VALID CT-AI_V1.0_WORLD VCE - VALID CT-AI_V1.0_WORLD EXAM BOOTCAMP

Valid CT-AI_v1.0_World Vce - Valid CT-AI_v1.0_World Exam Bootcamp

Valid CT-AI_v1.0_World Vce - Valid CT-AI_v1.0_World Exam Bootcamp

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ISQI ISTQB Certified Tester AI Testing (v1.0) Sample Questions (Q28-Q33):

NEW QUESTION # 28
Which ONE of the following characteristics is the least likely to cause safety related issues for an Al system?
SELECT ONE OPTION

  • A. High complexity
  • B. Self-learning
  • C. Non-determinism
  • D. Robustness

Answer: D

Explanation:
The question asks which characteristic is least likely to cause safety-related issues for an AI system. Let's evaluate each option:
* Non-determinism (A): Non-deterministic systems can produce different outcomes even with the same inputs, which can lead to unpredictable behavior and potential safety issues.
* Robustness (B): Robustness refers to the ability of the system to handle errors, anomalies, and unexpected inputs gracefully. A robust system is less likely to cause safety issues because it can maintain functionality under varied conditions.
* High complexity (C): High complexity in AI systems can lead to difficulties in understanding, predicting, and managing the system's behavior, which can cause safety-related issues.
* Self-learning (D): Self-learning systems adapt based on new data, which can lead to unexpected changes in behavior. If not properly monitored and controlled, this can result in safety issues.
References:
* ISTQB CT-AI Syllabus Section 2.8 on Safety and AI discusses various factors affecting the safety of AI systems, emphasizing the importance of robustness in maintaining safe operation.


NEW QUESTION # 29
Data used for an object detection ML system was found to have been labelled incorrectly in many cases.
Which ONE of the following options is most likely the reason for this problem?
SELECT ONE OPTION

  • A. Bias issues
  • B. Accuracy issues
  • C. Privacy issues
  • D. Security issues

Answer: B


NEW QUESTION # 30
Pairwise testing can be used in the context of self-driving cars for controlling an explosion in the number of combinations of parameters.
Which ONE of the following options is LEAST likely to be a reason for this incredible growth of parameters?
SELECT ONE OPTION

  • A. Different features like ADAS, Lane Change Assistance etc.
  • B. Different weather conditions
  • C. ML model metrics to evaluate the functional performance
  • D. Different Road Types

Answer: C

Explanation:
Pairwise testing is used to handle the large number of combinations of parameters that can arise in complex systems like self-driving cars. The question asks which of the given options isleast likelyto be a reason for the explosion in the number of parameters.
* Different Road Types (A): Self-driving cars must operate on various road types, such as highways, city streets, rural roads, etc. Each road type can have different characteristics, requiring the car's system to adapt and handle different scenarios. Thus, this is a significant factor contributing to the growth of parameters.
* Different Weather Conditions (B): Weather conditions such as rain, snow, fog, and bright sunlight significantly affect the performance of self-driving cars. The car's sensors and algorithms must adapt to these varying conditions, which adds to the number of parameters that need to be considered.
* ML Model Metrics to Evaluate Functional Performance (C): While evaluating machine learning (ML) model performance is crucial, it does not directly contribute to the explosion of parameter combinations in the same way that road types, weather conditions, and car features do. Metrics are used to measure and assess performance but are not themselves variable conditions that the system must handle.
* Different Features like ADAS, Lane Change Assistance, etc. (D): Advanced Driver Assistance Systems (ADAS) and other features add complexity to self-driving cars. Each feature can have multiple settings and operational modes, contributing to the overall number of parameters.
Hence, theleast likelyreason for the incredible growth in the number of parameters isC. ML model metrics to evaluate the functional performance.
References:
* ISTQB CT-AI Syllabus Section 9.2 on Pairwise Testing discusses the application of this technique to manage the combinations of different variables in AI-based systems, including those used in self-driving cars.
* Sample Exam Questions document, Question #29 provides context for the explosion in parameter combinations in self-driving cars and highlights the use of pairwise testing as a method to manage this complexity.


NEW QUESTION # 31
Which ONE of the following options represents a technology MOST TYPICALLY used to implement Al?
SELECT ONE OPTION

  • A. Procedural programming
  • B. Search engines
  • C. Genetic algorithms
  • D. Case control structures

Answer: C

Explanation:
Technology Most Typically Used to Implement AI:Genetic algorithms are a well-known technique used in AI. They are inspired by the process of natural selection and are used to find approximate solutions to optimization and search problems. Unlike search engines, procedural programming, or case control structures, genetic algorithms are specifically designed for evolving solutions and are commonly employed in AI implementations.
Reference:ISTQB_CT-AI_Syllabus_v1.0, Section 1.4 AI Technologies, which identifies different technologies used to implement AI.


NEW QUESTION # 32
In a conference on artificial intelligence (Al), a speaker made the statement, "The current implementation of Al using models which do NOT change by themselves is NOT true Al*. Based on your understanding of Al, is this above statement CORRECT or INCORRECT and why?
SELECT ONE OPTION

  • A. This statement is correct. In general, what is considered Al today may change over time.
  • B. This statement is incorrect. What is considered Al today will continue to be Al even as technology evolves and changes.
  • C. This statement is incorrect. Current Al is true Al and there is no reason to believe that this fact will change over time.
  • D. This statement is correct. In general, today the term Al is utilized incorrectly.

Answer: A

Explanation:
A: This statement is incorrect. Current AI is true AI and there is no reason to believe that this fact will change over time.
* AI is an evolving field, and the definition of what constitutes AI can change as technology advances.
B: This statement is correct. In general, what is considered AI today may change over time.
* The term AI is dynamic and has evolved over the years. What is considered AI today might be viewed as standard computing in the future. Historically, as technologies become mainstream, they often cease to be considered "AI".
C: This statement is incorrect. What is considered AI today will continue to be AI even as technology evolves and changes.
* This perspective does not account for the historical evolution of the definition of AI. As new technologies emerge, the boundaries of AI shift.
D: This statement is correct. In general, today the term AI is utilized incorrectly.
* While some may argue this, it is not a universal truth. The term AI encompasses a broad range of technologies and applications, and its usage is generally consistent with current technological capabilities.


NEW QUESTION # 33
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