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WorksheetsDe 71 cau - In-progress
Total questions: 110
Worksheet time: 55mins
What is a key characteristic of machine learning in the context of AI capabilities?
Can perfectly mimic human intelligence and decision-making
Uses algorithms to learn from data and make decisions
Relies on preprogrammed rules to make decisions
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?
Completeness
Accuracy
Consistency
Cloud Kicks' latest email campaign is struggling to attract new customers.
How can AI increase the company's customer email engagement?
Remove invalid email addresses
Create personalized emails
Resend emails to inactive recipients
How does data quality impact the trustworthiness of Al-driven decisions?
Low-quality data reduces the risk of overfitting the model, improving the trustworthiness of the predictions.
The use of both low-quality and high-quality data can improve the accuracy and reliability of AI-driven decisions.
High-quality data improves the reliability and credibility of Al-driven decisions, fostering trust among users.
What is a possible outcome of poor data quality?
AI models maintain accuracy but have slower response times.
AI predictions become more focused and less robust.
Biases in data can be inadvertently learned and amplified by AI systems.
Which statement exemplifies Salesforces honesty guideline when training AI models?
Control bias, toxicity, and harmful content with embedded guardrails and guidance.
Minimize the AI models carbon footprint and environment impact during training.
Ensure appropriate consent and transparency when using AI-generated responses.
Which Einstein capability uses emails to create content for Knowledge articles?
Predict
Generate
Discover
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?
Implement Salesforce's Trusted AI Principles.
Integrate AI models that auto-correct biased data.
Use demographic data to identify minority groups.
What is an example of ethical debt?
Delaying an AI product launch to retrain an AI data model
Violating a data privacy law and falling to pay fines
Launching an AI feature after discovering a harmful bias
How does AI which CRM help sales representatives better understand previous customer interactions?
Creates, localizes, and translates product descriptions
Triggers personalized service replies
Provides call summaries
What is the role of Salesforce Trust AI principles in the context of CRM system?
Providing a framework for AI data model accuracy
Outlining the technical specifications for AI integration
Guiding ethical and responsible use of AI
Which type of bias imposes a system 's values on others?
Automation
Societal
Association
Cloud Kicks discovered multiple variations of state and country values in contact records.
Which data quality dimension is affected by this issue?
Usage
Accuracy
Consistency
What is a Key consideration regarding data quality in AI implementation?
Techniques from customizing AI features in Salesforce
Integration process of AI models with Salesforce workflows
Data's role in training and fine-tuning Salesforce AI models
What is the main focus of the Accountability principle in Salesforce's Trusted AI Principles?
Taking responsibility for one's actions toward customers, partners, and society
Safeguarding fundamental human rights and protecting sensitive data
Ensuring transparency In Al-driven recommendations and predictions
A sales manager wants to improve their processes using AI in Salesforce?
Which application of AI would be most beneficial?
Data modeling and management
Lead soring and opportunity forecasting
Sales dashboards and reporting
How does the "right of least privilege" reduce the risk of handling sensitive personal data?
By reducing how many attributes are collected
By limiting how many people have access to data
By applying data retention policies
What Is a benefit of data quality and transparency as it pertains to bias in generated AI?
Chances of bias are aggravated
Chances of bIas and mitigated
Chances of bias are remove
The Cloud technical team is assessing the effectiveness of their AI development processes?
Which established Salesforce Ethical Maturity Model should the team use to guide the development of trusted AI solution?
Ethical AI Prediction Maturity Model
Ethical AI Process Maturity Model
Ethical AI practice Maturity Model
Cloud Kicks wants to evaluate its data quality to ensure accurate and up-to-date records.
Which type of records negatively impact data quality?
Duplicate
Complete
Structured
Cloud Kicks is testing a new AI model.
Which approach aligns with Salesforce's Trusted AI Principle of Incluslvity?
Rely on a development team with uniform backgrounds to assess the potential societal implications of the model.
Test only with data from a specific region or demographic to limit the risk of data leaks.
