STUDY SALESFORCE-AI-ASSOCIATE GROUP & CERTIFICATION SALESFORCE-AI-ASSOCIATE TEST ANSWERS

Study Salesforce-AI-Associate Group & Certification Salesforce-AI-Associate Test Answers

Study Salesforce-AI-Associate Group & Certification Salesforce-AI-Associate Test Answers

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Salesforce Salesforce-AI-Associate Exam Syllabus Topics:

TopicDetails
Topic 1
  • AI Fundamentals: This topic discusses the major principles and applications of AI within Salesforce. It also focuses on different types of AI and their capabilities.
Topic 2
  • Ethical Considerations of AI: It delves into the ethical challenges of AI such as human bias in machine learning, lack of transparency, etc. The topic also explains how to apply the Trusted AI Principles of Salesforce to given scenarios.
Topic 3
  • Data for AI: Questions about the importance of data quality and different elements or components of data quality are related to this topic.
Topic 4
  • AI Capabilities in CRM: Get familiar with the benefits of AI and capabilities of CRM.

Salesforce Certified AI Associate Exam Sample Questions (Q85-Q90):

NEW QUESTION # 85
What can bias in AI algorithms in CRM lead to?

  • A. Personalization and target marketing changes
  • B. Ethical challenges in CRM systems
  • C. Advertising cost increases

Answer: B

Explanation:
Explanation
"Bias in AI algorithms in CRM can lead to ethical challenges in CRM systems. Bias means that AI algorithms favor or discriminate certain groups or outcomes based on irrelevant or unfair criteria. Bias can affect the fairness and ethics of CRM systems, as they may affect how customers are perceived, treated, or represented by AI algorithms. For example, bias can lead to ethical challenges in CRM systems if AI algorithms make inaccurate or harmful predictions or recommendations based on customers' identity or characteristics."


NEW QUESTION # 86
Cloud kicks wants to develop a solution to predict customers' interest based on historical data. The company found that employee region uses a text field to capture the product category while employee from all other locations use a picklist.
Which dimensionof data quality is affected in this scenario?

  • A. Consistency
  • B. Completeness
  • C. Accuracy

Answer: A

Explanation:
"Consistency is the dimension of data quality that is affected in this scenario. Consistency means that the data values are uniform and follow a common standard or format across different records, fields, or sources.
Inconsistent data can cause confusion, errors, or duplication in data analysis and processing. For example, using different field types for the same attribute can affect the consistency of the data."


NEW QUESTION # 87
What role does data quality play in the ethical us of AI applications?

  • A. Low-quality data reduces the risk of unintended bias as the data is not overfitted to demographic groups.
  • B. High-quality data ensures the process of demographic attributes requires for personalized campaigns.
  • C. High-quality data is essential for ensuring unbased and for fair AI decisions, promoting ethical use, and preventing discrimi...

Answer: C

Explanation:
Explanation
"High-quality data is essential for ensuring unbiased and fair AI decisions, promoting ethical use, and preventing discrimination. High-quality data means that the data is accurate, complete, consistent, relevant, and timely for the AI task. High-quality data can help ensure unbiased and fair AI decisions by providing a balanced and representative sample of the target population or domain. High-quality data can also help promote ethical use and prevent discrimination by respecting the rights and preferences of users regarding their personal data."


NEW QUESTION # 88
How does a data quality assessment impact business outcome for companies using AI?

  • A. Improves the speed of AI recommendations
  • B. Accelerates the delivery of new AI solutions
  • C. Provides a benchmark for AI predictions

Answer: C

Explanation:
"A data quality assessment impacts business outcomes for companies using AI by providing a benchmark for AI predictions. A data quality assessment is a process that measures and evaluates the quality of data for a specific purpose or task. A data quality assessment can help identify and address any issues or gaps in the data quality dimensions, such as accuracy, completeness, consistency, relevance, and timeliness. A data quality assessment can impact business outcomes for companies using AI by providing a benchmark for AIpredictions, as it can help ensure that the predictions are based on high-quality data that reflects the true state or condition of the target population or domain."


NEW QUESTION # 89
What is a potential outcome of using poor-quality data in AI application?

  • A. AI model training becomes slower and less efficient
  • B. AI models become more interpretable
  • C. AI models may produce biased or erroneous results.

Answer: C

Explanation:
"A potential outcome of using poor-quality data inAI applications is that AI models may produce biased or erroneous results. Poor-quality data means that the data is inaccurate, incomplete, inconsistent, irrelevant, or outdated for the AI task. Poor-quality data can affect the performance and reliabilityof AI models, as they may not have enough or correct information to learn from or make accurate predictions. Poor-quality data can also introduce or exacerbate biases or errors in AI models, such as human bias, societal bias, confirmation bias, or overfitting or underfitting."


NEW QUESTION # 90
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The Salesforce-AI-Associate exam is highly competitive and acing it is not a piece of cake for majority of the people. It requires a great skill set and deep knowledge Salesforce-AI-Associate Exam Questions. An aspirant achieving Salesforce Certified AI Associate Exam (Salesforce-AI-Associate) certificate truly reflects his hard work and consistent struggle. These Salesforce-AI-Associate exam practice test a person's true capacities and passing it requires extensive knowledge of each Salesforce-AI-Associate topic.

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