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The ISTQB CT-AI exam questions are designed and verified by experienced and qualified ISTQB CT-AI exam trainers. So you rest assured that with Certified Tester AI Testing Exam (CT-AI) exam dumps you can streamline your CT-AI exam preparation process and get confidence to pass Certified Tester AI Testing Exam (CT-AI) exam in first attempt.
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NEW QUESTION # 11
A facial recognition system is being deployed at airports in order to scan passengers' faces and compare them to a database of vaccinations, in order to identify unvaccinated passengers in a pandemic.
There are a number of components involved including cameras, a model to segment the image, and a model to identify the face and match it against a known photograph. It is important that there are few false negatives, and that passengers cannot subvert the system.
Which ONE of the following types of testing is the MOST appropriate options for the tests you would choose in system testing?
Answer: A
Explanation:
Adversarial testing is the most appropriate approach in this case because the system needs to be robust against attempts to subvert it (e.g., by using masks, photos, or other methods to deceive the system). Adversarial testing specifically focuses on identifying vulnerabilities where attackers may try to manipulate or bypass the system's security or functionality, ensuring that the facial recognition system is resilient against such tactics.
NEW QUESTION # 12
Which ONE of the following statements is MOST true about black box adversarial testing?
Answer: C
Explanation:
The correct answer is B . The CT-AI syllabus explains that black-box adversarial attacks involve exploring the model to determine its functionality and then building a duplicate model with similar functionality. The attacker then uses a white-box approach on the duplicate model to identify adversarial examples. Because adversarial examples are generally transferable, those examples will normally also work on the original model.
Option A describes white-box adversarial testing, where the algorithm, model settings, and parameters are known. Option C describes data poisoning , where training data is manipulated to induce incorrect future predictions or create vulnerabilities. Option D describes pairwise or broader combinatorial testing, which is used where many parameters and values make exhaustive testing impractical. Black-box adversarial testing is instead based on limited knowledge of the target model and the empirical transferability of adversarial examples. If a duplicate model cannot be built, the syllabus also notes that high-volume automated testing may be used to discover adversarial examples and observe results.
References/topics: CT-AI Syllabus Chapter 9, Section 9.1.1 "Adversarial Attacks"; Section 9.1.2 "Data Poisoning."
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NEW QUESTION # 13
Which of the following characteristics of AI-based systems make it more difficult to ensure they are safe?
Answer: C
Explanation:
AI-based systems oftenexhibit non-deterministic behavior, meaning theydo not always produce the same output for the same input. This makesensuring safety more difficult, as the system's behavior can change based on new data, environmental factors, or updates.
* Why Non-determinism Affects Safety:
* In traditional software, the same input always produces the same output.
* In AI systems, outputsvary probabilisticallydepending on learned patterns and weights.
* This unpredictability makes itharder to verify correctness, reliability, and safety, especially in critical domains likeautonomous vehicles, medical AI, and industrial automation.
* A (Simplicity):AI-based systems are typicallycomplex, not simple, which contributes to safety challenges.
* B (Sustainability):While sustainability is an important AI consideration, it doesnot directly affect safety.
* D (Robustness):Lack of robustnesscan make AI systems unsafe, butnon-determinism is the primary issuethat complicates safety verification.
* ISTQB CT-AI Syllabus (Section 2.8: Safety and AI)
* "The characteristics of AI-based systems that make it more difficult to ensure they are safe include: complexity, non-determinism, probabilistic nature, self-learning, lack of transparency, interpretability and explainability, lack of robustness".
Why Other Options Are Incorrect:Supporting References from ISTQB Certified Tester AI Testing Study Guide:Conclusion:Sincenon-determinism makes AI behavior unpredictable, complicating safety assurance, thecorrect answer is C.
NEW QUESTION # 14
Which of the following options BEST describes an example of reinforcement learning?
Answer: D
Explanation:
The correct answer is A . Reinforcement learning is described in the CT-AI syllabus as an approach in which an intelligent agent learns by interacting with its environment iteratively and learning from experience. The agent receives rewards for correct decisions and penalties for incorrect decisions. The syllabus also identifies robotics, autonomous vehicles, and chatbots as application examples for reinforcement learning.
A house-cleaning robot that adjusts its path based on route efficiency and dirt removed fits this pattern closely. It acts in an environment, observes results, and improves its behaviour according to an implicit reward such as efficient coverage and cleaning effectiveness. Option B may involve optimization, but the description is less clearly framed around agent-environment interaction and reward-based trial learning.
Option C describes data acquisition for supervised or self-improving image recognition, not reinforcement learning. Option D describes predictive modelling based on historical labelled or structured data, which is more consistent with supervised learning.
References/topics: CT-AI Syllabus Chapter 3, Section 3.1.3 "Reinforcement Learning."
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NEW QUESTION # 15
A local business has a mail pickup/delivery robot for their office. The robot currently uses a track to move between pickup/drop off locations. When it arrives at a destination, the robot stops to allow a human to remove or deposit mail.
The office has decided to upgrade the robot to include AI capabilities that allow the robot to perform its duties without a track, without running into obstacles, and without human intervention.
The test team is creating a list of new and previously established test objectives and acceptance criteria to be used in the testing of the robot upgrade. Which of the following test objectives will test an AI quality characteristic for this system?
Answer: D
Explanation:
AI-based systems have specific quality characteristics, includingevolution,autonomy, andadaptability. A test objective that evaluates whether an AI systemevolvesto improve performance over time directly aligns with AI quality characteristics.
Explanation of Answer Choices:
* Option A: The robot must evolve to optimize its routing.
* Correct.Evolution is an AI quality characteristic that ensures the systemlearns from past experiencesand adapts to improve efficiency.
* Option B: The robot must recharge for no more than six hours a day.
* Incorrect.This is an operational constraint rather than an AI-specific quality characteristic.
* Option C: The robot must record the time of each delivery which is compiled into a report.
* Incorrect.Logging data does not relate to AI quality characteristics likeadaptability or autonomy.
* Option D: The robot must complete 99.99% of its deliveries each day.
* Incorrect.This is a performance target rather than an AI quality characteristic.
ISTQB CT-AI Syllabus References:
* Evolution as an AI Quality Characteristic:"Check how well the system learns from its own experience. Check how well the system copes when the profile of data changes (i.e., concept drift)".
Thus,Option A is the best choice as it directly tests an AI quality characteristic (evolution) in the upgraded autonomous robot.
NEW QUESTION # 16
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