Test with diverse and representative datasets appropriate for how the model will be used.
What is the most likely impact that high-quality data will have on customer relationships?
Improved customer trust and satisfaction
Higher customer acquisition costs
Increased brand loyalty
A developer has a large amount of data, but it is scattered across different systems and is not standardized.
Which key data quality element should they focus on to ensure the effectiveness of the AI models?
Performance
Consistency
Volume
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?
Usage
Duplication
Consent
Which best describes the different between predictive AI and generative AI?
Predictive new and original output for a given input.
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.
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
Cloud Kicks wants to ensure that multiple records for the same customer are removed in Salesforce.
Which feature should be used to accomplish this?
Trigger deletion of old records
Standardized field names
Duplicate management
Cloud Kicks uses Einstein to generate predictions out is not seeing accurate results?
What to a potential mason for this?
Too much data
The wrong product
Poor data quality
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?
Consistency
Accuracy
Completeness
Which type of bias results from data being labeled according to stereotypes?
Association
Societal
Interaction
A sales manager is looking to enhance the quality of lead data in their CRM system.
Which process will most likely help the team accomplish this goal?
Review and update missing lead information.
Redesign the lead conversion process,
Prioritize active leads quarterly.
What is machine learning?
AI that creates new content
AI that can grow its intelligence
A data model used in Salesforce
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?
Multi-Select Picklist
Text
Rich Text Area
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?
Lead scoring, opportunity forecasting, and case classification
Machine learning models and chatbot predictions
Sales data cleansing and customer support data governance
What are the potential consequences of an organization suffering from poor data quality?
Revenue loss, poor customer service, and reputational damage
Technical debt, monolithic system architecture, and slow ETL throughput
Low employee morale, stock devaluation, and inability to attract top talent
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?
Determine data outcomes.
Remove biased data.
Determine data availability.
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?
Build a Data Management Strategy.
Leverage data quality apps from AppExchange
Build reports to expire the data quality.
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?
Duplication
Consistency
Age
How does a data quality assessment impact business outcome for companies using AI?
Provides a benchmark for AI predictions
Improves the speed of AI recommendations
Accelerates the delivery of new AI solutions
Which features of Einstein enhance sales efficiency and effectiveness?
Opportunity Scoring, Opportunity List View, Opportunity Dashboard
Opportunity Scoring, Lead Scoring, Account Insights
Opportunity List View, Lead List View, Account List view
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?
Confirmation
Survivorship
Societal
Cloud Kicks plans to use automated chat as its primary support channel.
Which Einstein feature should they use?
Discovery
Bots
Next Best Action
In the context of Salesforce's Trusted AI Principles what does the principle of Empowerment primarily aim to achieve?
Empower users to solve challenging technical problems using neural networks.
Empower users to contribute to the growing body of knowledge of leading AI research.
Empower users to off all skill level to build AI application with clicks, not code.
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?
An explanation of the prediction's rationale and a model card that describes how the model was created
An explanation of how Prediction Builder works and a link to Salesforce's Trusted AI Principles
A marketing article of the product that clearly outlines the oroduct's capabilities and features
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?
Number of variables ipn the dataset
Age of the dataset
Size of the dataset
What should an organization do to enforce consistency across accounts for newly entered records?
Merge all duplicate accounts into a single record when duplicate entries are detected.
Input the data exactly as it appears from the source, such as the company's website or social media,
Implement naming conventions or a predefined list of user-selectable values for organization-wide records.
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?
Volume
Reliability
Age
What is a societal implication of excluding ethics in AI development?
Faster and cheaper development
More innovation and creativity
Harm to marginalized communities
Cloud Kicks relies on data analysis to optimize its product recommendations for customers.
How will incomplete data quality impact the company's recommendations?
The response time for the product
The accuracy of the product
The diversity of the product
A business analyst (BA) is preparing a new use case for Al. They run a report to check for null values in the attributes they plan to use.
Which data quality component Is the BA verifying by checking for null values?
