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NEW QUESTION # 39
What should organizations do to ensure data quality for their AI initiatives?
- A. Prioritize model fine-tuning over data quality improvements.
- B. Collect and curate high-quality data from reliable sources.
- C. Rely on AI algorithms to automatically handle data quality issues.
Answer: B
Explanation:
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."
NEW QUESTION # 40
Which features of Einstein enhance sales efficiency and effectiveness?
- A. Opportunity List View, Lead List View, Account List view
- B. Opportunity Scoring, Opportunity List View, Opportunity Dashboard
- C. Opportunity Scoring, Lead Scoring, Account Insights
Answer: C
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 # 41
What Is a benefit of data quality and transparency as it pertains to bias in generated AI?
- A. Chances of bIas and mitigated
- B. Chances of bias are aggravated
- C. Chances of bias are remove
Answer: A
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 # 42
Which type of bias imposes a system 's values on others?
- A. Societal
- B. Association
- C. Automation
Answer: A
Explanation:
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."
NEW QUESTION # 43
Cloud Kicks wants to create a custom service analytics application to analyze cases in Salesforce. The application should rely on accurate data to ensure efficient case resolution.
Which data quality dimension Is essential for this custom application?
- A. Consistency
- B. Age
- C. Duplication
Answer: A
Explanation:
Explanation
"Consistency is the data quality dimension that is essential for creating a custom service analytics application to analyze cases in Salesforce. Consistency means that the data values are uniform and follow a common standard or format across different records, fields, or sources. Consistent data can ensure that the custom application can accurately and efficiently analyze cases and provide meaningful insights."
NEW QUESTION # 44
What is a key benefit of effective interaction between humans and AI systems?
- A. Leads to more informed and balanced decision making
- B. Alerts humans to the presence of biased data
- C. Reduces the need for human involvement
Answer: A
Explanation:
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."
NEW QUESTION # 45
What should be done to prevent bias from entering an AI system when training it?
- A. Use alternative assumptions.
- B. Include Proxy variables.
- C. Import diverse training data.
Answer: C
Explanation:
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."
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. Use demographic data to identify minority groups.
- B. Integrate AI models that auto-correct biased data.
- C. Implement Salesforce's Trusted AI Principles.
Answer: C
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
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. Consistency
- C. Accuracy
Answer: B
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 # 48
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
Answer: B
Explanation:
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."
NEW QUESTION # 49
How does the "right of least privilege" reduce the risk of handling sensitive personal data?
- A. By applying data retention policies
- B. By reducing how many attributes are collected
- C. By limiting how many people have access to data
Answer: C
Explanation:
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."
NEW QUESTION # 50
Which action should be taken to develop and implement trusted generated AI with Salesforce's safety guideline in mind?
- A. Develop right-sized models to reduce our carbon footprint.
- B. Be transparent when AI has created and automatically delivered content.
- C. Create guardrails that mitigates toxicity and protect PII
Answer: C
Explanation:
Explanation
"Creating guardrails that mitigate toxicity and protect PII is an action that should be taken to develop and implement trusted generative AI 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. Creating guardrails 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 AI systems. Creating guardrails can also help protect PII by masking or anonymizing personal or sensitive information generated by AI systems."
NEW QUESTION # 51
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. Usage
- B. Consent
- C. Duplication
Answer: C
Explanation:
Explanation
"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."
NEW QUESTION # 52
Cloud kicks wants to develop a solution to predict customers' interest based on historical data. The company found that employee region uses a text field to capture the product category while employee from all other locations use a picklist.
Which dimension of data quality is affected in this scenario?
- A. Completeness
- B. Consistency
- C. Accuracy
Answer: B
Explanation:
Explanation
"Consistency is the dimension of data quality 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 andprocessing. For example, using different field types for the same attribute can affect the consistency of the data."
NEW QUESTION # 53
What is a potential outcome of using poor-quality data in AI application?
- A. AI models may produce biased or erroneous results.
- B. AI model training becomes slower and less efficient
- C. AI models become more interpretable
Answer: A
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 # 54
A financial institution plans a campaign for preapproved credit cards?
How should they implement Salesforce's Trusted AI Principle of Transparency?
- A. Flag sensitive variables and their proxies to prevent discriminatory lending practices.
- B. Incorporate customer feedback into the model's continuous training.
- C. Communicate how risk factors such as credit score can impact customer eligibility.
Answer: A
Explanation:
Explanation
"Flagging sensitive variables and their proxies to prevent discriminatory lending practices is how they should implement Salesforce's Trusted AI Principle of Transparency. Transparency is one of the Trusted AI Principles that states 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. Flagging sensitive variables and their proxies means identifying and marking variables that can potentially cause discrimination or unfair treatment based on a person's identity or characteristics, such as age, gender, race, income, or credit score. Flagging sensitive variables and their proxies can help implement Transparency by allowing users to understand and evaluate the data used or generated by AI systems."
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. Confirmation
- B. Societal
- C. Survivorship
Answer: A
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
A business analyst (BA) wants to improve business by enhancing their sales processes and customer..
Which AI application should the BA use to meet their needs?
- A. Lead scoring, opportunity forecasting, and case classification
- B. Sales data cleansing and customer support data governance
- C. Machine learning models and chatbot predictions
Answer: A
Explanation:
Explanation
"Lead scoring, opportunity forecasting, and case classification are AI applications that can help a business analyst improve their sales processes and customer support. Lead scoring can help prioritize leads based on their likelihood to convert, opportunity forecasting can help predict future sales or revenue based on historical data and trends, and case classification can help categorize and route cases based on their attributes."
NEW QUESTION # 57
What is machine learning?
- A. AI that can grow its intelligence
- B. A data model used in Salesforce
- C. AI that creates new content
Answer: B
Explanation:
Explanation
"A data model is a machine learning feature used in Salesforce. A data model is a representation or abstraction of a real-world phenomenon or process using data structures and algorithms. A data model can be used to describe, analyze, or predict various aspects of the phenomenon or process using machine learning techniques."
NEW QUESTION # 58
How does a data quality assessment impact business outcome for companies using AI?
- A. Accelerates the delivery of new AI solutions
- B. Provides a benchmark for AI predictions
- C. Improves the speed of AI recommendations
Answer: B
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 # 59
A sales manager wants to improve their processes using AI in Salesforce?
Which application of AI would be most beneficial?
- A. Data modeling and management
- B. Sales dashboards and reporting
- C. Lead soring and opportunity forecasting
Answer: C
Explanation:
Explanation
"Lead scoring and opportunity forecasting are applications of AI that would be most beneficial for a sales manager who wants to improve their processes using AI in Salesforce. Lead scoring can help prioritize leads based on their likelihood to convert, while opportunity forecasting can help predict future sales or revenue based on historical data and trends. These applications of AI can help optimize sales processes by providing insights and recommendations that can increase sales efficiency and effectiveness."
NEW QUESTION # 60
What are the three commonly used examples of AI in CRM?
- A. Einstein Bots, face recognition, recommendations
- B. Predictive scoring, forecasting, recommendations
- C. Predictive scoring, reporting, Image classification
Answer: B
Explanation:
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."
NEW QUESTION # 61
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. A marketing article of the product that clearly outlines the oroduct's capabilities and features
- B. An explanation of the prediction's rationale and a model card that describes how the model was created
- C. An explanation of how Prediction Builder works and a link to Salesforce's Trusted AI Principles
Answer: B
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 # 62
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