[2024年01月] 無料Salesforce-AI-Associate試験問題集試験点数を伸ばそう
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質問 # 18
What is a key benefit of effective interaction between humans and AI systems?
- A. Alerts humans to the presence of biased data
- B. Leads to more informed and balanced decision making
- C. Reduces the need for human involvement
正解：B
解説：
Explanation
"A key benefit of effective interaction between humans and AI systems is that it leads to more informed and balanced decision making. Effective interaction means that humans and AI systems can communicate and collaborate with each other in a clear, natural, and respectful way. Effective interaction can help leverage the strengths and complement the weaknesses of both humans and AI systems. Effective interaction can also help increase trust, confidence, and satisfaction in using AI systems."
質問 # 19
Which data does Salesforce automatically exclude from marketing Cloud Einstein engagement model training to mitigate bias and ethic...
- A. Geographic
- B. Geographic
- C. Cryptographic
正解：A
解説：
Explanation
"Demographic data is the data 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 # 20
Which features of Einstein enhance sales efficiency and effectiveness?
- A. Opportunity Scoring, Lead Scoring, Account Insights
- B. Opportunity Scoring, Opportunity List View, Opportunity Dashboard
- C. Opportunity List View, Lead List View, Account List view
正解：A
解説：
Explanation
"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 # 21
What is the rile of data quality in achieving AI business Objectives?
- A. Data quality is unnecessary because AI can work with all data types.
- B. Data quality is important for maintain Ai data storage limits
- C. Data quality is required to create accurate AI data insights.
正解：C
解説：
Explanation
"Data quality is required to create accurate AI data insights. Data quality is the degree to which data is accurate, complete, consistent, relevant, and timely for the AI task. Data quality can affect the performance and reliability of AI systems, as they depend on the quality of the data they use to learn from and make predictions. Data quality can also affect the accuracy and validity of AI data insights, as they reflect the quality of the data used or generated by AI systems."
質問 # 22
A developer is tasked with selecting a suitable dataset for training an AI model in Salesforce to accurately predict current customer behavior.
What Is a crucial factor that the developer should consider during selection?
- A. Number of variables ipn the dataset
- B. Size of the dataset
- C. Age of the dataset
正解：B
解説：
Explanation
"The size of the dataset is a crucial factor that the developer should consider during selection. The size of the dataset refers to the amount or volume of data available for training an AI model. The size of the dataset can affect the feasibility and quality of the AI model, as well as the choice of AI techniques and tools. The size of the dataset should be large enough to provide sufficient information for the AI model to learn from and generalize well to new data."
質問 # 23
Which statement exemplifies Salesforces honesty guideline when training AI models?
- A. Minimize the AI models carbon footprint and environment impact during training.
- B. Ensure appropriate consent and transparency when using AI-generated responses.
- C. Control bias, toxicity, and harmful content with embedded guardrails and guidance.
正解：B
解説：
Explanation
"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 and preferences 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 # 24
What is a Key consideration regarding data quality in AI implementation?
- A. Data's role in training and fine-tuning Salesforce AI models
- B. Integration process of AI models with Salesforce workflows
- C. Techniques from customizing AI features in Salesforce
正解：A
解説：
Explanation
"Data's role in training and fine-tuning Salesforce AI models is a key consideration regarding data quality in AI implementation. Data quality is the degree to which data is accurate, complete, consistent, relevant, and timely for the AI task. Data quality can affect the performance and reliability of AI systems, as they depend on the quality of the data they use to learn from and make predictions. Data's role in training and fine-tuning Salesforce AI models means understanding how data is used to build, train, test, and improve AI models in Salesforce, such as Einstein Prediction Builder or Einstein Discovery."
質問 # 25
Which type of bias imposes a system 's values on others?
- A. Association
- B. Societal
- C. Automation
正解：B
解説：
Explanation
"Societal bias is the type of bias that imposes a system's values on others. Societal bias is a type of bias that reflects the assumptions, norms, or values of a specific society or culture. Societal bias can affect the fairness and ethics of AI systems, as they may affect how different groups or domains are perceived, treated, or represented by AI systems. For example, societal bias can occur when AI systems impose a system's values on others, such as using Western standards of beauty or success to judge or rank people from other cultures."
質問 # 26
How does the "right of least privilege" reduce the risk of handling sensitive personal data?
- A. By applying data retention policies
- B. By limiting how many people have access to data
- C. By reducing how many attributes are collected
正解：B
解説：
Explanation
"The "right of least privilege" reduces the risk of handling sensitive personal data by limiting how many people have access to data. The "right of least privilege" is a security principle that states that each user or system should have the minimum level of access or privilege necessary to perform their tasks or functions.
The "right of least privilege" can help protect sensitive personal data from unauthorized access, misuse, or leakage."
質問 # 27
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：
Explanation
"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 by others. 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 # 28
Cloud Kicks wants to use an AI mode to predict the demand for shoes using historical data on sales and regional characteristics.
What is an essential data quality dimension to achieve this goal?
- A. Volume
- B. Age
- C. Reliability
正解：C
解説：
Explanation
"Reliability is an essential data quality dimension to achieve the goal of predicting the demand for shoes using historical data on sales and regional characteristics. Reliability means that the data values are trustworthy, credible, and authoritative for the AI task. Reliable data can improve the accuracy and confidence of AI predictions, as they reflect the true state or condition of the target population or domain. For example, reliable data can help predict the demand for shoes by using verified and validated sales and regional data."
質問 # 29
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 diversity of product recommendations Is Improved.
- B. The accuracy of product recommendations is hindered.
- C. The response time for product recommendations is stalled.
正解：B
解説：
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."
質問 # 30
What is the main focus of the Accountability principle in Salesforce's Trusted AI Principles?
- A. Ensuring transparency In Al-driven recommendations and predictions
- B. Taking responsibility for one's actions toward customers, partners, and society
- C. Safeguarding fundamental human rights and protecting sensitive data
正解：B
解説：
Explanation
"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 # 31
What is the most likely impact that high-quality data will have on customer relationships?
- A. Higher customer acquisition costs
- B. Increased brand loyalty
- C. Improved customer trust and satisfaction
正解：C
解説：
Explanation
"The most likely impact that high-quality data will have on customer relationships is improved customer trust and satisfaction. High-quality data means that the data is accurate, complete, consistent, relevant, and timely for the AI task. High-quality data can improve customer relationships by enabling AI systems to provide personalized and relevant products, services, or solutions that meet the customers' expectations, needs, and interests. High-quality data can also improve customer trust and satisfaction by reducing errors, delays, or waste in customer interactions."
質問 # 32
A consultant conducts a series of Consequence Scanning workshops to support testing diverse datasets.
Which Salesforce Trusted AI Principles is being practiced>
- A. Accountability
- B. Transparency
- C. Inclusivity
正解：C
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 # 33
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. Email address
- B. Nickname
- C. Financial status
正解：C
解説：
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."
質問 # 34
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