QUIZ: AI-IRBs Governance and Ethical Oversight
Assessment settings
- Passing grade required: Yes
- Passing grade: 80%
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You’ve demonstrated a solid understanding of key concepts around Institutional Review Boards for AI Governance. Keep this momentum going as you dive deeper into the next chapters. Your insights into ethical oversight and responsible AI development will help shape a more trustworthy, transparent AI future.
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Although your score did not meet the passing threshold this time, don’t be discouraged. Take a moment to review the chapter materials—paying special attention to historical IRB foundations, ethical oversight processes, and the role of AI-IRBs. Once you feel ready, come back and try again. Each attempt is a valuable step toward mastering these essential concepts for responsible AI governance.
Questions and answer key
1. Which historical event led to the creation of the Nuremberg Code, a foundational document for ethical guidelines in research?
Type: single
- The Manhattan Project
- The Great Depression
- The Nuremberg Trials
- The Turing Test
Explanation
Correct Answer: C
Explanation: The Nuremberg Trials (post–World War II) exposed severe ethical violations in medical research, leading to the creation of the Nuremberg Code. This code established principles such as informed consent and the protection of human research subjects, which later shaped the foundations of Institutional Review Boards (IRBs).
2. Traditional IRBs were originally established primarily to:
Type: single
- Oversee AI development in corporate settings
- Review and monitor research involving human subjects
- Enforce international trade regulations
- Develop standard operating procedures for universities
Explanation
Correct Answer: B
Explanation: The historical role of IRBs was centered on protecting human participants in research (e.g., biomedical, social science), ensuring ethical standards like informed consent and minimizing harm.
3. In the context of AI governance, one core function of AI-IRBs is to:
Type: single
- Design marketing strategies for AI products
- Certify AI developers for technical proficiency
- Evaluate ethical risks such as privacy and algorithmic bias
- Regulate global trade of AI components
Explanation
Correct Answer: C
Explanation: AI-IRBs focus on ethical considerations unique to AI, including data privacy and the possibility of embedded bias in training data or algorithms. They help ensure AI systems align with societal values and legal requirements.
4. Why is the concept of informed consent particularly challenging for AI projects?
Type: single
- AI projects rarely involve people at any level
- AI systems can be developed without using data
- AI algorithms often operate as “black boxes,” making it hard for participants to understand how decisions are made
- There are international laws that outlaw informed consent in AI research
Explanation
Correct Answer: C
Explanation: The “black box” nature of many AI algorithms makes it difficult to explain how decisions are derived. This lack of transparency complicates the process of fully informing participants or data subjects about potential risks and outcomes.
5. What is a key difference between internal and external AI-IRBs?
Type: single
- Internal AI-IRBs focus solely on legal compliance, while external AI-IRBs only look at financial risks
- Internal AI-IRBs operate within the same organization developing the AI, whereas external AI-IRBs provide independent, third-party oversight
- External AI-IRBs handle technical product development, while internal AI-IRBs set product pricing
- External AI-IRBs cannot enforce any ethical guidelines
Explanation
Correct Answer: B
Explanation: Internal AI-IRBs exist within the organization and review projects with insider context, but may face conflicts of interest. External AI-IRBs, in contrast, bring independent expertise and a neutral perspective on ethical governance.
6. One of the principal reasons AI-IRBs are needed, as discussed in the readings, is because AI systems:
Type: single
- Never involve human data
- Are fully transparent by design
- Can make decisions that carry significant societal impact
- Operate only in closed laboratory environments
Explanation
Correct Answer: C
Explanation: As AI becomes deeply integrated into healthcare, finance, and beyond, its decisions can affect individuals and communities on a large scale. AI-IRBs help ensure these decisions are fair, responsible, and ethically sound.
7. Which of the following best describes “algorithmic bias”?
Type: single
- A programming error that slows down AI processing
- The tendency of AI systems to produce outcomes reflecting biases present in training data
- The process of AI becoming self-aware
- A tool used to eliminate ethical risks in AI
Explanation
Correct Answer: B
Explanation: Algorithmic bias happens when AI is trained on datasets that contain historical or societal biases. This can lead to discriminatory or unfair outcomes unless specifically addressed.
8. According to the material, which of the following is not typically a core function of AI-IRBs?
Type: single
- Ethical review of AI projects
- Compliance monitoring
- Conducting public relations campaigns for AI products
- Fostering education and training on AI ethics
Explanation
Correct Answer: C
Explanation: While AI-IRBs have multiple functions—like reviewing ethics, monitoring compliance, and providing education—running public relations campaigns does not fall under their scope of ethical oversight.
9. Why is ongoing “compliance monitoring” essential for AI systems post-deployment?
Type: single
- To ensure AI systems receive constant software updates
- To continuously assess whether AI maintains ethical standards and does not introduce new risks
- To eliminate the need for transparency in AI decisions
- To gather user data for marketing purposes
Explanation
Correct Answer: B
Explanation: Once deployed, AI systems can evolve or adapt over time, potentially introducing new ethical concerns or biases. Ongoing monitoring ensures they remain compliant with established ethical and regulatory guidelines.
10. Which of the following strategies was highlighted as important for AI-IRBs to mitigate algorithmic bias?
Type: single
- Prohibiting the collection of any data at all
- Encouraging AI models to remain secret and proprietary
- Using diverse and representative training datasets
- Outsourcing all AI activities to a different country
Explanation
Correct Answer: C
Explanation: Selecting training data that accurately reflects the diversity of the real-world population helps AI systems avoid perpetuating societal biases. AI-IRBs can guide developers to include various demographic factors and monitor for fairness.