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NEW QUESTION # 71
What is the 1956 Dartmouth summer research project on Al best known as?
- A. A meeting focused on the impacts of the launch of the first mass-produced computer.
- B. A research project to create a test for machine intelligence.
- C. A research project on the impacts of technology on society.
- D. A meeting focused on the founding of the Al field.
Answer: D
Explanation:
The 1956 Dartmouth summer research project on AI is best known as a meeting focused on the founding of the AI field. This conference is historically significant because it marked the formal beginning of artificial intelligence as an academic discipline. The term "artificial intelligence" was coined during this event, and it laid the foundation for future research and development in AI.
Reference: The AIGP Body of Knowledge highlights the importance of the Dartmouth Conference as a pivotal moment in the history of AI, which established AI as a distinct field of study and research.
NEW QUESTION # 72
Which of the following disclosures is NOT required for an EU organization that developed and deployed a high-risk Al system?
- A. The fact that an Al system is being used.
- B. The location(s) where data is stored.
- C. How an individual may contest a decision.
- D. The human oversight measures employed.
Answer: B
Explanation:
Under the EU AI Act, organizations that develop and deploy high-risk AI systems are required to provide several key disclosures to ensure transparency and accountability. These include the human oversight measures employed, how individuals can contest decisions made by the AI system, and informing individuals that an AI system is being used. However, there is no specific requirement to disclose the exact locations where data is stored. The focus of the Act is on the transparency of the AI system's operation and its impact on individuals, rather than on the technical details of data storage locations.
NEW QUESTION # 73
All of the following are common optimization techniques in deep learning to determine weights that represent the strength of the connection between artificial neurons EXCEPT?
- A. Momentum, which improves the convergence speed and stability of neural network training.
- B. Gradient descent, which initially sets weights arbitrary values, and then at each step changes them.
- C. Autoregression, which analyzes and makes predictions about time-series data.
- D. Backpropagation, which starts from the last layer working backwards.
Answer: C
Explanation:
Autoregression is not a common optimization technique in deep learning to determine weights for artificial neurons. Common techniques include gradient descent, momentum, and backpropagation. Autoregression is more commonly associated with time-series analysis and forecasting rather than neural network optimization.
Reference: AIGP BODY OF KNOWLEDGE, which discusses common optimization techniques used in deep learning.
NEW QUESTION # 74
The planning phase of the Al life cycle articulates all of the following EXCEPT the?
- A. Approach to governance.
- B. Context in which the model will operate.
- C. Choice of the architecture.
- D. Objective of the model.
Answer: A
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 # 75
Scenario:
A European AI technology company was found to be non-compliant with certain provisions of the EU AI Act.
The regulator is considering penalties under the enforcement provisions of the regulation.
According to the EU AI Act, which of the following non-compliance examples could lead to fines of up to €
15 million or 3% of annual worldwide turnover (whichever is higher)?
- A. In case of breach of a provider's obligations for high-risk AI systems
- B. In case of AI Act prohibitions
- C. In case of the supply of misleading information to notified bodies in reply to a request
- D. In case of a breach of AI Act prohibition by the Union institutions, bodies, offices and agencies
Answer: A
Explanation:
The correct answer is B. The EU AI Act assigns a tiered penalty system based on the severity of the violation. A breach of obligations related to high-risk AI systems falls into the mid-tier category, triggering fines of €15 million or 3% of annual global turnover.
From the AIGP ILT Guide - EU AI Act Module:
"Providers of high-risk AI systems must comply with strict documentation, testing, monitoring, and registration obligations. Breaches of these result in significant fines of up to €15 million or 3% of turnover." AI Governance in Practice Report 2024 supports this:
"Non-compliance with obligations under Title III (high-risk systems) leads to financial penalties under Article
71(3) of the EU AI Act."
Note: The highest penalty (€35 million or 7%) applies to prohibited AI uses, not to obligations for high- risk systems.
NEW QUESTION # 76
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. Previously unknown properties are discovered in data and used to predict and make improvements in the data.
- C. Statistical inferences are drawn from a sample with the goal of predicting human intelligence.
- D. Systems can automatically improve from experience through predictive patterns.
