Which of the following controls BEST mitigates the risk of data poisoning?
Answer(s): A
Data validation ensures that incoming training data is accurate, complete, and consistent with expected patterns. By verifying and filtering data before it is used for model training, organizations can prevent malicious or corrupted inputs that could compromise model integrity, effectively mitigating data poisoning risks.
An organization utilizes AI-enabled mapping software to plan routes for delivery drivers. A driver following the AI route drives the wrong way down a one-way street, despite numerous signs. Which of the following biases does this scenario demonstrate?
Answer(s): D
This scenario illustrates automation bias, where individuals over-rely on AI recommendations, trusting the system even when it contradicts observable real-world cues (e.g., traffic signs). Overdependence on AI can lead to errors when humans fail to critically assess automated guidance.
An automotive manufacturer uses AI-enabled sensors on machinery to monitor variables such as vibration, temperature, and pressure. Which of the following BEST demonstrates how this approach contributes to operational resilience?
Using AI-enabled sensors for continuous monitoring allows the organization to perform predictive maintenance, addressing potential issues before failures occur. This proactive approach enhances operational resilience by reducing downtime, preventing costly breakdowns, and ensuring continuity of manufacturing processes.
When an attacker uses synthetic data to reverse engineer an organization's AI model, it is an example of which of the following types of attack?
Answer(s): C
Model distillation attacks involve using synthetic or carefully crafted data to query an AI model repeatedly and reconstruct its underlying parameters or behavior. This allows attackers to approximate the original model without direct access, effectively reverse engineering it.
An organization develops and implements an AI-based plug-in for users that summarizes their individual emails. Which of the following is the GREATEST risk associated with this application?
An AI-based email summarization plug-in processes sensitive personal and business information. If parameters controlling data access, processing scope, or output are insufficiently restricted, the application could expose confidential content, mishandle sensitive information, or generate inaccurate summaries, posing the greatest risk.
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