[May-2026] IAPP AIGP Exam Practice Test Questions - VerifiedDumps
Updated Certification Exam AIGP Dumps - Practice Test Questions
IAPP AIGP Exam Syllabus Topics:
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NEW QUESTION # 65
Scenario:
An organization wants to leverage its existing compliance structures to identify AI-specific risks as part of an ongoing data governance audit.
Which of the following compliance-related controls within an organization is most easily adapted to identify AI risks?
- A. Privacy impact assessments
- B. Privacy training
- C. Transfer risk assessments
- D. Penetration testing
Answer: A
Explanation:
The correct answer is D - Privacy impact assessments (PIAs). These are directly adaptable for identifying risks in AI systems, particularly around data usage, bias, and individual impacts.
From the AIGP ILT Guide - Risk Management Module:
"PIAs and DPIAs are existing tools used in privacy compliance that can be extended to evaluate the risks of AI, including fairness, explainability, and legality." AI Governance in Practice Report 2024 further explains:
"Organizations can adapt privacy impact assessments to evaluate the ethical, legal, and technical risks posed by AI systems. They provide a structured and recognized method." PIAs are preferable over general security practices (like pen testing) which do not address algorithmic bias or legal compliance directly.
NEW QUESTION # 66
All of the following are reasons to deploy a challenger AI model in addition to a champion AI model EXCEPT to:
- A. Automate real-time monitoring of the champion model.
- B. Perform testing on the champion model.
- C. Provide a framework to consider alternatives to the champion model.
- D. Retrain the champion model.
Answer: D
Explanation:
Retraining the champion model is a maintenance activity, not a reason to deploy a challenger model; challenger models provide alternative options for comparison and testing.
NEW QUESTION # 67
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. Define a model-validation methodology.
- B. Perform a readiness assessment.
- C. Document maintenance teams and processes.
- D. Identify known edge cases to monitor post-deployment.
Answer: B
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 # 68
CASE STUDY
A global marketing agency is adapting a large language model ("LLM") to generate content for an upcoming marketing campaign for a client's new product: a hard hat designed for construction workers of any gender to better protect them from head injuries.
The marketing agency is accessing the LLM through an application programming interface ("API") developed by a third-party technology company. They want to generate text to be used for targeted advertising communications that highlight the benefits of the hard hat to potential purchasers. Both the marketing agency and the technology company have taken reasonable steps to address Al governance.
The marketing company has:
* Entered into a contract with the technology company with suitable representations and warranties.
* Completed an impact assessment on the LLM for this intended use.
* Built technical guidance on how to measure and mitigate bias in the LLM.
* Enabled technical aspects of transparency, explainability, robustness and privacy.
* Followed applicable regulatory requirements.
* Created specific legal statements and disclosures regarding the use of the Al on its client's advertising.
The technology company has:
* Provided guidance and resources to developers to address environmental concerns.
* Build technical guidance on how to measure and mitigate bias in the LLM.
* Provided tools and resources to measure bias specific to the LLM.
* Enabled technical aspects of transparency, explainability, robustness and privacy.
* Mapped and mitigated potential societal harms and large-scale impacts.
* Followed applicable regulatory requirements and industry standards.
* Created specific legal statements and disclosures regarding the LLM. including with respect to IP and rights to data.
The technology company has also addressed environmental concerns and societal harms.
Which of the following results would be considered biased outputs from this AI system EXCEPT?
- A. The images of female workers are hyper-sexualized
- B. The content generated for minority construction workers is insufficient
- C. The advertising text generated for female audiences focuses on color and style
- D. The generated ads are sent to construction companies, not individual workers
Answer: D
Explanation:
The correct answer isA. Sending ads to construction companies (business entities) rather than individual workers isa business targeting decision, not inherently a biased AI output.
From the AIGP ILT Participant Guide - Bias & Fairness Module:
"Biased outputs often include stereotyping, exclusion of underrepresented groups, or reinforcing harmful societal assumptions." Examples likeinsufficient representation of minority groupsorgender-stereotyping in visuals or languageare typical manifestations of bias.
AI Governance in Practice Report2025also notes:
"Bias in generative models may manifest in representation gaps, stereotyping, or unequal performance across demographic groups." Option A, by contrast, describes adistribution strategy, not a bias generated by the AI model.