Answer: D
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 # 77
Which of the following steps occurs in the design phase of the Al life cycle?
- A. Data augmentation.
- B. Performance evaluation.
- C. Risk impact estimation.
- D. Model explainability.
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 # 78
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 conduct and collective agreements are what type of assessment tools as defined by the Organization for Economic Cooperation and Development (OECD)?
- A. Procedural
- B. Technical
- C. Analytic
- D. Educational
Answer: A
Explanation:
The correct answer is B - Procedural. The OECD Framework for Classifying AI Systems categorizes codes of conduct and collective agreements as procedural tools because 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 2024 elaborates:
"These procedural tools support internal accountability mechanisms and ethics compliance frameworks...
they are part of soft governance."
These tools do not measure or analyze technical performance, hence they are not technical or analytic.
NEW QUESTION # 79
CASE STUDY
Please use the following answer the next question:
XYZ Corp., a premier payroll services company that employs thousands of people globally, is embarking on a new hiring campaign and wants to implement policies and procedures to identify and retain the best talent. The new talent will help the company's product team expand its payroll offerings to companies in the healthcare and transportation sectors, including in Asia.
It has become time consuming and expensive for HR to review all resumes, and they are concerned that human reviewers might be susceptible to bias.
Address these concerns, the company is considering using a third-party Al tool to screen resumes and assist with hiring. They have been talking to several vendors about possibly obtaining a third-party Al-enabled hiring solution, as long as it would achieve its goals and comply with all applicable laws.
The organization has a large procurement team that is responsible for the contracting of technology solutions.
One of the procurement team's goals is to reduce costs, and it often prefers lower-cost solutions. Others within the company are responsible for integrating and deploying technology solutions into the organization's operations in a responsible, cost-effective manner.
The organization is aware of the risks presented by Al hiring tools and wants to mitigate them. It also questions how best to organize and train its existing personnel to use the Al hiring tool responsibly. Their concerns are heightened by the fact that relevant laws vary across jurisdictions and continue to change.
Which other stakeholder groups should be involved in the selection and implementation of the Al hiring tool?
- A. Finance and Legal.
- B. Litigation and Product Development.
- C. Marketing and Compliance.
- D. Supply Chain and Marketing.
Answer: A
Explanation:
In the selection and implementation of the AI hiring tool, involving Finance and Legal is crucial. The Finance team is essential for assessing cost implications, budget considerations, and financial risks. The Legal team is necessary to ensure compliance with applicable laws and regulations, including those related to data privacy, employment, and anti-discrimination. Involving these stakeholders ensures a comprehensive evaluation of both the financial viability and legal compliance of the AI tool, mitigating potential risks and aligning with organizational objectives and regulatory requirements.
NEW QUESTION # 80
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 organization's privacy policy
- C. The user privacy notice
- D. The organization's acceptable use policy
Answer: C
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 # 81
A company deploys an AI model for fraud detection in online transactions. During its operation, the model begins to exhibit high rates of false positives, flagging legitimate transactions as fraudulent.
Which is the best step the company should take to address this development?
- A. Conduct training for customer service teams to handle flagged transactions.
- B. Maintain records of all false positives.
- C. Deactivate the model until an assessment is made.
- D. Dedicate more resources to monitor the model.
Answer: C
Explanation:
When an AI system causessignificant false positives, especially in sensitive contexts likefraud detection, the priority is tohalt harmful activityand perform a full assessment. Continued use without understanding the fault may cause furthercustomer harmand legal exposure.
From theAI Governance in Practice Report 2024:
"Incident management plans should enable identification, escalation, and system rollback to prevent continued harm from malfunctioning AI systems." (p. 12, 35)
NEW QUESTION # 82
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 willgive privacy notice to individuals before using their personal data to train or test the tool.
- B. The provider willobtain and maintain insurance to cover potential claims.
- C. The provider willdefend and indemnify the company against infringement claims.
- D. The provider willwarrant that the tool will work as intended.
Answer: C
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 # 83
After completing model testing and validation, which of the following is the most important step that an organization takes prior to deploying the model into production?
- A. Identify known edge cases to monitor post-deployment.
