Which of the following is the MOST important reason for applying regular software updates to AI systems operating in high-risk environments?
Answer(s): D
Regular software updates are essential in high-risk AI environments because they address security vulnerabilities and protect the system from attacks that could compromise output integrity. Ensuring the reliability and trustworthiness of AI outputs is the primary governance concern.
Which of the following is the MOST important AI data governance method to protect privacy and data security?
Periodic monitoring is essential for detecting privacy violations, unauthorized data use, and emerging security risks in AI systems. Continuous oversight ensures that data handling practices remain compliant and secure throughout the AI life cycle, making it the most important governance method for protecting privacy and data security.
A car rental company is developing an AI system to dynamically adjust rental pricing based on demand, location, and customer profiles. Which of the following is the MOST important reason to conduct specific testing during development?
Dynamic pricing based on customer profiles carries a high risk of discriminatory outcomes. Testing must ensure the AI does not unintentionally produce biased or unfair pricing decisions, making this the most important governance and ethical concern during development.
Which of the following should be done FIRST when developing an incident management process for AI threats?
Answer(s): B
Defining clear roles and responsibilities is the foundational first step in developing an AI incident management process. Without clarity on who is accountable for detection, response, decision-making, and communication, subsequent procedures such as classification and escalation cannot be executed effectively.
Which of the following roles is BEST suited to define the implementation roadmaps for adopting AI solutions?
A steering committee is responsible for strategic oversight and is best positioned to define AI implementation roadmaps, ensuring alignment with organizational goals, governance requirements, and enterprise-wide priorities.
After AI training data has been tested for biases, which of the following is MOST important to check in order to validate the effectiveness of the testing?
After bias testing, the most important validation step is ensuring that the AI model’s outputs stay within the organization’s acceptable risk level. This confirms that bias mitigation efforts were effective and that resulting decisions do not create unacceptable ethical, legal, or operational risks.
Which of the following is the GREATEST risk associated with the use of AI coding tools by software developers?
Answer(s): C
AI coding tools may generate insecure code patterns or omit essential security controls, increasing the likelihood of introducing vulnerabilities into applications. This poses the greatest risk because it directly compromises software security and can lead to significant exploitation.
An insurance company uses an AI model to set premium rates. To align with AI-related policies on fairness, which of the following is the FIRST course of action?
The first step in addressing fairness is to review the training data to identify potential sources of bias. Understanding whether biased data exists is necessary before modifying datasets or comparing alternative models.
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answer to this question "what administrative safeguards should be implemented to protect the collected data while in use by manasa and her product management team? " it should be (c) for the following reasons: this administrative safeguard involves controlling access to collected data by ensuring that only individuals who need the data for their job responsibilities have access to it. this helps minimize the risk of unauthorized access and potential misuse of sensitive information. while other options such as (a) documenting data flows and (b) conducting a privacy impact assessment (pia) are important steps in data protection, implementing a "need to know" access policy directly addresses the issue of protecting data while in use by limiting access to those who require it for legitimate purposes. (d) is not directly related to safeguarding data during use; it focuses on data transfers and location.
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