[Mar-2024] Free Salesforce-AI-Associate Exam Questions Salesforce-AI-Associate Actual Free Exam Questions
Verified Salesforce-AI-Associate dumps and 78 unique questions
Salesforce Salesforce-AI-Associate Exam Syllabus Topics:
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NEW QUESTION # 38
What role does data quality play in the ethical us of AI applications?
- A. High-quality data is essential for ensuring unbased 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 data is not overfitted to demographic groups.
Answer: A
Explanation:
Explanation
"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."
NEW QUESTION # 39
What is a Key consideration regarding data quality in AI implementation?
- A. Integration process of AI models with Salesforce workflows
- B. Data's role in training and fine-tuning Salesforce AI models
- C. Techniques from customizing AI features in Salesforce
Answer: B
Explanation:
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."
NEW QUESTION # 40
How does AI which CRM help sales representatives better understand previous customer interactions?
- A. Triggers personalized service replies
- B. Provides call summaries
- C. Creates, localizes, and translates product descriptions
Answer: B
Explanation:
Explanation
"Providing call summaries is how AI with CRM helps sales representatives better understand previous customer interactions. Call summaries are a feature that uses natural language processing (NLP) to analyze voice conversations between sales representatives and customers and generate summaries or transcripts of the calls. Call summaries can help sales representatives better understand previous customer interactions by providing key information, insights, or action items from the calls."
NEW QUESTION # 41
To avoid introducing unintended bias to an AI model, which type of data should be omitted?
- A. Engagement
- B. Transactional
- C. Demographic
Answer: C
Explanation:
Explanation
"Demographic data should be omitted to avoid introducing unintended bias to an AI model. 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."
NEW QUESTION # 42
An administrator at Cloud Kicks wants to ensure that a field is set up on the customer record so their preferred name can be captured.
Which Salesforce field type should the administrator use to accomplish this?
- A. Text
- B. Multi-Select Picklist
- C. Rich Text Area
Answer: A
Explanation:
Explanation
"A text field type should be used to capture the customer's preferred name. A text field type allows the user to enter any combination of letters, numbers, or symbols. A text field type can be used to store names, addresses, phone numbers, or other personal information."
NEW QUESTION # 43
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
Answer: A
Explanation:
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."
NEW QUESTION # 44
Cloud Kicks wants to use Einstein Prediction Builder to determine a customer's likelihood of buying specific products; however, data quality is a...
How can data quality be assessed quality?
- A. Build reports to expire the data quality.
- B. Leverage data quality apps from AppExchange
- C. Build a Data Management Strategy.
Answer: B
Explanation:
Explanation
"Leveraging data quality apps from AppExchange is how data quality can be assessed. 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. Leveraging data quality apps from AppExchange means using third-party applications or solutions that can help measure, monitor, or improve data quality in Salesforce."
NEW QUESTION # 45
What is the best method to safeguard customer data privacy?
- A. Track customer data consent preferences.
- B. Archive customer data on a recurring schedule.
- C. Automatically anonymize all customer data.
Answer: A
Explanation:
Explanation
"Tracking customer data consent preferences is the best method to safeguard customer data privacy. Data privacy is the right of individuals to control how their personal data is collected, used, shared, or stored by others. Tracking customer data consent preferences means respecting and honoring the choices and preferences of customers regarding their personal data. Tracking customer data consent preferences can help ensure compliance with data privacy laws and regulations, as well as build trust and loyalty with customers."
NEW QUESTION # 46
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. Implement Salesforce's Trusted AI Principles.
- B. Integrate AI models that auto-correct biased data.
- C. Use demographic data to identify minority groups.
Answer: A
Explanation:
Explanation
"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."
NEW QUESTION # 47
How does a data quality assessment impact business outcome for companies using AI?
- A. Improves the speed of AI recommendations
- B. Accelerates the delivery of new AI solutions
- C. Provides a benchmark for AI predictions
Answer: C
Explanation:
Explanation
"A data quality assessment impacts business outcomes for companies using AI by providing a benchmark for AI predictions. A data quality assessment is a process that measures and evaluates the quality of data for a specific purpose or task. A data quality assessment can help identify and address any issues or gaps in the data quality dimensions, such as accuracy, completeness, consistency, relevance, and timeliness. A data quality assessment can impact business outcomes for companies using AI by providing a benchmark for AI predictions, as it can help ensure that the predictions are based on high-quality data that reflects the true state or condition of the target population or domain."
NEW QUESTION # 48
Cloud kicks wants to decrease the workload for its customer care agents by implementing a chatbot on its website that partially deflects incoming cases by answering frequency asked questions Which field of AI is most suitable for this scenario?