- B. Document maintenance teams and processes.
- C. Define a model-validation methodology.
- D. Perform a readiness assessment.
Answer: D
Explanation:
After completing model testing and validation, the most important step prior to deploying the model into production is to perform a readiness assessment. This assessment ensures that the model is fully prepared for deployment, addressing any potential issues related to infrastructure, performance, security, and compliance.
It verifies that the model meets all necessary criteria for a successful launch. Other steps, such as defining a model-validation methodology, documenting maintenance teams and processes, and identifying known edge cases, are also important but come secondary to confirming overall readiness. Reference: AIGP Body of Knowledge on Deployment Readiness.
NEW QUESTION # 84
CASE STUDY
A company is considering the procurement of an AI system designed to enhance the security of IT infrastructure. The AI system analyzes how users type on their laptops, including typing speed, rhythm and pressure, to create a unique user profile. This data is then used to authenticate users and ensure that only authorized personnel can access sensitive resources.
The data processed by the AI system would be classified as:
- A. Special category data, if it can be used to uniquely identify a person
- B. Organizational data, since it is part of the authentication process
- C. Non-sensitive personal data, since it does not reveal information about health, gender or race
- D. Non-personal data, as long as it is not linked to a user ID
Answer: A
Explanation:
The correct answer is D. Keystroke dynamics, used to identify individuals, fall under biometric data, which is a special category of personal data under the GDPR and other frameworks.
From the AI Governance in Practice Report 2024:
"Keystroke dynamics may constitute biometric data if used to uniquely identify an individual... Biometric data is classified as special category personal data and requires higher protection standards." Also reflected in ILT Participant Guide:
"Biometric data, such as facial images, voiceprints, iris scans or keystroke patterns, are treated as special category data when they are used for the purpose of uniquely identifying individuals."
NEW QUESTION # 85
According to the EU Al Act, providers of what kind of machine learning systems will be required to register with an EU oversight agency before placing their systems in the EU market?
- A. Al systems that are "strong" general intelligence.
- B. Al systems trained on sensitive personal data.
- C. Al systems that are high-risk.
- D. Al systems that are harmful based on a legal risk-utility calculation.
Answer: C
Explanation:
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.
NEW QUESTION # 86
Which of the following best defines an "Al model"?
- A. A corpus of data which an Al algorithm analyzes to make predictions.
- B. A system of controls that is used to govern an Al algorithm.
- C. A program that has been trained on a set of data to find patterns within the data.
- D. A system that applies defined rules to execute tasks.
Answer: C
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 # 87
Scenario:
Business A provides grammar and writing assistance tools and licenses a generative AI model from Business B to enhance its offerings. Business A is concerned that the AI model might produce inappropriate or toxic content and wants to implement governance processes to prevent this.
Which of the following governance processes should Business A take to best protect its users against potentially inappropriate text?
- A. Business A should test that the AI model performs as expected and meets their minimum requirements for filtering toxic or obscene text
- B. Business A should ask Business B for detailed documentation on the generative AI model's training data and whether it contained toxic or obscene sources
- C. Business A should establish a user reporting feature that allows users to flag toxic or obscene text, and report any incidents to Business B
- D. Business A should fine-tune the AI model on user-generated text that has been verified to be appropriate
Answer: A
Explanation:
The correct answer is B. According to responsible AI practices, pre-deployment testing to ensure the model behaves as expected and aligns with organizational requirements is critical.
From the AIGP ILT Guide:
"Testing for unacceptable outcomes such as toxicity, discrimination, or hallucinations should be included in the AI governance life cycle, particularly during development and prior to deployment." Also emphasized in the AI Governance in Practice Report 2024:
"Organizations must verify legal and regulatory compliance, monitor performance, and mitigate risks prior to deployment." Testing the model to meet safety and appropriateness standards is more proactive and preventive than relying solely on user reporting or requesting documentation.
NEW QUESTION # 88
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. Upon initial deployment of the system.
- C. When the algorithmic impact assessment has been completed.
- D. Upon release of a new version of the system.
