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IAPP AIGP Exam Syllabus Topics:

SectionObjectives
Foundations of AI Systems and Governance- Governance principles and accountability
  • 1. Responsible AI principles
    • 2. Organizational governance roles
      - AI system concepts, lifecycle, and terminology
      • 1. AI system lifecycle overview
        • 2. AI definitions and taxonomy
          AI Lifecycle Governance Implementation- Operational governance controls
          • 1. Deployment and monitoring controls
            • 2. Model development oversight
              AI Risk Management and Impact Assessment- Risk identification and mitigation
              • 1. AI risk categories and classification
                • 2. Bias, fairness, and transparency risks
                  Regulatory and Legal Frameworks for AI- Global AI governance regulations
                  • 1. NIST AI Risk Management Framework
                    • 2. EU AI Act principles

                      >> Latest AIGP Practice Questions <<

                      IAPP - AIGP - Latest IAPP Certified Artificial Intelligence Governance Professional Practice Questions

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                      IAPP Certified Artificial Intelligence Governance Professional Sample Questions (Q106-Q111):

                      NEW QUESTION # 106
                      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:

                      Answer: B

                      Explanation:
                      Autoregression is a statistical modeling technique for time-series analysis, not a weight optimization technique used in deep learning neural networks.


                      NEW QUESTION # 107
                      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?

                      Answer: B

                      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 # 108
                      What is the primary purpose of an AI impact assessment?

                      Answer: B

                      Explanation:
                      The correct answer is D. AI Impact Assessments are primarily used to identify and manage risks and harms associated with AI systems.
                      From the AIGP Body of Knowledge:
                      "The goal of an AI impact assessment is to ensure that risks are identified, evaluated, and mitigated prior to or during development and deployment." As further confirmed in the AI Governance in Practice Report 2024 (Part III):
                      "Risk-based tools like DPIAs and Algorithmic Impact Assessments help identify potential risks to individuals and society, enabling organizations to implement mitigation plans and safeguards." While benefits may be noted in such assessments, the core objective is to manage risks and promote responsible AI.


                      NEW QUESTION # 109
                      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 of the following measures should XYZ adopt to best mitigate its risk of reputational harm from using the Al tool?

                      Answer: C

                      Explanation:
                      To mitigate the risk of reputational harm from using an AI hiring tool, XYZ Corp should rigorously test the AI tool both before and after deployment. Pre-deployment testing ensures the tool works correctly and does not introduce bias or other issues. Post-deployment testing ensures the tool continues to operate as intended and adapts to any changes in data or usage patterns. This approach helps to identify and address potential issues proactively, thereby reducing the risk of reputational harm. Ensuring the vendor assumes responsibility for damages (B) does not address the root cause of potential issues, selecting the most economical tool (C) may compromise quality, and continuing manual screening (D) defeats the purpose of using the AI tool.


                      NEW QUESTION # 110
                      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?

                      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 # 111
                      ......

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