NEW QUESTION # 69
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 that are harmful based on a legal risk-utility calculation.
- C. Al systems that are high-risk.
- D. Al systems trained on sensitive personal data.
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 # 70
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 AI as a workplace tool?
- A. Impose a general ban on the use of generative AI.
- B. Limit access to specific uses of generative AI.
- C. Limit access of generative AI to engineers and developers.
- D. Impose a ban on the use of generative AI in agencies that protect national security.
Answer: B
Explanation:
Under the November 2023 Executive Order on Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence, the Office of Management and Budget (OMB) is tasked with developing guidance for federal agencies on the responsible use of generative AI in the workplace. This guidance emphasizes the need for agencies to provide access to generative AI tools with appropriate safeguards, rather than imposing blanket restrictions or bans. The goal is to ensure that AI tools are used in a manner that protects Americans' rights and safety while promoting innovation and efficiency in government operations.
NEW QUESTION # 71
Your company is developing an AI system for global markets. This system involves personal data processing and some decision making that may affect rights of the individuals. Part of your role as an AI governance professional is to ensure the AI system complies with various international regulatory requirements. Which of the following approaches best aligns with a comprehensive understanding of and compliance with AI regulatory requirements in this scenario?
- A. Adopt a region-specific compliance strategy where the AI is modified to meet regulatory requirements of each region independently, disregarding commonalities or overlaps in international regulations.
- B. Consider that if the AI system complies with local regulations of the country where the company is based, it is not necessary to comply with international regulations as AI is adaptable globally.
- C. Develop a compliance strategy based on the strictest requirements in various regulations, including the EU AI Act, GDPR and HIPAA, and harmonize into a unified compliance framework.
- D. Focus on the EU AI Act as it is the most comprehensive regulation and its likely compliance with the act will ensure compliance with other international regulations that apply to AI.
Answer: C
NEW QUESTION # 72
CASE STUDY
A global marketing agency is adapting a large language model ("LLM") to generate content for an upcoming marketing campaign for a client's new product: a hard hat designed for construction workers of any gender to better protect them from head injuries.
The marketing agency is accessing the LLM through an application programming interface ("API") developed by a third-party technology company. They want to generate text to be used for targeted advertising communications that highlight the benefits of the hard hat to potential purchasers. Both the marketing agency and the technology company have taken reasonable steps to address Al governance.
The marketing company has:
* Entered into a contract with the technology company with suitable representations and warranties.
* Completed an impact assessment on the LLM for this intended use.
* Built technical guidance on how to measure and mitigate bias in the LLM.
* Enabled technical aspects of transparency, explainability, robustness and privacy.
* Followed applicable regulatory requirements.
* Created specific legal statements and disclosures regarding the use of the Al on its client's advertising.
The technology company has:
* Provided guidance and resources to developers to address environmental concerns.
* Build technical guidance on how to measure and mitigate bias in the LLM.
* Provided tools and resources to measure bias specific to the LLM.
* Enabled technical aspects of transparency, explainability, robustness and privacy.
* Mapped and mitigated potential societal harms and large-scale impacts.
* Followed applicable regulatory requirements and industry standards.
* Created specific legal statements and disclosures regarding the LLM. including with respect to IP and rights to data.
The marketing company and its tech provider have taken reasonable steps to govern the AI's use, including legal disclosures, impact assessments, and bias mitigation. However, the company wants to take one more step to improve governance and reduce risks related to ongoing oversight and accountability.
While the marketing agency took steps to mitigate its risks, the best additional step would be to:
- A. Establish a governance committee to oversee the project
- B. Evaluate the use of AI in the marketing industry to identify best practices
- C. Engage a third party to lead the procurement selection process
- D. Negotiate an intellectual property indemnity from the technology company
Answer: A
Explanation:
The correct answer is D. Forming a dedicated governance committee ensures continuous oversight, role clarity, and accountability throughout the AI lifecycle.
From the AIGP ILT Guide - Governance Structures:
"Organizations using AI in high-impact scenarios should establish a governance body responsible for oversight of risk, compliance, and ethical alignment." Also reflected in AI Governance in Practice Report 2024:
"Committees support cross-functional decision-making, provide guidance for updates, and maintain accountability. This is especially critical for high-stakes applications like marketing to diverse audiences." Options A, B, and C are valid supplementary actions, but D offers a long-term and systematic governance mechanism.
