QUESTION # 66
Scenario:
An organization is planning to deploy a new internal application that uses AI to make automated decisions about individuals. This application will process personal information and may affect individuals' access to certain benefits or opportunities.
Which of the following documents must be updated to ensure transparency?
- A. The organization's website privacy notice
- B. The user privacy notice
- C. The organization's privacy policy
- D. The organization's acceptable use policy
Answer: B
Explanation:
The correct answer is D. Transparency obligations under data protection laws, such as GDPR and most AI governance frameworks, require that users whose data is being processed be directly informed.
From the AIGP ILT Guide (Privacy Module):
"The user privacy notice must be updated to explain the nature of automated processing, the logic involved, and the significance and consequences for the data subject." Also, per AI Governance in Practice Report 2024 (Part III):
"Transparency obligations apply throughout the lifecycle of AI... Individuals must be informed about automated decision-making and profiling that may impact them." Unlike internal policies or general privacy notices, the user privacy notice provides direct transparency to the individual data subjects affected by AI processing.
NEW QUESTION # 67
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