A bank deploys an AI system to approve credit card applications. During routine monitoring, the data science team discovers that an attacker has been submitting thousands of fraudulent applications designed to gradually shift the model's decision boundary, causing it to approve more high-risk applicants over time. The bank's compliance officer wants to prevent this type of manipulation while maintaining model accuracy for legitimate applicants. What should the bank implement?

Restricting access to the model's training data to only senior data scientists

Switching to a simpler linear model to reduce the attack surface

Periodic retraining with a random sample of all applications

Anomaly detection on application patterns combined with human review of flagged outliers

An e-commerce company uses an AI chatbot to handle customer service. The chatbot sometimes gives incorrect information about refunds, and customers cannot tell whether they are talking to a human or a bot. The company wants to improve accountability and transparency. What should they implement?

Clearly label the chatbot as an AI and provide a way to escalate to a human agent.

Keep the chatbot but do not disclose its AI nature to avoid customer confusion.

Train the chatbot on more data to improve accuracy.

Remove the chatbot and hire more human agents.

A university uses an AI system to rank applicants for admission. The system uses historical admission data that reflects past biases against certain demographic groups. The university wants to ensure fairness in the new admissions process. What is the most appropriate action?

Replace the AI system with a random lottery for admissions.

Adjust the model's decision threshold to equalize acceptance rates across demographic groups.

Remove demographic attributes from the training data.

Use the model as is because historical data reflects real performance.

EC-CouncilArtificial Intelligence Essentials

Domain 5Objective 1

Ethical, Societal, and Security Concerns in AI AIE Practice Questions (Page 3)

Part of the AI Ethics and Responsible AI domain, which makes up ~18% of our current practice bank.

42questions here

9free pages

4concepts

Questions 11–15

11foundation · easy
Which mitigation strategy involves establishing rules, policies, and oversight mechanisms to ensure that AI systems are developed and used responsibly?
Select an answer first
12application · medium
A bank deploys an AI system to approve credit card applications. During routine monitoring, the data science team discovers that an attacker has been submitting thousands of fraudulent applications designed to gradually shift the model's decision boundary, causing it to approve more high-risk applicants over time. The bank's compliance officer wants to prevent this type of manipulation while maintaining model accuracy for legitimate applicants. What should the bank implement?
Select an answer first
13application · medium
An e-commerce company uses an AI chatbot to handle customer service. The chatbot sometimes gives incorrect information about refunds, and customers cannot tell whether they are talking to a human or a bot. The company wants to improve accountability and transparency. What should they implement?
Select an answer first
14application · medium
A university uses an AI system to rank applicants for admission. The system uses historical admission data that reflects past biases against certain demographic groups. The university wants to ensure fairness in the new admissions process. What is the most appropriate action?
Select an answer first
15foundation · easy
Which ethical principle in AI requires that the decision-making processes of an AI system be open to inspection and understandable by relevant stakeholders?
Select an answer first

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Ethical, Societal, and Security Concerns in AI AIE Practice Questions (Page 3)

Questions 11–15

Which mitigation strategy involves establishing rules, policies, and oversight mechanisms to ensure that AI systems are developed and used responsibly?

An e-commerce company uses an AI chatbot to handle customer service. The chatbot sometimes gives incorrect information about refunds, and customers cannot tell whether they are talking to a human or a bot. The company wants to improve accountability and transparency. What should they implement?

A university uses an AI system to rank applicants for admission. The system uses historical admission data that reflects past biases against certain demographic groups. The university wants to ensure fairness in the new admissions process. What is the most appropriate action?

Which ethical principle in AI requires that the decision-making processes of an AI system be open to inspection and understandable by relevant stakeholders?

Keep studying — AI Ethics and Responsible AI