SISA CSPAI Exam Practice Test Instant Access

Question 1

When integrating LLMs using a Prompting Technique, what is a significant challenge in achieving consistent performance across diverse applications?

AHandling the security concerns that arise from dynamically generated prompts

BOvercoming the lack of transparency in understanding how the LLM interprets varying prompt structures.

CThe need for optimizing prompt templates to ensure generalization across different contexts.

DReducing latency in generating responses to meet real-time application requirements.

Answer : C

Question 2

A company's chatbot, Tay, was poisoned by malicious interactions. What is the primary lesson learned from this case study?

AContinuous live training is essential for enhancing chatbot performance.

BEncrypting user data can prevent such attacks

COpen interaction with users without safeguards can lead to model poisoning and generation of inappropriate content.

DChatbots should have limited conversational abilities to prevent poisoning.

Answer : C

Question 3

In a machine translation system where context from both early and later words in a sentence is crucial, a team is considering moving from RNN-based models to Transformer models. How does the self-attention mechanism in Transformer architecture support this task?

ABy processing words in strict sequential order, which is essential for capturing meaning

BBy considering all words in a sentence equally and simultaneously, allowing the model to establish long-range dependencies.

CBy assigning a constant weight to each word, ensuring uniform translation output

DBy focusing only on the most recent word in the sentence to speed up translation

Answer : B

Question 4

How does ISO 27563 support privacy in AI systems?

ABy providing guidelines for privacy-enhancing technologies in AI.

BBy mandating the use of specific encryption algorithms.

CBy limiting AI to non-personal data only.

DBy focusing on performance metrics over privacy.

Answer : A

Question 5

In a time-series prediction task, how does an RNN effectively model sequential data?

ABy focusing on the overall sequence structure rather than individual time steps for a more holistic approach.

BBy processing each time step independently, optimizing the model's performance over time.

CBy storing only the most recent time step, ensuring efficient memory usage for real-time predictions

DBy using hidden states to retain context from prior time steps, allowing it to capture dependencies across the sequence.

Answer : D

Question 6

In line with the US Executive Order on AI, a company's AI application has encountered a security vulnerability. What should be prioritized to align with the order's expectations?

AImplementing a rapid response to address and remediate the vulnerability, followed by a review of security practices.

BImmediate public disclosure of the vulnerability.

CHalting all AI projects until a full investigation is complete.

DIgnoring the vulnerability if it does not affect core functionalities.

Answer : A

Question 7

How does machine learning improve the accuracy of predictive models in finance?

ABy using historical data patterns to make predictions without updates

BBy relying exclusively on manual adjustments and human input for predictions.

CBy continuously learning from new data patterns to refine predictions

DBy avoiding any use of past data and focusing solely on current trends

Answer : C

SISA Certified Security Professional in Artificial Intelligence CSPAI Exam Practice Test