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Salesforce Salesforce-AI-Associate Latest Dumps Pdf | Salesforce-AI-Associate Dump Torrent

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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

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

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

Topic 4

Data for AI: Questions about the importance of data quality and different elements or components of data quality are related to this topic.

Salesforce Certified AI Associate Exam Sample Questions (Q94-Q99):

NEW QUESTION # 94
A business analyst (BA) is preparing a new use case for Al. They run a report to check for null values in the attributes they plan to use.
Which data quality component Is the BA verifying by checking for null values?

A. Usage
B. Duplication
C. Completeness

Answer: C

Explanation:
By checking for null values, a business analyst (BA) is verifying the data quality component of completeness.
Completeness refers to the absence of missing values or gaps in the data, which is essential for the accuracy and reliability of reports and analytics used in AI models. Null values can indicate incomplete data, which may adversely affect the performance of AI applications by leading to incorrect predictions or insights.
Salesforce emphasizes the importance of data completeness for effective data analysis and provides tools for data quality assessment and improvement. Details on handling data completeness in Salesforce can be explored at Salesforce Help Data Management.

NEW QUESTION # 95
A Salesforce administrator creates a new field to capture an order's destination country.
Which field type should they use to ensure data quality?

A. Number
B. Picklist
C. Text

Answer: B

Explanation:
Explanation
"A picklist field type should be used to ensure data quality for capturing an order's destination country. A picklist field type allows the user to select one or more predefined values from a list. A picklist field type can ensure data quality by enforcing consistency, accuracy, and completeness of the data values."

NEW QUESTION # 96
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 dimension of data quality is affected in this scenario?

A. Accuracy
B. Completeness
C. Consistency

Answer: C

Explanation:
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 andprocessing. For example, using different field types for the same attribute can affect the consistency of the data."

NEW QUESTION # 97
A financial institution plans a campaign for preapproved credit cards?
How should they implement Salesforce's Trusted AI Principle of Transparency?

A. Incorporate customer feedback into the model's continuous training.
B. Flagsensitive variables and their proxies to prevent discriminatory lending practices.
C. Communicate how risk factors such as credit score can impact customer eligibility.

Answer: B

Explanation:
"Flagging sensitive variables and their proxies to prevent discriminatory lending practicesis how they should implement Salesforce's Trusted AI Principle of Transparency. Transparency is one of the Trusted AI Principles that states that AI systems should be designed and developed with respect for clarity and openness in how they work and why they make certain decisions. Transparency also means that AI users should be able to access relevant information and documentation about the AI systems they interact with. Flagging sensitive variables and their proxies means identifying and marking variablesthat can potentially cause discrimination or unfair treatment based on a person's identity or characteristics, such as age, gender, race, income, or credit score. Flagging sensitive variables and their proxies can help implement Transparency by allowing users to understand and evaluate the data used or generated by AI systems."

NEW QUESTION # 98
What is an implication of user consent in regard to AI data privacy?

A. AI operates Independently of user privacy and consent.
B. AI ensures complete data privacy by automatically obtaining user consent.
C. AI infringes on privacy when user consent is not obtained.

Answer: C

Explanation:
"AI infringes on privacy when user consent is not obtained. User consent is the permission or agreement given by a user to allow their personal data to be collected, used, shared, or stored byothers. User consent is an important aspect of data privacy, which is the right of individuals to control how their personal data is handled by others. AI infringes on privacy when user consent is not obtained because it violates the user's rights and preferences regarding their personal data."

NEW QUESTION # 99
......

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