リアルSalesforce-AI-Associate問題集でSalesforce正確な解答2025年最新版を試そう
AI Associate Salesforce-AI-Associate試験練習問題集
Salesforce Salesforce-AI-Associate 認定試験の出題範囲：
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質問 # 52
What is a potential outcome of using poor-quality data in AI application?
- A. AI models become more interpretable
- B. AI model training becomes slower and less efficient
- C. AI models may produce biased or erroneous results.
正解：C
解説：
Explanation
"A potential outcome of using poor-quality data in AI applications is that AI models may produce biased or erroneous results. Poor-quality data means that the data is inaccurate, incomplete,inconsistent, irrelevant, or outdated for the AI task. Poor-quality data can affect the performance and reliability of AI models, as they may not have enough or correct information to learn from or make accurate predictions. Poor-quality data can also introduce or exacerbate biases or errors in AI models, such as human bias, societal bias, confirmation bias, or overfitting or underfitting."
質問 # 53
What is the role of Salesforce Trust AI principles in the context of CRM system?
- A. Guiding ethical and responsible use of AI
- B. Providing a framework for AI data model accuracy
- C. Outlining the technical specifications for AI integration
正解：A
解説：
"The role of Salesforce Trust AI principles in the context of CRM systems is guiding ethical and responsible use of AI. Salesforce Trust AI principles are a set of guidelines and best practicesfor developing and using AI systems in a responsible and ethical way. The principles include Accountability, Fairness & Equality, Transparency & Explainability, Privacy & Security, Reliability & Safety, Inclusivity & Diversity, Empowerment & Education. The principles aim to ensure that AI systems are aligned with the values and interests of customers, partners, and society."
質問 # 54
Cloud Kicks is testing a new AI model.
Which approach aligns with Salesforce's Trusted AI Principle of Incluslvity?
- A. Test with diverse and representative datasets appropriate for how the model will be used.
- B. Test only with data from a specific region or demographic to limit the risk of data leaks.
- C. Rely on a development team with uniform backgrounds to assess the potential societal implications of the model.
正解：A
解説：
Explanation
"Testing with diverse and representative datasets appropriate for how the model will be used aligns with Salesforce's Trusted AI Principle of Inclusivity. Inclusivity means that AI systems should be designed and developed with respect for diversity and inclusion of different perspectives, backgrounds, and experiences.
Testing with diverse and representative datasets can help ensure that the models are fair, unbiased, and representative of the target population or domain."
質問 # 55
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.
正解：B
解説：
"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 byothers. 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."
質問 # 56
A data quality expert at Cloud Kicks want to ensure that each new contact contains at least an email address ...
Which feature should they use to accomplish this?
- A. Autofill
- B. Validation rule
- C. Duplicate matching rule
正解：B
解説：
Explanation
"A validation rule should be used to ensure that each new contact contains at least an email address or phone number. A validation rule is a feature that checks the data entered by users for errors before saving it to Salesforce. A validation rule can help ensure data quality by enforcing certain criteria or conditions for the data values."
質問 # 57
Which type of bias results from data being labeled according to stereotypes?
- A. Association
- B. Societal
- C. Interaction
正解：B
解説：
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."
質問 # 58
A business analyst (BA) is preparing a new use case for Al. They run a report to check for null values in the attributes they plan to use.
Which data quality component Is the BA verifying by checking for null values?
- A. Duplication
- B. Usage
- C. Completeness
正解：C
解説：
By checking for null values, a business analyst (BA) is verifying the data quality component of completeness.
Completeness refers to the absence of missing values or gaps in the data, which is essential for the accuracy and reliability of reports and analytics used in AI models. Null values can indicate incomplete data, which may adversely affect the performance of AI applications by leading to incorrect predictions or insights.
Salesforce emphasizes the importance of data completeness for effective data analysis and provides tools for data quality assessment and improvement. Details on handling data completeness in Salesforce can be explored at Salesforce Help Data Management.