NEW QUESTION # 73
CASE STUDY
Please use the following to answer the next question:
A local police department in the United States procured an AI 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 AI system works by surveying 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 to 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 AI 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 AI 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 AI 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. Ensure an accused is given notice that the AI system was used.
- B. Consider the AI recommendation as part of the criminal investigation.
- C. Explain to the accused how the AI system works.
- D. Confirm the AI recommendation prior to sentencing.
Answer: B
Explanation:
The best oversight requires that police officers consider AI recommendations as one input within a broader investigation, ensuring human judgment and due process are maintained.
NEW QUESTION # 74
What are the roles and responsibilities of deployers of a proprietary model? (Choose three.)
- A. Regulatory compliance.
- B. Ethical testing.
- C. Technical performance.
- D. System documentation.
- E. Ethical design.
Answer: A,B,C
Explanation:
Deployers of a proprietary model are responsible for ethical testing, ensuring technical performance, and maintaining regulatory compliance when using the model in their environment and for their use case.
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 AI Act prohibitions
- B. In case of breach of a provider's obligations for high-risk AI systems
- C. In case of a breach of AI Act prohibition by the Union institutions, bodies, offices and agencies
- D. In case of the supply of misleading information to notified bodies in reply to a request
Answer: B
Explanation:
The correct answer isB. The EU AI Act assigns atiered penalty systembased on the severity of the violation.
A breach ofobligations related to high-risk AI systemsfalls 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: Thehighest penalty (€35 million or 7%)applies toprohibited AI uses, not to obligations for high-risk systems.
NEW QUESTION # 76
Your organization is searching for a new way to help accurately forecast sales predictions by various types of customers.
Which of the following is the best type of model to choose if your organization wants to customize the model and avoid lock-in?
- A. A classic machine learning model.
- B. A proprietary generative AI model.
- C. A free large language model.
- D. A subscription-based, multimodal model.
Answer: A
Explanation:
Forcustomizable, interpretable modelsthat allow organizations toretain control and avoid vendor lock-in, classic ML models(e.g., regression, decision trees, random forests) are optimal.
From theAI Governance in Practice Report 2024:
"Organizations seeking transparency, customizability, and control often prefer classic ML models due to their flexibility and ease of governance." (p. 33)
* AandCmay have limited transparency and are often tied to specific providers.
* Dinvolves ongoing costs and limited model control.
NEW QUESTION # 77
Business A sells software that provides users with writing and grammar assistance. Business B is a cloud services provider that trains its own AI models.
* Business A has decided to add generative AI features to their software.
* Rather than create their own generative AI model, Business A has chosen to license a model from Business B:
* Business A will then integrate the model into their writing assistance software to provide generative AI capabilities.
* Business A is most concerned that its writing assistance software could recommend toxic or obscene text to its users.
Which of the following governance processes should Business A take to best protect its users against potentially inappropriate text?
- A. 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.
- B. Business A should establish a user reporting feature that allows users to flag toxic or obscene text, and report any incidents to Business B.
- C. Business A should test that the AI model performs as expected and meets their minimum requirements for filtering toxic or obscene text.
- D. Business A should fine-tune the AI model on user-generated text that has been verified to be appropriate.
Answer: C
Explanation:
Business A is integrating a generative AI model licensed from a third party (Business B) and is primarily concerned with the risk of toxic or obscene outputs being delivered to users. In this scenario,testing and validationof the AI model for such content risks is the most direct and effective governance strategy.
According to theAI Governance in Practice Report 2024, organizations thatdeployAI must engage in performance monitoring protocolsand ensure systems perform adequately for theirintended purposes, including filtering harmful content:
"Operational governance... development of: #Performance monitoring protocols to ensure systems perform adequately for their intended purposes." (p. 12)
"Product governance... includes: #System impact assessments to identify and address risk prior to product development or deployment." (p. 11) Furthermore, under theEU AI Act, which sets the global standard many organizations aim to align with, there is a clear obligation to test and monitor systems for potential harmful behavior:
"The act imposes regulatory obligations... such as establishing appropriate accountability structures,assessing system impact, providing technical documentation,establishing risk management protocols and monitoring performance..." (p. 7) Option B directly reflects this best practice ofpre-deployment testing and validationto ensure that the model aligns with Business A's minimum content safety requirements.
