Salesforce-AI-Associate Practice Questions

A.  

Duplication

B.  

Usage

C.  

Completeness

A.  

Predictive scoring, reporting, Image classification

B.  

Predictive scoring, forecasting, recommendations

C.  

Einstein Bots, face recognition, recommendations

A.  

Dashboard of Current Leads and Cases

B.  

Sales path and Automaton Case Escalations

C.  

Einstein Lead Scoring and Case Classification

A.  

Using a large dataset that is computationally expensive

B.  

Using a dataset that represents diverse perspectives and populations

C.  

Using a dataset that underrepresents perspectives and populations

A.  

Text

B.  

Picklist

C.  

Number

A.  

Plan and align territories,

B.  

Run a new report or dashboard.

C.  

Identify business objectives.

A.  

The use of both low-quality and high-quality data can improve the accuracy and reliability of AI-driven decisions.

B.  

High-quality data improves the reliability and credibility of Al-driven decisions, fostering trust among users.

C.  

Low-quality data reduces the risk of overfitting the model, improving the trustworthiness of the predictions.

A.  

Potential for human bias in machine learning algorithms and the lack of transparency in AI decision-making processes

B.  

Implicit transparency of AI systems, which makes It easy for users to understand and trust their decisions

C.  

Inherent neutrality of AI systems, which eliminates any potential for human bias in decision-making

A.  

Faster and cheaper development

B.  

More innovation and creativity

C.  

Harm to marginalized communities

A.  

The data is collected in area time from sources systems.

B.  

The data is skewed toward is particular demographic or source.

C.  

The data is collected from a diverse range of sources and demographics.