[2024年12月10日] Salesforce-AI-Associate PDFで最近更新された問題です集試験点数を伸ばそう
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Salesforce Salesforce-AI-Associate 認定試験の出題範囲：
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質問 # 44
Which Einstein capability uses emails to create content for Knowledge articles?
- A. Generate
- B. Discover
- C. Predict
正解：A
解説：
"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."
質問 # 45
A consultant conducts a series of Consequence Scanning workshops to support testing diverse datasets.
Which Salesforce Trusted AI Principles is being practiced>
- A. Transparency
- B. Inclusivity
- C. Accountability
正解：B
解説：
Explanation
"Conducting a series of Consequence Scanning workshops to support testing diverse datasets is an action that practices Salesforce's Trusted AI Principle of Inclusivity. Inclusivity is one of the Trusted AI Principles that states that AI systems should be designed and developed with respect for diversity and inclusion of different perspectives, backgrounds, and experiences. Conducting Consequence Scanning workshops means engaging with various stakeholders to identify and assess the potential impacts and implications of AI systems on different groups or domains. Conducting Consequence Scanning workshops can help practice Inclusivity by ensuring that diverse datasets are used to test and evaluate AI systems."
質問 # 46
Cloud Kicks wants to evaluate its data quality to ensure accurate and up-to-date records.
Which type of records negatively impact data quality?
- A. Complete
- B. Structured
- C. Duplicate
正解：C
解説：
Duplicate records negatively impact data quality by creating inconsistencies and confusion in database management, leading to potential errors in customer relationship management (CRM) systems like Salesforce. Duplicates can skew analytics results, lead to inefficiencies in customer service, and result in redundant marketing efforts. Salesforce offers various tools to identify and merge duplicate records, thereby maintaining high data integrity. More about managing duplicate records in Salesforce and ensuring data quality can be found in Salesforce's documentation on duplicate management at Salesforce Duplicate Management.
質問 # 47
Cloud Kicks wants to evaluate the quality of its sales data.
Which first step should they take for the data quality assessment?
- A. Run a new report or dashboard.
- B. Plan and align territories,
- C. Identify business objectives.
正解：C
解説：
The first step Cloud Kicks should take for data quality assessment is to identify business objectives. This is crucial because understanding how the company uses customer data to support its business objectives will guide the assessment process1. By identifying the business objectives, Cloud Kicks can determine what customer data is required to support those objectives and how that data is being used. This foundational step is essential before moving on to other aspects of data quality assessment, such as running reports or planning territories. It aligns the data quality initiatives with the company's goals and ensures that the assessment is focused on areas that will drive business value
質問 # 48
What is a possible outcome of poor data quality?
- A. Biases in data can be inadvertently learned and amplified by AI systems.
- B. AI models maintain accuracy but have slower response times.
- C. AI predictions become more focused and less robust.
正解：A
解説：
"A possible outcome of poor data quality is that biases in data can be inadvertently learned and amplified by AI systems. Poor data quality means that the data is inaccurate, incomplete, inconsistent, irrelevant, or outdated for the AI task. Poor data quality can affect the performance and reliability of AI systems, as they may not have enough or correct information to learn from or make accurate predictions. Poor data quality can also introduce or exacerbate biases in data, such as human bias, societal bias, or confirmation bias, which can affect the fairness and ethics of AI systems."
質問 # 49
Which statement exemplifies Salesforces honesty guideline when training AI models?
- A. Ensure appropriate consent and transparency when using AI-generated responses.
- B. Minimize the AI models carbon footprint and environment impact during training.
- C. Control bias, toxicity, and harmful content withembedded guardrails and guidance.
正解：A
解説：
"Ensuring appropriate consent and transparency when using AI-generated responses is a statement that exemplifies Salesforce's honesty guideline when training AI models. Salesforce's honesty guideline is one of the Trusted AI Principles that states that AI systems should be designed and developed with respect for honesty and integrity in how they work and what they produce. Ensuring appropriate consent and transparency means respecting and honoring the choices andpreferences of users regarding how their data is used or generated by AI systems. Ensuring appropriate consent and transparency also means providing clear and accurate information and documentation about the AI systems and their outputs."
質問 # 50
Which best describes the different between predictive AI and generative AI?
- A. Predictive AI and generative have the same capabilities differ in the type of input they receive:
predictive AI receives raw data whereas generation AI receives natural language. - B. Predictive AI uses machine learning to classes or predict output from its input data whereas generative AI does not use machine learning to generate its output
- C. Predictive new and original output for a given input.
