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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

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

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

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

Salesforce Certified AI Associate Exam Sample Questions (Q32-Q37):

NEW QUESTION # 32
A financial institution plans a campaign for preapproved credit cards?
How should they implement Salesforce's Trusted AI Principle of Transparency?

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

Answer: A

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 # 33
How does a data quality assessment impact business outcome for companies using AI?

A. Improves the speed of AI recommendations
B. Accelerates the delivery of new AI solutions
C. Provides a benchmark for AI predictions

Answer: C

Explanation:
Explanation
"A data quality assessment impacts business outcomes for companies using AI by providing a benchmark for AI predictions. A data quality assessment is a process that measures and evaluates the quality of data for a specific purpose or task. A data quality assessment can help identify and address any issues or gaps in the data quality dimensions, such as accuracy, completeness, consistency, relevance, and timeliness. A data quality assessment can impact business outcomes for companies using AI by providing a benchmark for AI predictions, as it can help ensure that the predictions are based on high-quality data that reflects the true state or condition of the target population or domain."

NEW QUESTION # 34
Cloud Kicks wants to ensure that multiple records for the same customer are removed in Salesforce.
Which feature should be used to accomplish this?

A. Trigger deletion of old records
B. Standardized field names
C. Duplicate management

Answer: C

Explanation:
"Duplicate management should be used to remove multiple records for the same customer in Salesforce.
Duplicate managementis a feature that helps prevent and manage duplicate records in Salesforce. Duplicate management can help define matching rules, duplicate rules, and alert messages to detect and merge duplicate records."

NEW QUESTION # 35
What is a possible outcome of poor data quality?

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

Answer: A

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 # 36
A service leader wants use AI to help customer resolve their issues quicker in a guided self-serve application.
Which Einstein functionality provides the best solution?

A. Bots
B. Case Classification
C. Recommendation

Answer: A

Explanation:
Explanation
"Bots provide the best solution for a service leader who wants to use AI to help customers resolve their issues quicker in a guided self-serve application. Bots are a feature that uses natural language processing (NLP) and natural language understanding (NLU) to create conversational interfaces that can interact with customers using text or voice. Bots can help automate and streamline customer service processes by providing answers, suggestions, or actions based on the customer's intent and context."

NEW QUESTION # 37
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