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High Pass-Rate Salesforce-AI-Associate Reliable Exam Prep - Easy and Guaranteed Salesforce-AI-Associate Exam Success

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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

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

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

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 (Q24-Q29):

NEW QUESTION # 24
What is the significance of explainability of trusted AI systems?

A. Increases the complexity of AI models
B. Enhances the security and accuracy of AI models
C. Describes how Al models make decisions

Answer: C

Explanation:
The significance of the explainability of trusted AI systems is that it describes how AI models make decisions. Explainability is crucial for building trust and accountability in AI systems, ensuring that users and stakeholders understand the decision-making processes and outcomes generated by AI. This is particularly important in scenarios where AI decisions impact personal or financial status, such as in credit scoring or healthcare diagnostics. Salesforce emphasizes the importance of explainable AI through its ethical AI practices, aiming to make AI systems more transparent and understandable. More details about Salesforce's approach to ethical and explainable AI can be found in Salesforce AI ethics resources at Salesforce AI Ethics.

NEW QUESTION # 25
What is a sensitive variable that car esc to bias?

A. Education level
B. Country
C. Gender

Answer: C

Explanation:
"Gender is a sensitive variable that can leadto bias. A sensitive variable is a variable that can potentially cause discrimination or unfair treatment based on a person's identity or characteristics. For example, gender is a sensitive variable because it can affect how people are perceived, treated,or represented by AI systems."

NEW QUESTION # 26
Which type of bias imposes a system 's values on others?

A. Automation
B. Societal
C. Association

Answer: B

NEW QUESTION # 27
What are some key benefits of AI in improving customer experiences in CRM?

A. Fully automates the customer service experience, ensuring seamless automated interactions with customers
B. Improves CRM security protocols, safeguarding sensitive customer data from potential breaches and threats
C. Streamlines case management by categorizing and tracking customer support cases, identifying topics, and summarizing case resolutions

Answer: C

Explanation:
Explanation
"Streamlining case management by categorizing and tracking customer support cases, identifying topics, and summarizing case resolutions are some key benefits of AI in improving customer experiences in CRM. AI can help automate and optimize various aspects of customer service, such as routing cases to the right agents, providing relevant information or suggestions, and generating reports or insights. AI can also help enhance customer satisfaction and loyalty by reducing wait times, improving response quality, and providing personalized solutions."

NEW QUESTION # 28
What is the main focus of the Accountability principle in Salesforce's Trusted AI Principles?

A. Ensuring transparency In Al-driven recommendations and predictions
B. Taking responsibility for one's actions toward customers, partners, and society
C. Safeguarding fundamental human rights and protecting sensitive data

Answer: B

Explanation:
Explanation
"The main focus of the Accountability principle in Salesforce's Trusted AI Principles is taking responsibility for one's actions toward customers, partners, and society. Accountability means that AI systems should be designed and developed with respect for the impact and consequences of their actions on others.
Accountability also means that AI developers and users should be aware of and adhere to the ethical, legal, and regulatory standards and expectations of their industry and domain."

NEW QUESTION # 29
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