Infosys Certified Responsible AI Practitioner
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Join Premium10 Infosys Certified Responsible AI Practitioner practice questions with answers
Real Lex exam-pattern multiple-choice questions for the Infosys Certified Responsible AI Practitioner certification. Each question includes the correct answer. The full question bank is available to Premium members.
- Question 1
An AI-based system is used to predict parole outcomes, but it is criticized for lacking transparency in its decision-making process. What is the most effective approach to improve trust in this system?
- ✓Reduce the number of variables in the model to simplify the decision-making process.Correct
- BDevelop a user-friendly interface that shows only the final decisions without details.
- CImplement explainable AI techniques that clarify how decisions are made and what factors influence them.
- DIncrease the training data size without changing the algorithm to enhance accuracy.
- Question 2
Generative AI models like GPT and Stable Diffusion differ from traditional machine learning models in several ways. Which of the following statements accurately reflects a challenge unique to generative AI?
- ✓Generative models are inherently more accurate than discriminative models due to their training on massive datasets.Correct
- BGenerative AI is less susceptible to biases because it generates outputs from scratch without predefined categories.
- CThe unpredictability of output quality necessitates human oversight to ensure cultural sensitivity and appropriateness.
- DGenerative AI models produce outputs that are always factually correct and reliable, reducing the need for human intervention.
- Question 3
In the context of generative AI, the term "hallucinations" refers to the generation of fabricated information. Which of the following scenarios best illustrates the potential risks associated with this phenomenon?
- ✓A generative model accurately generates a fictional story based on user prompts, without any factual errors.Correct
- BAn AI system misattributes an invention to the wrong individual, leading to a public relations issue for a tech company.
- CA generative AI chat interface provides consistent and accurate medical advice to users, enhancing their understanding of health issues.
- DA corporate training program uses AI-generated content that perfectly aligns with the company’s established guidelines.
- Question 4
What is a significant concern related to the lack of transparency in AI systems?
- ✓AI systems are always accurate and reliable.Correct
- BIndividuals may not understand how AI systems make decisions, leading to mistrust.
- CAI systems cannot be trained on biased data.
- DTransparency guarantees ethical behavior in AI technologies.
- Question 5
What issue was identified with AI algorithms used during the COVID-19 pandemic?
- ✓They accurately diagnosed all patients without error.Correct
- BThey were trained on mislabeled or unverified data, leading to flawed assessments.
- CThey significantly reduced the need for human medical staff.
- DThey could predict patient outcomes with complete accuracy.
- Question 6
Which of the following measures is NOT mentioned as a way to foster accountability in AI systems?
- ✓Regular audits and evaluations of AI systemsCorrect
- BEstablishing clear lines of responsibility
- CIncreasing the complexity of AI algorithms
- DImplementing legal and regulatory frameworks
- Question 7
To ensure fairness in AI systems, which practice is recommended for mitigating bias?
- ✓Collecting data from a single demographic groupCorrect
- BEngaging with diverse stakeholders during development
- CReducing transparency in decision-making processes
- DLimiting user control over personal data
- Question 8
What is the primary goal of data minimization in the context of Responsible AI?
- ✓To collect as much data as possible for analysisCorrect
- BTo restrict personal data collection to the minimum necessary
- CTo ensure all data is stored indefinitely
- DTo enhance the complexity of data processing
- Question 9
Which of the following techniques is specifically designed to provide local interpretability for complex AI models by approximating their behavior with a simpler model?
- ✓Interpretability by DesignCorrect
- BProxy Modeling
- CCounterfactual Explanations
- DLayer-wise Relevance Propagation
- Question 10
What is a primary benefit of implementing explainability in AI systems?
- ✓Ensuring AI systems do not discriminate against certain groups.Correct
- BPrioritizing complex algorithms that provide the most accurate results.
- CTo provide clear and understandable reasoning behind an AI's actions.
- DConsidering potential risks and taking steps to mitigate them
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