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Exam Salesforce-AI-Associate Guide Materials & Salesforce-AI-Associate Reliable Test Review

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Salesforce Salesforce-AI-Associate Exam Syllabus Topics:

Topic
Details

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

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 Capabilities in CRM: Get familiar with the benefits of AI and capabilities of CRM.

Topic 4

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.

Salesforce Certified AI Associate Exam Sample Questions (Q30-Q35):

NEW QUESTION # 30
Why is it critical to consider privacy concerns when dealing with AI and CRM data?

A. Ensures compliance with laws and regulations
B. Confirms the data is accessible to all users
C. Increases the volume of data collected

Answer: A

Explanation:
Explanation
"It is critical to consider privacy concerns when dealing with AI and CRM data because it ensures compliance with laws and regulations. Data privacy is the right of individuals to control how their personal data is collected, used, shared, or stored by others. Data privacy laws and regulations are legal frameworks that define and enforce the rights and obligations of data subjects, data controllers, and data processors regarding personal data. Data privacy laws and regulations vary by country, region, or industry, and may impose different requirements or restrictions on how AI and CRM data can be handled."

NEW QUESTION # 31
What is one technique to mitigate bias and ensure fairness in AI applications?

A. Using data that contains more examples of minority groups than majority groups
B. Excluding data features from the Al application to benefit a population
C. Ongoing auditing and monitoring of data that is used in AI applications

Answer: C

Explanation:
A technique to mitigate bias and ensure fairness in AI applications is ongoing auditing and monitoring of the data used in AI applications. Regular audits help identify and address any biases that may exist in the data, ensuring that AI models function fairly and without prejudice. Monitoring involves continuously checking the performance of AI systems to safeguard against discriminatory outcomes. Salesforce emphasizes the importance of ethical AI practices, including transparency and fairness, which can be further explored through Salesforce's AI ethics guidelines at Salesforce AI Ethics.

NEW QUESTION # 32
How is natural language processing (NLP) used in the context of AI capabilities?

A. To cleanse and prepare data for AI implementations
B. To interpret and understand programminglanguage
C. To understand and generate human language

Answer: C

Explanation:
"Natural language processing (NLP) is used in the context of AI capabilities to understand and generate human language. NLP can enable AI systems to interact with humans using natural language, such as speech or text. NLP can also enable AI systems to analyze and extract information from natural language data, such as documents, emails, or social media posts."

NEW QUESTION # 33
Cloud Kicks relies on data analysis to optimize its product recommendations for customers.
How will incomplete data quality impact the company's recommendations?

A. The diversity of the product
B. The accuracy of the product
C. The response time for the product

Answer: B

Explanation:
Incomplete data quality negatively impacts the accuracy of product recommendations made by Cloud Kicks.
If data is missing or incomplete, the AI models used for product recommendation may not have enough information to accurately predict customer preferences and behavior. This leads to recommendations that may not align well with customer needs, reducing customer satisfaction and potentially affecting sales.
Ensuring complete and accurate data is crucial for effective recommendation systems. Salesforce discusses the impact of data quality on AI outcomes and strategies to enhance data integrity in their documentation on AI and data management, which can be referenced at Data Management for AI.

NEW QUESTION # 34
What can bias in AI algorithms in CRM lead to?

A. Personalization and target marketing changes
B. Advertising cost increases
C. Ethical challengesin CRM systems

Answer: C

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 andethics 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 # 35
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