Completeness
Duplication
Usage
Why is it critical to consider privacy concerns when dealing with AI and CRM data?
Confirms the data is accessible to all users
Increases the volume of data collected
Ensures compliance with laws and regulations
What are the three commonly used examples of AI in CRM?
Einstein Bots, face recognition, recommendations
Predictive scoring, forecasting, recommendations
Predictive scoring, reporting, Image classification
A financial institution plans a campaign for preapproved credit cards?
How should they implement Salesforce's Trusted AI Principle of Transparency?
Communicate how risk factors such as credit score can impact customer eligibility.
Incorporate customer feedback into the model's continuous training.
Flag sensitive variables and their proxies to prevent discriminatory lending practices.
How does an organization benefit from using AI to personalize the shopping experience of online customers?
Customers are more likely to share personal information with a site that personalizes their experience.
Customers are more likely to be satisfied with their shopping experience.
Customers are more likely to visit competitor sites that personalize their experience.
Cloud Kicks wants to evaluate the quality of its sales data.
Which first step should they take for the data quality assessment?
Run a new report or dashboard.
Plan and align territories,
Identify business objectives.
A consultant discusses the role of humans in AI-driven CRM processes with a customer. What is one challenge the consultant should mention about human-AI collaboration in decision-making?
Lack of technical skills on the team
Difficulty interpreting AI decisions
High cost of AI implementation
Which data does Salesforce automatically exclude from marketing Cloud Einstein engagement model training to mitigate bias and ethic...
Geographic
Geographicggew
Cryptographic
What are some of the ethical challenges associated with AI development?
Potential for human bias in machine learning algorithms and the lack of transparency in AI decision-making processes
Implicit transparency of AI systems, which makes It easy for users to understand and trust their decisions
Inherent neutrality of AI systems, which eliminates any potential for human bias in decision-making
What is a sensitive variable that car esc to bias?
Gender
Country
Education level
t data quality dimension refers to the frequency and timelines of data updates?
Data Leakage
Data Freshness
. Data Source
What is one technique to mitigate bias and ensure fairness in AI applications?
Ongoing auditing and monitoring of data that is used in AI applications
Excluding data features from the Al application to benefit a population
Using data that contains more examples of minority groups than majority groups
What is a potential source of bias in training data for AI models?
The data is collected in area time from sources systems.
The data is skewed toward is particular demographic or source.
The data is collected from a diverse range of sources and demographics.
What is the best method to safeguard customer data privacy?
Automatically anonymize all customer data.
Track customer data consent preferences.
Archive customer data on a recurring schedule.
What does the term "data completeness" refer to in the context of data quality?
The degree to which all required data points are present in the dataset
The process of aggregating multiple datasets from various databases
The ability to access data from multiple sources in real time
What should be done to prevent bias from entering an AI system when training it?
Include proxy variables
Use alternative assumptions
Import diverse training data
What should organizations do to ensure data quality for their AI initiatives?
Rely on AI algorithms to automatically handle data quality issues.
Collect and curate high-quality data from reliable sources.
Prioritize model fine-tuning over data quality improvements.
What is a potential outcome of using poor-quality data in AI application?
AI model training becomes slower and less efficient
AI models become more interpretable
AI models may produce biased or erroneous results.
How does AI assist in lead qualification?
Scores leads based on customer data
Creates personalized SMS campaigns
Automatically interacts with prospects
Which AI tool is a web of connections, guided by weights and biases?
Neural networks
Predictive Analytics
Rules- based systems
Mark this item for later review
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?
Nickname
Email address
Financial status
How does poor data quality affect predictive and generative AI models?
Increases raw data volume
Creates inaccurate results
Decreases storage efficiency
What is the significance of explain ability of trusted AI systems?
Increases the complexity of AI models
Enhances the security and accuracy of AI models
Describes how Al models make decisions
A system admin recognizes the need to put a data management strategy in place.
What is a key component of data management strategy?
Naming Convention
Data Backup
Color Coding
A consultant conducts a series of Consequence Scanning workshops to support testing diverse datasets.
