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Salesforce Certified AI Associate Practice Test - Questions Answers, Page 2

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What are some of the ethical challenges associated with AI development?

A.
Potential for human bias in machine learning algorithms and the lack of transparency in AI decision-making processes
A.
Potential for human bias in machine learning algorithms and the lack of transparency in AI decision-making processes
Answers
B.
Implicit transparency of AI systems, which makes It easy for users to understand and trust their decisions
B.
Implicit transparency of AI systems, which makes It easy for users to understand and trust their decisions
Answers
C.
Inherent neutrality of AI systems, which eliminates any potential for human bias in decision-making
C.
Inherent neutrality of AI systems, which eliminates any potential for human bias in decision-making
Answers
Suggested answer: A

Explanation:

''Some of the ethical challenges associated with AI development are the potential for human bias in machine learning algorithms and the lack of transparency in AI decision-making processes. Human bias can arise from the data used to train the models, the design choices made by the developers, or the interpretation of the results by the users. Lack of transparency can make it difficult to understand how and why AI systems make certain decisions, which can affect trust, accountability, and fairness.''

Cloud Kicks discovered multiple variations of state and country values in contact records.

Which data quality dimension is affected by this issue?

A.
Usage
A.
Usage
Answers
B.
Accuracy
B.
Accuracy
Answers
C.
Consistency
C.
Consistency
Answers
Suggested answer: C

Explanation:

''Consistency is the data quality dimension that is affected by multiple variations of state and country values in contact records. 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 and processing.''

How is natural language processing (NLP) used in the context of AI capabilities?

A.
To cleanse and prepare data for AI implementations
A.
To cleanse and prepare data for AI implementations
Answers
B.
To interpret and understand programming language
B.
To interpret and understand programming language
Answers
C.
To understand and generate human language
C.
To understand and generate human language
Answers
Suggested answer: C

Explanation:

''Natural language processing (NLP) is used in the context of AI capabilities to understand and generate human language. NLP can enable AI systems to interact with humans using natural language, such as speech or text. NLP can also enable AI systems to analyze and extract information from natural language data, such as documents, emails, or social media posts.''

What is an example of Salesforce's Trusted AI Principle of Inclusivity in practice?

A.
Testing models with diverse datasets
A.
Testing models with diverse datasets
Answers
B.
Striving for model explain ability
B.
Striving for model explain ability
Answers
C.
Working with human rights experts
C.
Working with human rights experts
Answers
Suggested answer: A

Explanation:

''An example of Salesforce's Trusted AI Principle of Inclusivity in practice is testing models with diverse datasets. Inclusivity means that AI systems should be designed and developed with respect for diversity and inclusion of different perspectives, backgrounds, and experiences. Testing models with diverse datasets can help ensure that the models are fair, unbiased, and representative of the target population or domain.''

Cloud Kicks wants to create a custom service analytics application to analyze cases in Salesforce. The application should rely on accurate data to ensure efficient case resolution.

Which data quality dimension Is essential for this custom application?

A.
Consistency
A.
Consistency
Answers
B.
Duplication
B.
Duplication
Answers
C.
Age
C.
Age
Answers
Suggested answer: A

Explanation:

''Consistency is the data quality dimension that is essential for creating a custom service analytics application to analyze cases in Salesforce. Consistency means that the data values are uniform and follow a common standard or format across different records, fields, or sources. Consistent data can ensure that the custom application can accurately and efficiently analyze cases and provide meaningful insights.''

What should organizations do to ensure data quality for their AI initiatives?

A.
Collect and curate high-quality data from reliable sources.
A.
Collect and curate high-quality data from reliable sources.
Answers
B.
Rely on AI algorithms to automatically handle data quality issues.
B.
Rely on AI algorithms to automatically handle data quality issues.
Answers
C.
Prioritize model fine-tuning over data quality improvements.
C.
Prioritize model fine-tuning over data quality improvements.
Answers
Suggested answer: A

Explanation:

''Organizations should collect and curate high-quality data from reliable sources to ensure data quality for their AI initiatives. High-quality data means that the data is accurate, complete, consistent, relevant, and timely for the AI task. Reliable sources mean that the data is trustworthy, credible, and authoritative. Collecting and curating high-quality data from reliable sources can improve the performance and reliability of AI systems.''

Which Einstein capability uses emails to create content for Knowledge articles?

A.
Generate
A.
Generate
Answers
B.
Discover
B.
Discover
Answers
C.
Predict
C.
Predict
Answers
Suggested answer: A

Explanation:

''Einstein Generate uses emails to create content for Knowledge articles. Einstein Generate is a natural language generation (NLG) feature that can automatically write summaries, descriptions, or recommendations based on data or text inputs. For example, Einstein Generate can analyze email conversations between agents and customers and generate draft articles for the Knowledge base.''

Which type of bias results from data being labeled according to stereotypes?

A.
Association
A.
Association
Answers
B.
Societal
B.
Societal
Answers
C.
Interaction
C.
Interaction
Answers
Suggested answer: B

Explanation:

''Societal bias results from data being labeled according to stereotypes. Societal bias is a type of bias that reflects the assumptions, norms, or values of a specific society or culture. For example, societal bias can occur when data is labeled based on gender, race, ethnicity, or religion stereotypes.''

Salesforce defines bias as using a person's Immutable traits to classify them or market to them.

Which potentially sensitive attribute is an example of an immutable trait?

A.
Financial status
A.
Financial status
Answers
B.
Nickname
B.
Nickname
Answers
C.
Email address
C.
Email address
Answers
Suggested answer: A

Explanation:

''Financial status is an example of an immutable trait. Immutable traits are characteristics that are inherent, fixed, or unchangeable. For example, financial status is an immutable trait because it is determined by factors beyond one's control, such as birth, inheritance, or economic conditions. Nickname and email address are not immutable traits because they can be changed by choice or preference.''

Cloud Kicks relies on data analysis to optimize its product recommendation; however, CK encounters a recurring Issue of Incomplete customer records, with missing contact Information and incomplete purchase histories.

How will this incomplete data quality impact the company's operations?

A.
The accuracy of product recommendations is hindered.
A.
The accuracy of product recommendations is hindered.
Answers
B.
The diversity of product recommendations Is Improved.
B.
The diversity of product recommendations Is Improved.
Answers
C.
The response time for product recommendations is stalled.
C.
The response time for product recommendations is stalled.
Answers
Suggested answer: A

Explanation:

''The incomplete data quality will impact the company's operations by hindering the accuracy of product recommendations. Incomplete data means that the data is missing some values or attributes that are relevant for the AI task. Incomplete data can affect the performance and reliability of AI models, as they may not have enough information to learn from or make accurate predictions. For example, incomplete customer records can affect the quality of product recommendations, as the AI model may not be able to capture the customers' preferences, behavior, or needs.''

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