Salesforce-AI-Associate PDF試験材料2024年最新の実際に出るSalesforce-AI-Associate問題集
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質問 # 57
Which data does Salesforce automatically exclude from marketing Cloud Einstein engagement model training to mitigate bias and ethic...
- A. Cryptographic
- B. Geographic
- C. Geographic
正解：B
解説：
"Demographic data is thedata that Salesforce automatically excludes from Marketing Cloud Einstein engagement model training to mitigate bias and ethical concerns. Demographic data is data that describes the characteristics of a population or a group of people, such as age, gender, race, ethnicity, income, education, or occupation. Demographic data can lead to bias if it is used to discriminate or treat people differently based on their identity or attributes. Demographic data can also reflect existing biases or stereotypes in society or culture, which can affect the fairness and ethics of AI systems. Salesforce excludes demographic data from Marketing Cloud Einstein engagement model training to mitigate bias and ethical concerns by ensuring that the models are based on behavioral data rather than personal data."
質問 # 58
Cloud Kicks wants to develop a solutionto predict customers product interests based on historical data. The company found that employees from one region use a text field to capture the product category, while employees from all other locations use a plckllst.
Which data quality dimension is affected in this scenario?
- A. Completeness
- B. Accuracy
- C. Consistency
正解：C
解説：
"Consistency is the data quality dimension that is affected in this scenario. Consistency means that the data values are uniform and follow a common standard or format acrossdifferent records, fields, or sources.
Inconsistent data can cause confusion, errors, or duplication in data analysis and processing. For example, using different field types for the same attribute can affect the consistency of the data."
質問 # 59
How does an organization benefit from using AI to personalize the shopping experience of online customers?
- A. Customers are more likely to visit competitor sites that personalize their experience.
- B. Customers are more likely to be satisfied with their shopping experience.
- C. Customers are morelikely to share personal information with a site that personalizes their experience.
正解：B
解説：
"An organization benefits from using AI to personalize the shopping experience of online customers by increasing customer satisfaction. AI can help provide customized and relevant product recommendations, offers, or content based on the customers' preferences, behavior, or needs. AI can also help create a more engaging and interactive shopping experience by using natural language processing (NLP) or computer vision techniques. Personalized shopping experiences can improve customer satisfaction by meeting their expectations, needs, and interests."
質問 # 60
What are the three commonly used examples of AI in CRM?
- A. Predictive scoring, forecasting, recommendations
- B. Predictive scoring, reporting, Image classification
- C. Einstein Bots, face recognition, recommendations
正解：A
解説：
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."
質問 # 61
What are predictive analytics, machine learning, natural language processing (NLP), and computer vision?
- A. Different types of automation tools used in Salesforce
- B. Different types of AI that can be applied in Salesforce
- C. Different types of data models used in Salesforce
正解：B
解説：
Predictive analytics, machine learning, natural language processing (NLP), and computer vision are all types of artificial intelligence technologies that can be applied in Salesforce to enhance various aspects of business operations and customer interactions. Predictive analytics uses historical data to make predictions about future events. Machine learning involves algorithms that can learn from and make decisions based on data. NLP is concerned with the interactions between computers and humans using natural language, and computer vision interprets and processes visual information from the world to make sense of it in the way humans do.
Salesforce harnesses these AI technologies, particularly through its Einstein platform, to provide powerful tools that help businesses automate tasks, make better decisions, and offer more personalized services. For more on how Salesforce utilizes these AI technologies, you can explore the Einstein AI services documentation at Salesforce Einstein.
質問 # 62
What are some of the ethical challenges associated with AI development?
- A. Implicit transparency of AI systems, which makes It easy for users to understand and trust their decisions
- B. Inherent neutrality of AI systems, which eliminates any potential for human bias in decision-making
- C. Potential for human bias in machine learning algorithms and the lack of transparency in AI decision-making processes
正解：C
解説：
"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 themodels, 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."
質問 # 63
Which best describes the different between predictive AI and generative AI?
- A. Predictive new and original output for a given input.
- B. Predictive AI and generative have the same capabilities differ in the type of input theyreceive: predictive AI receives raw data whereas generation AI receives natural language.
