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30/03/2024 5:59 am
Free Salesforce Salesforce AI Associate Dumps are shared online. You can view and discuss Salesforce Salesforce AI Associate questions and answers for free below. FreeSalesforce Certified AI Associate Exam (SU23) Exam Questions.
30/03/2024 5:59 am
What is a benefit of a diverse, balanced, and large dataset?
- A . Training time
- B . Data privacy
- C . Model accuracy
Suggested Answer: C
Explanation:
“Model accuracy is a benefit of a diverse, balanced, and large dataset. A diverse dataset can capture a variety of features and patterns that are relevant for the AI task. A balanced dataset can avoid overfitting or underfitting the model to a specific subset of data. A large dataset can provide enough information for the model to learn from and generalize well to new data.”
Explanation:
“Model accuracy is a benefit of a diverse, balanced, and large dataset. A diverse dataset can capture a variety of features and patterns that are relevant for the AI task. A balanced dataset can avoid overfitting or underfitting the model to a specific subset of data. A large dataset can provide enough information for the model to learn from and generalize well to new data.”
30/03/2024 5:59 am
What are the three commonly used examples of AI in CRM?
- A . Predictive scoring, reporting, Image classification
- B . Predictive scoring, forecasting, recommendations
- C . Einstein Bots, face recognition, recommendations
Suggested Answer: B
Explanation:
“Predictive scoring, forecasting, and recommendations are three commonly used examples of AI in CRM. Predictive scoring can help prioritize leads, opportunities, and customers based on their likelihood to convert, churn, or buy. Forecasting can help predict future sales, revenue, or demand based on historical data and trends. Recommendations can help suggest the best products, services, or actions for each customer based on their preferences, behavior, and needs.”
Explanation:
“Predictive scoring, forecasting, and recommendations are three commonly used examples of AI in CRM. Predictive scoring can help prioritize leads, opportunities, and customers based on their likelihood to convert, churn, or buy. Forecasting can help predict future sales, revenue, or demand based on historical data and trends. Recommendations can help suggest the best products, services, or actions for each customer based on their preferences, behavior, and needs.”
30/03/2024 5:59 am
Cloud Kicks wants to optimize its business operations by incorporating AI into its CRM.
What should the company do first to prepare its data for use with AI?
- A . Remove biased data.
- B . Determine data availability.
- C . Determine data outcomes.
Suggested Answer: B
Explanation:
Before using AI to optimize business operations, the company should first assess the availability and quality of its data. Data is the fuel for AI, and without sufficient and relevant data, AI cannot produce accurate and reliable results. Therefore, the company should identify what data it has, where it is stored, how it is accessed, and how it is maintained. This will help the company understand the feasibility and scope of its AI projects.
Explanation:
Before using AI to optimize business operations, the company should first assess the availability and quality of its data. Data is the fuel for AI, and without sufficient and relevant data, AI cannot produce accurate and reliable results. Therefore, the company should identify what data it has, where it is stored, how it is accessed, and how it is maintained. This will help the company understand the feasibility and scope of its AI projects.
30/03/2024 5:59 am
A healthcare company implements an algorithm to analyze patient data and assist in medical diagnosis.
Which primary role does data Quality play In this AI application?
- A . Enhanced accuracy and reliability of medical predictions and diagnoses
- B . Ensured compatibility of AI algorithms with the system's Infrastructure
- C . Reduced need for healthcare expertise in interpreting AI outouts
Suggested Answer: A
Explanation:
“Data quality plays a crucial role in enhancing the accuracy and reliability of medical predictions and diagnoses. Poor data quality can lead to inaccurate or misleading results, which can have serious consequences for patients’ health and well-being. Therefore, it is important to ensure that the data used for AI applications in healthcare is accurate, complete, consistent, and relevant.”
Explanation:
“Data quality plays a crucial role in enhancing the accuracy and reliability of medical predictions and diagnoses. Poor data quality can lead to inaccurate or misleading results, which can have serious consequences for patients’ health and well-being. Therefore, it is important to ensure that the data used for AI applications in healthcare is accurate, complete, consistent, and relevant.”
30/03/2024 5:59 am
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
- 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
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.”
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.”
30/03/2024 5:59 am
Cloud Kicks discovered multiple variations of state and country values in contact records.
Which data quality dimension is affected by this issue?
- A . Usage
- B . Accuracy
- C . Consistency
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.”
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.”
30/03/2024 5:59 am
How is natural language processing (NLP) used in the context of AI capabilities?
- A . To cleanse and prepare data for AI implementations
- B . To interpret and understand programming language
- C . To understand and generate human language
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.”
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.”
30/03/2024 5:59 am
What is an example of Salesforce's Trusted AI Principle of Inclusivity in practice?
- A . Testing models with diverse datasets
- B . Striving for model explain ability
- C . Working with human rights experts
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.”
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.”
30/03/2024 5:59 am
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
- B . Duplication
- C . Age
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.”
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.”
30/03/2024 5:59 am
What should organizations do to ensure data quality for their AI initiatives?
- A . Collect and curate high-quality data from reliable sources.
- B . Rely on AI algorithms to automatically handle data quality issues.
- C . Prioritize model fine-tuning over data quality improvements.
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.”
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.”
30/03/2024 5:59 am
Which Einstein capability uses emails to create content for Knowledge articles?
- A . Generate
- B . Discover
- C . Predict
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.”
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.”
30/03/2024 5:59 am
Which type of bias results from data being labeled according to stereotypes?
- A . Association
- B . Societal
- C . Interaction
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.”
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.”
30/03/2024 5:59 am
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
- B . Nickname
- C . Email address
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.”
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.”
30/03/2024 5:59 am
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.
- B . The diversity of product recommendations Is Improved.
- C . The response time for product recommendations is stalled.
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.”
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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