Salesforce-AI-Associate PDF VCE, Salesforce-AI-Associate Latest Test Questions

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Salesforce - Efficient Salesforce-AI-Associate PDF VCE

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Salesforce Salesforce-AI-Associate Exam Syllabus Topics:

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

Salesforce Certified AI Associate Exam Sample Questions (Q65-Q70):

NEW QUESTION # 65
Cloud Kicks implements a new product recommendation feature for its shoppers that recommends shoes of a given color to display to customers based on the color of the products from their purchase history.
Which type of bias is most likely to be encountered in this scenario?

A. Survivorship
B. Societal
C. Confirmation

Answer: C

Explanation:
"Confirmation bias is most likely to be encountered in this scenario. Confirmation bias is a type of bias that occurs when data or information confirms or supports one'sexisting beliefs or expectations. For example, confirmation bias can occur when a product recommendation feature only recommends shoes of a given color based on the customer's purchase history, without considering other factors or preferences that may influence their choice."

NEW QUESTION # 66
Which statement exemplifies Salesforces honesty guideline when training AI models?

A. Ensure appropriate consent and transparency when using AI-generated responses.
B. Minimize the AI models carbon footprint and environment impact during training.
C. Control bias, toxicity, and harmful content with embedded guardrails and guidance.

Answer: A

Explanation:
Explanation
"Ensuring appropriate consent and transparency when using AI-generated responses is a statement that exemplifies Salesforce's honesty guideline when training AI models. Salesforce's honesty guideline is one of the Trusted AI Principles that states that AI systems should be designed and developed with respect for honesty and integrity in how they work and what they produce. Ensuring appropriate consent and transparency means respecting and honoring the choices and preferences of users regarding how their data is used or generated by AI systems. Ensuring appropriate consent and transparency also means providing clear and accurate information and documentation about the AI systems and their outputs."

NEW QUESTION # 67
What can bias in AI algorithms in CRM lead to?

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

Answer: A

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 # 68
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. Streamlines case management by categorizing and tracking customer support cases, identifying topics, and summarizing case resolutions
C. Improves CRM security protocols, safeguarding sensitive customer data from potential breaches and threats

Answer: B

NEW QUESTION # 69
What is a possible outcome of poor data quality?

A. AI predictions become more focused and less robust.
B. Biases in data can be inadvertently learned and amplified by AI systems.
C. AI models maintain accuracy but have slower response times.

Answer: B

Explanation:
Explanation
"A possible outcome of poor data quality is that biases in data can be inadvertently learned and amplified by AI systems. Poor data quality means that the data is inaccurate, incomplete, inconsistent, irrelevant, or outdated for the AI task. Poor data quality can affect the performance and reliability of AI systems, as they may not have enough or correct information to learn from or make accurate predictions. Poor data quality can also introduce or exacerbate biases in data, such as human bias, societal bias, or confirmation bias, which can affect the fairness and ethics of AI systems."

NEW QUESTION # 70
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SALESFORCE-AI-ASSOCIATE PDF VCE, SALESFORCE-AI-ASSOCIATE LATEST TEST QUESTIONS

Salesforce-AI-Associate PDF VCE, Salesforce-AI-Associate Latest Test Questions