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Salesforce-AI-Associate Practice Test


Page 5 out of 22 Pages

A financial institution plans a campaign for preapproved credit cards? How should they implement Salesforce’s Trusted AI Principle of Transparency?


A. Communicate how risk factors such as credit score can impact customer eligibility.


B. Flag sensitive variables and their proxies to prevent discriminatory lending practices.


C. Incorporate customer feedback into the model’s continuous training.





B.
  Flag sensitive variables and their proxies to prevent discriminatory lending practices.


Explanation:
“Flagging sensitive variables and their proxies to prevent discriminatory lending practices is 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 variables that 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.”

What is an implication of user consent in regard to AI data privacy?


A. AI ensures complete data privacy by automatically obtaining user consent.


B. AI infringes on privacy when user consent is not obtained.


C. AI operates Independently of user privacy and consent.





B.
  AI infringes on privacy when user consent is not obtained.


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 by others. 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.”

What are predictive analytics, machine learning, natural language processing (NLP), and computer vision?


A. Different types of data models used in Salesforce


B. Different types of automation tools used in Salesforce


C. Different types of AI that can be applied in Salesforce





C.
  Different types of AI that can be applied in Salesforce


Explanation:
Predictive analytics, machine learning, natural language processing (NLP), and computer vision are all types of artificial intelligence technologies that can be applied in Salesforce to enhance various aspects of business operations and customer interactions. Predictive analytics uses historical data to make predictions about future events. Machine learning involves algorithms that can learn from and make decisions based on data. NLP is concerned with the interactions between computers and humans using natural language, and computer vision interprets and processes visual information from the world to make sense of it in the way humans do. Salesforce harnesses these AI technologies, particularly through its Einstein platform, to provide powerful tools that help businesses automate tasks, make better decisions, and offer more personalized services. For more on how Salesforce utilizes these AI technologies, you can explore the Einstein AI services documentation at Salesforce Einstein.

What is an example of ethical debt?


A. Violating a data privacy law and failing to pay fines


B. Delaying an AI product launch to retrain an AI data model


C. Launching an AI feature after discovering a harmful bias





C.
  Launching an AI feature after discovering a harmful bias

Which features of Einstein enhance sales efficiency and effectiveness?


A. Opportunity Scoring, Lead Scoring, Account Insights


B. Opportunity List View, Lead List View, Account List view


C. Opportunity Scoring, Opportunity List View, Opportunity Dashboard





A.
  Opportunity Scoring, Lead Scoring, Account Insights


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