Answer: B
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 # 89
During the development of semi-autonomous vehicles, various failures occurred as a result of the sensors misinterpreting environmental surroundings, such as sunlight.
These failures are an example of?
- A. Hallucination.
- B. Forgetting.
- C. Uncertainty.
- D. Brittleness.
Answer: D
Explanation:
The failures in semi-autonomous vehicles due to sensors misinterpreting environmental surroundings, such as sunlight, are examples of brittleness. Brittleness in AI systems refers to their inability to handle variations in input data or unexpected conditions, leading to failures when the system encounters situations that were not adequately covered during training. These systems perform well under specific conditions but fail when those conditions change. Reference: AIGP Body of Knowledge on AI System Robustness and Failures.
NEW QUESTION # 90
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?
- A. An AI algorithm being used in a credit decision-making process by a financial institution
- B. An AI customer service system claiming that it is as accurate as a human support agent
- C. An AI tool using scraped digital content to generate news summaries on a publishing website
- D. An online platform offering recommendations to its users by displaying user-specific content and targeted advertisements
Answer: D
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 # 91
Which of the following deployments of generative Al best respects intellectual property rights?
- A. The system produces content that includes trademarks and copyrights.
- B. The system categorizes and applies filters to content based on licensing terms.
- C. The system produces content that is modified to closely resemble copyrightedwork.
- D. The system provides attribution to creators of publicly available information.
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 # 92
To maintain fairness in a deployed system, it is most important to?
- A. Detect anomalies outside established metrics that require new training data.
- B. Protect against loss of personal data in the model.
- C. Monitor for data drift that may affect performance and accuracy.
- D. Optimize computational resources and data to ensure efficiency and scalability.
Answer: C
NEW QUESTION # 93
A US-based mortgage lender has purchased a chatbot. They plan to have the chatbot collect information from consumers who are interested in loans and offer the consumers 2-3 different options based on its current pricing and product offerings, which change frequently. This chatbot was initially developed and previously deployed by a Russian airline for booking flights.
The best option for the part of the process that generates the loan offers is?
- A. Expert System.
- B. Quantum computing
- C. Retrieval-Augmented Generation.
- D. Multimodal Generative AI.
Answer: A
Explanation:
Offeringloan products based on current offerings and rulesrequires a system that can followexplicit business logic, not generate open-ended content. Anexpert system, which is a rules-based AI that uses "if- then" logic, is ideal here.
From the AI governance context:
"Rule-based AI systems are often preferred when decisions must adhere to precise regulatory or financial criteria." (aligned with AI best practices in regulated sectors)
* A. RAGis used to integrate external knowledge-not suitable for structured, rule-based logic.
* B. Multimodal modelshandle varied input types-not needed here.
* D. Quantum computingis not yet practical or relevant for this business use case.
NEW QUESTION # 94
A company is working to develop a self-driving car that can independently decide the appropriate route to take the driver after the driver provides an address.
If they want to make this self-driving car "strong" Al, as opposed to "weak," the engineers would also need to ensure?
- A. That the Al can differentiate among ethnic backgrounds of pedestrians.
- B. That they have obtained appropriate intellectual property (IP) licenses to use data for training the Al.
- C. Thatthe Al has full human cognitive abilities that can independently decide where to take the driver.
- D. That the Al has strong cybersecurity to prevent malicious actors from taking control of the car.
Answer: C
Explanation:
Strong AI, also known as artificial general intelligence (AGI), refers to AI that possesses the ability to understand, learn, and apply intelligence across a broad range of tasks, similar to human cognitive abilities.
For the self-driving car to be classified as "strong" AI, it would need to possess full human cognitive abilities to make independent decisions beyond pre-programmed instructions. Reference: AIGP BODY OF KNOWLEDGE and AI classifications.
NEW QUESTION # 95
Which of the following Al uses is best described as human-centric?
- A. Machine learning is used for demand forecasting and inventory management, ensuring that consumers can find products they want when they want them.
- B. Autonomous robots are used to move products within a warehouse, allowing human workers to reduce physical strain and alleviate monotony.
- C. Pattern recognition algorithms are used to improve the accuracy of weather predictions, which benefits many industries and everyday life.
- 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 # 96
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