Let's now evaluate the incorrect options:
* A. Fine-tuning on verified user-generated textmay improve model alignment but does not guarantee that the model will generalize correctly, especially if Business A lacks access to model internals (common in third-party licensing scenarios). Fine-tuning also introduces its own risks and may be contractually restricted.
* C. A user reporting featureisreactive, not preventive. While helpful for long-term monitoring and mitigation, it does not prevent the initial harm of toxic outputs, which isBusiness A's primary concern.
* D. Requesting documentation from Business Bis useful for transparency and risk management, but it does not replaceindependent verificationthat the model meets Business A's content safety standards.
Thus,testing the model's behavior for unacceptable outputs before deploymentis the most aligned approach with AI governance best practices and obligations.
NEW QUESTION # 78
All of the following may be permissible uses of an Al system under the EU Al Act EXCEPT?
- A. To promote equitable distribution of welfare benefits.
- B. To implement social scoring.
- C. To detect an individual's intent for law enforcement purposes.
- D. To manage border control.
Answer: B
Explanation:
The EU AI Act explicitly prohibits the use of AI systems for social scoring by public authorities, as it can lead to discrimination and unfair treatment of individuals based on their social behavior or perceived trustworthiness. While AI can be used to promote equitable distribution of welfare benefits, manage border control, and even detect an individual's intent for law enforcement purposes (within strict regulatory and ethical boundaries), implementing social scoring systems is not permissible under the Act due to the significant risks to fundamental rights and freedoms.
NEW QUESTION # 79
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. Differential privacy.
- C. Pseudonymization.
- 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 # 80
The best method to ensure a comprehensive identification of risks for a new AI model is?
- A. An impact assessment.
- B. Red teaming.
- C. An environmental scan.
- D. Integration testing.
Answer: A
Explanation:
The most comprehensive way to identify a full range of risks - legal, ethical, operational, and societal - for a new AI model is through aformal impact assessment, such as aData Protection Impact Assessment (DPIA) orAlgorithmic Impact Assessment.
From theAI Governance in Practice Report2025:
"Risk-based approaches are often distilled into organizational risk management efforts, which put impact assessments at the heart of deciding whether harm can be reduced." (p. 29)
"DPIAs... help organizations identify, analyze and minimize data-related risks and demonstrate accountability." (p. 30)
* A. Environmental scanis too general.
* B. Red teamingis useful for adversarial risk but not broad.
* C. Integration testingfocuses on technical/system compatibility, not overall risk.
NEW QUESTION # 81
Which of the following would be the least likely step for an organization to take when designing an integrated compliance strategy for responsible AI?
- A. Meeting with and obtaining approval from senior management.
- B. Launching a survey to understand the concerns and interests of potentially impacted stakeholders.
- C. Employing a new software platform to modernize existing compliance processes across the organization.
- D. Consulting experts to consider the ethical principles underpinning the use of AI within the organization.
Answer: C
Explanation:
Modernizing compliance software is not a core or necessary activity when designing an integrated responsible AI compliance strategy. It may support operations later, but it is not a typical or essential early step compared to governance approval, stakeholder input, and ethical consultation.
NEW QUESTION # 82
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 tobest protect its usersagainst potentially inappropriate text?
- A. Business A should fine-tune the AI model on user-generated text that has been verified to be appropriate
- B. Business A should establish a user reporting feature that allows users to flag toxic or obscene text, and report any incidents to Business B
- C. 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
- D. Business A should test that the AI model performs as expected and meets their minimum requirements for filtering toxic or obscene text
Answer: D
Explanation:
The correct answer isB. According to responsible AI practices,pre-deployment testingto ensurethe 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 Report2025:
"Organizations must verify legal and regulatory compliance, monitor performance, and mitigate risksprior to deployment." Testing the model tomeet safety and appropriateness standardsis more proactive and preventive than relying solely on user reporting or requesting documentation.
NEW QUESTION # 83
The processes and methods that allow human users to understand and trust the outputs produced by AI are important in addressing which key regulatory concern?
- A. Responsible AI.
- B. Trustworthy AI.
- C. Explainable AI.
- D. Interpretable AI.