正解：C
解説：
"The difference between predictive AI and generative AI is that predictive AI analyzes existing data to make predictions or recommendations based on patterns or trends, while generative AI creates new content based on existing data or inputs. Predictive AI is a type of AI that uses machine learning techniques to learn from existing data and make predictions or recommendations based on the data. For example, predictive AI can be used to forecast sales, revenue, or demand based on historical data and trends. Generative AI is a type of AI that uses machine learning techniques to generate novel content such as images, text, music, or video based on existing data or inputs. For example, generative AI can be used to create realistic faces, write summaries, compose songs, or produce videos."
質問 # 51
What should organizations do to ensure data quality for their AI initiatives?
- A. Prioritize model fine-tuning over data quality improvements.
- B. Rely on AI algorithms to automatically handle data quality issues.
- C. Collect and curate high-quality data from reliable sources.
正解：C
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 # 52
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. Number
- B. Picklist
- C. Text
正解：B
解説：
"A picklist field type should be used to ensure data quality for capturing an order's destinationcountry. 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 # 53
What Is a benefit of data quality and transparency as it pertains to bias in generated AI?
- A. Chances of bias are remove
- B. Chances of bIas and mitigated
- C. Chances of bias are aggravated
正解：B
解説：
A benefit of data quality and transparency as it pertains to bias in generated AI is that the chances of bias are mitigated. High data quality ensures that AI models are trained on accurate and representative data, reducing the risk of biased outcomes. Transparency in AI processes helps stakeholders understand how decisions are made, allowing for the identification and correction of potential biases. Together, these practices contribute to the development of fairer and more accountable AI systems. Salesforce highlights the importance of these principles in its AI practices, particularly through its ethical AI framework, which advocates for fairness and accountability. More on Salesforce's commitment to promoting unbiased AI can be found in their AI ethics guidelines at Salesforce AI Ethics.
質問 # 54
Cloud Kicks wants to implement AI features on its 5aiesforce Platform but has concerns about potential ethical and privacy challenges.
What should they consider doing to minimize potential AI bias?
- A. Use demographic data to identify minority groups.
- B. Implement Salesforce's Trusted AI Principles.
- C. Integrate AI models that auto-correct biased data.
正解：B
解説：
"Implementing Salesforce's Trusted AI Principles is what Cloud Kicks should consider doing to minimize potential AI bias. Salesforce's Trusted AI Principles are a set of guidelines and best practices for 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."
質問 # 55
What is Salesforce's Trusted AI Principle of Transparency?
- A. The integration of AT models with Salesforce workflows
- B. The clear and understandable explanation of Al decisions and actions
- C. The customization of AT features to meet specific business requirements
正解：B
解説：
Salesforce's Trusted AI Principle of Transparency emphasizes the importance of providing clear and understandable explanations of AI decisions and actions. This principle ensures that users can understand how AI conclusions are drawn, which is crucial for trust and accountability, especially in business applications where AI decisions can have significant impacts. Transparency helps mitigate the "black box" nature of AI systems by making them more interpretable and allows for better oversight, compliance, and alignment with ethical guidelines. Salesforce elaborates on these principles in their ethical AI practices, which can be further explored at Salesforce Ethical AI.
質問 # 56
Which action should be taken to develop and implement trusted generated AI with Salesforce's safety guideline in mind?
- A. Create guardrails that mitigates toxicity and protect PII
- B. Be transparent when AI has created and automatically delivered content.
- C. Develop right-sized models to reduce our carbon footprint.
正解：A
解説：
"Creating guardrails that mitigate toxicity and protect PII is an action that should be taken to develop and implement trusted generativeAI with Salesforce's safety guideline in mind. Salesforce's safety guideline is one of the Trusted AI Principles that states that AI systems should be designed and developed with respect for the safety and well-being of humans and the environment. Creatingguardrails means implementing measures or mechanisms that can prevent or limit the potential harm or risk caused by AI systems. For example, creating guardrails can help mitigate toxicity by filtering out inappropriate or offensive content generated by AIsystems. Creating guardrails can also help protect PII by masking or anonymizing personal or sensitive information generated by AI systems."
質問 # 57
Why is it critical to consider privacy concernswhen dealing with AI and CRM data?
- A. Increases the volume of data collected
- B. Ensures compliance with laws and regulations
- C. Confirms the data is accessible to all users
正解：B
解説：
"It is critical to consider privacy concerns when dealing with AI and CRM data because it ensures compliance with laws and regulations. Data privacy is the right of individuals to control how their personal data is collected, used, shared, or stored by others. Data privacy laws and regulations are legal frameworks that defineand enforce the rights and obligations of data subjects, data controllers, and data processors regarding personal data. Data privacy laws and regulations vary by country, region, or industry, and may impose different requirements or restrictions on how AIand CRM data can be handled."
質問 # 58
What is a potential outcome of using poor-quality data in AI application?
- A. AI models may produce biased or erroneous results.
- B. AI models become more interpretable
- C. AI model training becomes slower and less efficient
正解：A
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 # 59
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