質問 # 59
A data quality expert at Cloud Kicks want to ensure that each new contact contains at least an email address
...
Which feature should they use to accomplish this?
- A. Autofill
- B. Validation rule
- C. Duplicate matching rule
正解：B
解説：
"A validation rule should be used to ensure that each new contact contains at least an email address or phone number. A validation rule is a feature that checks the data entered by users for errors before saving it to Salesforce. A validation rule can help ensure data quality by enforcing certain criteria or conditions for the data values."
質問 # 60
How does data quality impact the trustworthiness of Al-driven decisions?
- A. The use of both low-quality and high-quality data can improve the accuracy and reliability of AI-driven decisions.
- B. Low-quality data reduces the risk of overfitting the model, improving the trustworthiness of the predictions.
- C. High-quality data improves the reliability and credibility of Al-driven decisions, fostering trust among users.
正解：C
質問 # 61
Which features of Einstein enhance sales efficiency and effectiveness?
- A. Opportunity List View, Lead List View, Account List view
- B. Opportunity Scoring, Lead Scoring, Account Insights
- C. Opportunity Scoring, Opportunity List View, Opportunity Dashboard
正解：B
解説：
"Opportunity Scoring, Lead Scoring, Account Insights are features of Einstein that enhance sales efficiency and effectiveness. Opportunity Scoring and Lead Scoring use predictive models to assign scores to opportunities and leads based on their likelihood to close or convert. Account Insights use natural language processing (NLP) to provide relevant news and insights about accounts based on their industry, location, or events."
質問 # 62
A customer using Einstein Prediction Builder is confused about why a certain prediction was made.
Following Salesforce's Trusted AI Principle of Transparency, which customer information should be accessible on the Salesforce Platform?
- A. An explanation of the prediction's rationale and a model card that describes how the model was created
- B. A marketing article of the product that clearly outlines the oroduct's capabilities and features
- C. An explanation of how Prediction Builder works and a link to Salesforce's Trusted AI Principles
正解：A
解説：
Explanation
"An explanation of the prediction's rationale and a model card that describes how the model was created should be accessible on the Salesforce Platform following Salesforce's Trusted AI Principle of Transparency.
Transparency means 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."
質問 # 63
A Salesforce administrator creates a new field to capture an order's destination country.
Which field type should they use to ensure data quality?
- A. Text
- B. Number
- C. Picklist
正解：C
解説：
Explanation
"A picklist field type should be used to ensure data quality for capturing an order's destination country. A picklist field type allows the user to select one or more predefined values from a list. A picklist field type can ensure data quality by enforcing consistency, accuracy, and completeness of the data values."
質問 # 64
Salesforce defines bias as using aperson's Immutable traits to classify them or market to them.
Which potentially sensitive attribute is an example of an immutable trait?
- A. Nickname
- B. Financial status
- C. Email address
正解：B
解説：
"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 emailaddress are not immutable traits because they can be changed by choice or preference."
質問 # 65
What should an organization do to enforce consistency across accounts for newly entered records?
- A. Input the data exactly as it appears from the source, such as the company's website or social media,
- B. Merge all duplicate accounts into a single record when duplicate entries are detected.
- C. Implement naming conventions or a predefined list of user-selectable values for organization-wide records.
正解：C
解説：
To ensure consistency across accounts for newly entered records, organizations should implement naming conventions or a predefined list of user-selectable values. This approach standardizes data entry, reducing variations and errors. It also helps in maintaining clean data which is essential for accurate reporting and analytics. Using standardized naming conventions ensures that all users adhere to a consistent format, making it easier to manage and analyze data across the organization. For more information on best practices for data management in Salesforce, refer to Salesforce's documentation on Data Management Best Practices.
質問 # 66
What should organizations do to ensure data quality for their AI initiatives?
- A. Rely on AI algorithms to automatically handle data quality issues.
- B. Collect and curate high-quality data from reliable sources.
- C. Prioritize model fine-tuning over data quality improvements.
正解：B
解説：
"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."
質問 # 67
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