Answer: C
Explanation:
Explainable AI focuses specifically on providing users with understandable reasoning behind AI outputs so they can interpret, evaluate, and trust the system's decisions.
NEW QUESTION # 84
Which risk management framework/guide/standard focuses on value-based engineering methodology?
- A. Council of Europe Human Rights, Democracy, and the Rule of Law Assurance Framework (HUDERIA) for Al Systems.
- B. IEEE 7000-2021 Standard Model Process for Addressing Ethical Concerns during System Design.
- C. ISO 31000 Guidelines (Risk Management).
- D. ISO/IEC Guide 51 (Safety).
Answer: B
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 # 85
Under the Canadian Artificial Intelligence and Data Act, when must the Minister of Innovation, Science and Industry be notified about a high-impact AI system?
- A. When the algorithmic impact assessment has been completed.
- B. When use of the system causes or is likely to cause material harm.
- C. Upon release of a new version of the system.
- D. Upon initial deployment of the system.
Answer: B
Explanation:
Under the Canadian Artificial Intelligence and Data Act (AIDA), the responsible party must notify the Minister of Innovation, Science and Industry as soon as feasible if the use of a high-impact AI system results in or is likely to result in material harm.
NEW QUESTION # 86
A U.S. mortgage company developed an Al platform that was trained using anonymized details from mortgage applications, including the applicant's education, employment and demographic information, as well as from subsequent payment or default information. The Al platform will be used automatically grant or deny new mortgage applications, depending on whether the platform views an applicant as presenting a likely risk of default.
Which of the following laws is NOT relevant to this use case?
- A. Title VII of the Civil Rights Act of 1964.
- B. Equal Credit Opportunity Act.
- C. Fair Credit Reporting Act.
- D. Fair Housing Act.
Answer: A
Explanation:
The U.S. mortgage company's AI platform relates to housing and credit, making the Fair Housing Act (A), Fair Credit Reporting Act (B), and Equal Credit Opportunity Act (C) relevant. Title VII of the Civil Rights Act of 1964 deals with employment discrimination and is not directly relevant to the mortgage application context (D).
NEW QUESTION # 87
ISO/IEC 22989 and 42001 can be valuable resources for AI Governance professionals in all of the following ways EXCEPT:
- A. Addressing specific issues related to managing procurement processes with third parties that provide or develop AI systems for their organization.
- B. Establishing terminology and describing concepts so that governance team members can communicate with diverse parties and stakeholders from around the world.
- C. Recommending key activities to assess and manage risk: test, evaluate, verify and validate (TEVV).
- D. Being applicable to organizations of any size and industry seeking to use AI responsibly and effectively in their design processes, information systems and controls.
Answer: A
Explanation:
ISO/IEC 22989 and 42001 provide foundational concepts, terminology, and governance guidance for AI systems, but they do not address the detailed, specific processes required for managing procurement with third-party AI providers.
NEW QUESTION # 88
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. Thatthe Al has full human cognitive abilities that can independently decide where to take the driver.
- B. That the Al can differentiate among ethnic backgrounds of pedestrians.
- C. That they have obtained appropriate intellectual property (IP) licenses to use data for training the Al.
- D. That the Al has strong cybersecurity to prevent malicious actors from taking control of the car.
Answer: A
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 # 89
CASE STUDY
Please use the following to answer the next question:
A leading insurance provider that offers a range of coverage options to individuals has decided to utilize AI to streamline and improve its customer acquisition and underwriting process, including the accuracy and efficiency of pricing policies. The company has engaged a cloud provider to utilize and fine-tune its pre-trained, general purpose large language model ("LLM").
The company 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 to a human underwriter for final review.
The company 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. They have 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, the company realizes that the LLM declines a higher percentage of women's applications.
Each of the following steps would support fairness testing by the compliance team during the first month in production EXCEPT:
- A. Using tools to help understand factors that may account for differences in decision-making.
- B. Validating a similar level of decision-making across different demographic groups.
- C. Identifying if additional training data should be collected for specific demographic groups.
- D. Providing the applicants with information about the model capabilities and limitations.
Answer: D
Explanation:
Providing applicants with information about model capabilities is important for transparency but does not directly support fairness testing, which focuses on evaluating and mitigating bias in decision-making.
NEW QUESTION # 90
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