- C. 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
正解：A
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 # 64
Cloud Kicks learns of complaints from customers who are receiving too many sales calls and emails.
Which data quality dimension should be assessed to reduce these communication Inefficiencies?
- A. Duplication
- B. Usage
- C. Consent
正解：A
解説：
"Duplication is the data quality dimension that should be assessed to reduce communication inefficiencies.
Duplication means that the data contains multiple copies or instances of the same record or value.
Duplication can cause confusion, errors, or waste in data analysis and processing. For example, duplication can lead to communication inefficiencies if customers receive multiple calls or emails from different sources for the same purpose."
質問 # 65
In the context of Salesforce's Trusted AI Principles what does the principle of Empowerment primarily aim to achieve?
- A. Empower users to contribute to the growing body of knowledge of leading AI research.
- B. Empower users to off all skill level to build AI application with clicks, not code.
- C. Empower users to solve challenging technical problems using neural networks.
正解：B
解説：
"The principle of Empowerment primarily aims to achieve empowering users of all skill levels to build AI applications with clicks, not code. Empowerment is one of the Trusted AI Principles that states that AI systems should be designed and developed with respect for the empowerment and education of humans.
Empowering users means enabling users to access, use, and benefit from AI systems regardless of their technical expertise or background. For example, empowering users means providing tools and platforms that allow users to build AI applications with clicks, not code, such as Einstein Prediction Builder or Einstein Discovery."
質問 # 66
Cloud Kicks wants to improve the quality of its AI model's predictions with the use of a large amount of data.
Which data quality element should the company focus on?
- A. Volume
- B. Location
- C. Accuracy
正解：C
解説：
To improve the quality of AI model predictions, Cloud Kicks should focus on the accuracy of the data.
Accurate data ensures that the insights and predictions generated by AI models are reliable and valid. Data accuracy involves correcting errors, filling missing values, and verifying data sources to enhance the quality of information fed into the AI systems. Focusing on data accuracy helps in minimizing prediction errors and enhances the decision-making process based on AI insights. For more details on the importance of data quality in AI models, Salesforce provides extensive guidance in their documentation, which can be found at Data Quality and AI.
質問 # 67
What is the significance of explainability of trusted AI systems?
- A. Describes how Al models make decisions
- B. Enhances the security and accuracy of AI models
- C. Increases the complexity of AI models
正解：A
解説：
The significance of the explainability of trusted AI systems is that it describes how AI models make decisions.
Explainability is crucial for building trust and accountability in AI systems, ensuring that users and stakeholders understand the decision-making processes and outcomes generated by AI. This is particularly important in scenarios where AI decisions impact personal or financial status, such as in credit scoring or healthcare diagnostics. Salesforce emphasizes the importance of explainable AI through its ethical AI practices, aiming to make AI systems more transparent and understandable. More details about Salesforce's approach to ethical and explainable AI can be found in Salesforce AI ethics resources at Salesforce AI Ethics.
質問 # 68
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. Ensured compatibility of AI algorithms with the system's Infrastructure
- B. Reduced need for healthcare expertise in interpreting AI outouts
- C. Enhanced accuracy and reliability of medical predictions and diagnoses
正解：C
解説：
"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 dataused for AI applications in healthcare is accurate, complete, consistent, and relevant."
質問 # 69
Cloud Kicks is testing a new AI model.
Which approach aligns with Salesforce's Trusted AI Principle of Incluslvity?
- A. Rely on a development team with uniform backgrounds to assess the potential societal implications of the model.
- B. Test with diverse and representative datasets appropriate for how the model will be used.
- C. Test only with data from a specific region or demographic to limit the risk of data leaks.
正解：B
解説：
"Testing with diverseand 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 # 70
What are the three commonly used examples of AI in CRM?
- A. Predictive scoring, forecasting, recommendations
- B. Predictive scoring, reporting, Image classification
- C. Einstein Bots, face recognition, recommendations
正解：A
解説：
"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."
質問 # 71
What role does data quality play in the ethical us of AI applications?
- A. High-quality data is essential for ensuringunbased and for fair AI decisions, promoting ethical use, and preventing discrimi...
