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Salesforce Salesforce-AI-Associate Exam Syllabus Topics:

Topic	Details
Topic 1	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 2	Data for AI: Questions about the importance of data quality and different elements or components of data quality are related to this topic.
Topic 3	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 4	AI Capabilities in CRM: Get familiar with the benefits of AI and capabilities of CRM.

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Salesforce Certified AI Associate Exam Sample Questions (Q38-Q43):

NEW QUESTION # 38
What is a potential outcome of using poor-quality data in AI application?

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

Answer: A

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 Poor-quality data means that the data is inaccurate, incomplete, inconsistent, irrelevant, or outdated for the AI task.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 # 39
Cloud Kicks uses Einstein to generate predictions but is not seeing accurate results. What is a potential reason for this?

A. Poor data quality
B. The wrong product
C. Too much data

Answer: A

Explanation:
AI models rely on high-quality data to produce accurate and reliable predictions. Poor data quality-such as missing values, inconsistent formatting, or biased data-can negatively impact AI performance.
Option A (Incorrect): If Cloud Kicks is using Einstein AI, it is unlikely that they are using the wrong product, as Einstein is designed for predictive analytics. The issue is more likely related to data quality or model training.
Option B (Correct): Poor data quality is one of the most common reasons for inaccurate AI predictions. If the input data contains errors, biases, or incomplete information, the AI model will generate flawed insights.
Regular data cleaning and preprocessing are essential for improving prediction accuracy.
Option C (Incorrect): Having too much data does not necessarily result in inaccurate predictions. In fact, more data can improve model performance if properly structured and cleaned. However, if the data is noisy or unstructured, it may lead to inconsistencies.

NEW QUESTION # 40
Cloud Kicks wants to create a custom service analytics application to analyze cases in Salesforce. The application should rely on accurate data to ensure efficient case resolution.
Whichdata quality dimension Is essential for this custom application?

A. Age
B. Consistency
C. Duplication

Answer: B

Explanation:
"Consistency is the data quality dimension that is essential for creating a custom service analytics application to analyze cases in Salesforce. Consistency means that the data values are uniform and follow a common standard or format across different records, fields, or sources. Consistent data can ensure that the custom application can accurately and efficiently analyze cases and provide meaningful insights."

NEW QUESTION # 41
What should be done to prevent bias from entering an AI system when training it?

A. Import diverse training data.
B. Use alternative assumptions.
C. Include Proxy variables.

Answer: A

Explanation:
Explanation
"Using diverse training data is what should be done to prevent bias from entering an AI system when training it. Diverse training data means that the data covers a wide range of features andpatterns that are relevant for the AI task. Diverse training data can help prevent bias by ensuring that the AI system learns from a balanced and representative sample of the target population or domain. Diverse training data can also help improve the accuracy and generalization of the AI system by capturing more variations and scenarios in the data."

NEW QUESTION # 42
What is the role of Salesforce Trust AI principles in the context of CRM system?

A. Providing a framework for AI data model accuracy
B. Outlining the technical specifications for AI integration
C. Guiding ethical and responsible use of AI

Answer: C

Explanation:
Explanation
"The role of Salesforce Trust AI principles in the context of CRM systems is guiding ethical and responsible use of AI. Salesforce Trust AI principles are a set of guidelines and best practices for developing and using AI systems in a responsible and ethical way. The principles include Accountability, Fairness & Equality, Transparency & Explainability, Privacy & Security, Reliability & Safety, Inclusivity & Diversity, Empowerment & Education. The principles aim to ensure that AI systems are aligned with the values and interests of customers, partners, and society."

NEW QUESTION # 43
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