- A. Computer vision
- B. Natural language processing
- C. Predictive analytics
Answer: B
Explanation:
Explanation
"Natural language processing is the field of AI that is most suitable for this scenario. Natural language processing (NLP) is a branch of AI that enables computers to understand and generate natural language, such as speech or text. NLP can be used to create conversational interfaces that can interact with users using natural language, such as chatbots. Chatbots can help automate and streamline customer service processes by providing answers, suggestions, or actions based on the user's intent and context."
NEW QUESTION # 49
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.
Answer: C
Explanation:
Explanation
"High-quality data improves the reliability and credibility of AI-driven decisions, fostering trust among users.
High-quality data means that the data is accurate, complete, consistent, relevant, and timely for the AI task.
High-quality data can improve the performance and reliability of AI systems, as they have enough and correct information to learn from and make accurate predictions. High-quality data can also improve the trustworthiness of AI-driven decisions, as users can have more confidence and satisfaction in using AI systems."
NEW QUESTION # 50
What Is a benefit of data quality and transparency as it pertains to bias in generated AI?
- A. Chances of bias are aggravated
- B. Chances of bias are remove
- C. Chances of bIas and mitigated
Answer: C
Explanation:
Explanation
"Data quality and transparency can help mitigate the chances of bias in generative AI. Data quality means that the data is accurate, complete, consistent, relevant, and timely for the AI task. Data quality can help mitigate bias by ensuring that the generative AI model learns from a balanced and representative sample of the target population or domain. Data transparency means that the data sources, methods, and processes are clear and open to inspection and verification. Data transparency can help mitigate bias by allowing users to understand and evaluate the data used or generated by the generative AI model."
NEW QUESTION # 51
What is a possible outcome of poor data quality?
- A. Biases in data can be inadvertently learned and amplified by AI systems.
- B. AI predictions become more focused and less robust.
- C. AI models maintain accuracy but have slower response times.
Answer: A
Explanation:
Explanation
"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."
NEW QUESTION # 52
Cloud Kicks wants to develop a solution to 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
Answer: C
Explanation:
Explanation
"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 across different 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."
NEW QUESTION # 53
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
Answer: A
Explanation:
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."
NEW QUESTION # 54
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.
Answer: C
Explanation:
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."
NEW QUESTION # 55
Cloud Kicks implements a new product recommendation feature for its shoppers that recommends shoes of a given color to display to customers based on the color of the products from their purchase history.
Which type of bias is most likely to be encountered in this scenario?
- A. Societal
- B. Survivorship
- C. Confirmation
Answer: C
Explanation:
Explanation
"Confirmation bias is most likely to be encountered in this scenario. Confirmation bias is a type of bias that occurs when data or information confirms or supports one's existing beliefs or expectations. For example, confirmation bias can occur when a product recommendation feature only recommends shoes of a given color based on the customer's purchase history, without considering other factors or preferences that may influence their choice."
NEW QUESTION # 56
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. Nickname
- B. Financial status
- C. Email address
Answer: B
Explanation:
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."
NEW QUESTION # 57
What is a key characteristic of machine learning in the context of AI capabilities?
- A. Uses algorithms to learn from data and make decisions
- B. Can perfectly mimic human intelligence and decision-making
- C. Relies on preprogrammed rules to make decisions
Answer: A
Explanation:
Explanation
"Machine learning is a key characteristic of AI capabilities that uses algorithms to learn from data and make decisions. Machine learning is a branch of AI that enables computers to learn from data without being explicitly programmed. Machine learning algorithms can analyze data, identify patterns, and make predictions or recommendations based on the data."
NEW QUESTION # 58
What is a benefit of a diverse, balanced, and large dataset?
- A. Data privacy
- B. Training time
- C. Model accuracy
Answer: C
Explanation:
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."
NEW QUESTION # 59
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
Answer: C
Explanation:
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."
NEW QUESTION # 60
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. Determine data availability.
- B. Determine data outcomes.
- C. Remove biased data.
Answer: A
Explanation:
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.
NEW QUESTION # 61
What is a potential source of bias in training data for AI models?
- A. The data is collected from a diverse range of sources and demographics.
- B. The data is collected in area time from sources systems.
- C. The data is skewed toward is particular demographic or source.
Answer: C
Explanation:
Explanation
"A potential source of bias in training data for AI models is that the data is skewed toward a particular demographic or source. Skewed data means that the data is not balanced or representative of the target population or domain. Skewed data can introduce or exacerbate bias in AI models, as they may overfit or underfit the model to a specific subset of data. For example, skewed data can lead to bias if the data is collected from a limited or biased demographic or source, such as a certain age group, gender, race, location, or platform."
NEW QUESTION # 62
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