- B. High-quality data ensures the process of demographic attributes requires for personalized campaigns.
- C. Low-quality data reduces the risk of unintended bias as the datais not overfitted to demographic groups.
正解：A
解説：
"High-quality data is essential for ensuring unbiased and fair AI decisions, promoting ethical use, and preventing discrimination. High-quality data means that the data is accurate, complete, consistent, relevant, and timely for the AI task. High-quality data can help ensure unbiased and fair AI decisions by providing a balanced and representative sample of the target population or domain. High-quality data can also help promote ethical use and prevent discrimination by respecting the rights and preferences of users regarding their personal data."
質問 # 72
What should be done to prevent bias from entering an AI system when training it?
- A. Include Proxy variables.
- B. Import diverse training data.
- C. Use alternative assumptions.
正解：B
解説：
Explanation
"Using diverse training data is what should be done to prevent bias from entering an AI system when training it. Diverse training data means that the data covers a wide range of features andpatterns that are relevant for the AI task. Diverse training data can help prevent bias by ensuring that the AI system learns from a balanced and representative sample of the target population or domain. Diverse training data can also help improve the accuracy and generalization of the AI system by capturing more variations and scenarios in the data."
質問 # 73
What is an implication of user consent in regard to AI data privacy?
- A. AI infringes on privacy when user consent is not obtained.
- B. AI ensures complete data privacy by automatically obtaining user consent.
- C. AI operates Independently of user privacy and consent.
正解：A
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 # 74
Which Einstein capability uses emails to create content for Knowledge articles?
- A. Predict
- B. Generate
- C. Discover
正解：B
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 # 75
What should organizations do to ensure data quality for their AI initiatives?
- A. Collect and curate high-quality data from reliable sources.
- B. Prioritize model fine-tuning over data quality improvements.
- C. Rely on AI algorithms to automatically handle data quality issues.
正解：A
解説：
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."
質問 # 76
What is the main focus of the Accountability principle in Salesforce's Trusted AI Principles?
- A. Safeguarding fundamental human rights and protecting sensitive data
- B. Taking responsibility for one's actions toward customers, partners, and society
- C. Ensuring transparency In Al-driven recommendations and predictions
正解：B
解説：
"The main focus of the Accountability principle in Salesforce's Trusted AI Principles is taking responsibility for one's actions toward customers,partners, and society. Accountability means that AI systems should be designed and developed with respect for the impact and consequences of their actions on others.
Accountability also means that AI developers and users should be aware of and adhere to the ethical, legal, and regulatory standards and expectations of their industry and domain."
質問 # 77
A sales manager wants to use AI to help sales representatives log their calls quicker and more accurately.
Which functionality provides the best solution?
- A. Call Summaries
- B. Sales Dialer
- C. Auto-Generated Sales Tasks
正解：A
解説：
The best functionality to help sales representatives log their calls quicker and more accurately is the use of AI-generated Call Summaries. This feature leverages AI to analyze voice data from sales calls and automatically generate concise summaries and actionable insights, which are then logged into the CRM system. This not only speeds up the process of recording call details but also enhances the accuracy of the data captured, reducing the likelihood of human error and ensuring that important details are not missed.
Salesforce provides AI tools that integrate with telephony solutions to enable these capabilities, enhancing the efficiency of sales operations. For more information on Salesforce AI features like Einstein Call Coaching that support this functionality, visit Salesforce Einstein Call Coaching.
質問 # 78
What is a societal implication of excluding ethics in AI development?
- A. Faster and cheaper development
- B. Harm to marginalized communities
- C. More innovation and creativity
正解：B
解説：
Excluding ethics in AI development can lead to societal implications such as harm to marginalized communities. When ethical considerations are not integrated into AI development, the resulting technologies may perpetuate or amplify biases, leading to unfair treatment or discrimination against certain groups. This can reinforce existing social inequalities and prevent these communities from benefiting equally from the advancements in AI technology. Salesforce is committed to responsible AI development and emphasizes the importance of ethical considerations in their development practices to prevent such outcomes. Details on Salesforce's approach to ethical AI and its importance can be found at Salesforce Ethical AI.
質問 # 79
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