Which Salesforce Trusted AI Principles is being practiced>
Inclusivity
Transparency
Accountability
Which action should be taken to develop and implement trusted generated AI with Salesforce's safety guideline in mind?
Develop right-sized models to reduce our carbon footprint.
Create guardrails that mitigates toxicity and protect PII
Be transparent when AI has created and automatically delivered content.
What should be done to prevent bias from entering an AI system when training it?
Include proxy variables
Import diverse training data
Use alternative assumptions
CloudKicks wants to use AI to enhance its sales processes and customer experience. Which capability should they use
Sales path and automation of case escalation
Dashboard of Current Leads and Cases
Einstein Lead Scoring and Case Classification
. Which AI type plays a crucial role in Salesforce's predictive text and speech recognition capabilities, enabling the platform to understand and respond to user commands accurately?
Predictive Analysis
Computer Vision
Natural Language Processing (NLP)
Which feature of Marketing Cloud Einstein uses AI to predict consumer engagement with email and MobilePush messaging?
. Content Selection
Engagement Scoring
Email Recommendations
What is a unique and distinguishing feature of deep learning in the context of AI capabilities?
. Deep learning uses algorithm to cleanse and prepare data for AI implementations
Deep learning uses neural networks with multiple layers to learn from a large amount of data
Deep learning uses historical data to predict future outcomes
A Salesforce Consultant is discussing AI capabilities with a customer who is interested in improving their sales processes. Which type of AI would be most suitable for enhancing sales processes in Salesforce Customer 360?
Natural Language Processing (NLP)
Computer Vision
Predictive Analysis
What are the 3 main types of AI capabilities in Salesforce?
Generative, Descriptive, Analytic
Predictive, Generative, Analytic
Predictive, Reactive, Analytics
hich type of Salesforce application is recommended to enhance the sales process?
Einstein Lead Scoring
Einstein Prediction Builder
Einstein Voice
What is a key benefit in implementing AI in a CRM system?
Reduced data governance
Enhanced customer support
Improved platform speed
CloudKicks is implementing AI in their CRM system and is focusing on data management. What is the benefit of using a data management approach in AI implementation?
Reduces the amount of data in the CRM system
Eliminates the need for data governance
Emphasizes the importance of data quality
loudKicks wants to implement Salesforce AI features. They are concerned about potential ethical and privacy challenges. What should be recommended to minimize potential AI bias?
AI models that auto-correct biased data
Salesforce Trusted AI Principles
Demographic data to identify minority groups
consultant designs a new AI model for a financial services company that offers personal loans. Which variable within their proposed model might introduce unintended bias?
Loan Date
Postal Code
Payment Due Date
CloudKicks is planning to automate its customer service chat using natural language processing. According to Salesforce's Trusted AI Principles, how should this be disclosed to the customer?
They do not need to be informed that they're chatting with AI
Inform them at the beginning of the interaction that they're chatting with AI
Inform the customer they're chatting with AI when they request a live agent
CloudKicks wants to implement AI features in their CRM System. They have expressed concerns about the quality of their existing data. What advice should be given to them regarding the importance of data quality for AI implementation?
AI systems can handle any data inaccuracies
Assessing and improving data quality is crucial for accurate AI predictions and insights
Assessing data quality is only necessary for large datasets
What role does data play in AI models?
Data is only used for testing AI models
Data is used for testing and training AI models
Data is only used for validating AI models
A Salesforce consultant is considering the data sets to use for training AI models for a project on the Customer 360 platform. What should be considered when selecting data sets for the AI models?
Age, completeness, accuracy, consistency, duplication, and usage of the data se
Age, completeness, consistency, theme, duplication, and usage of the data sets
Duplication, accuracy, consistency, storage location and usage of the data sets
. What is a key consideration regarding data quality in AI implementation?
Integration process of AI models with Salesforce workflows
Techniques from customizing AI features in Salesforce
Data's role in training and fine-tuning the Salesforce AI models
How is Natural Language Processing (NLP) used in the context of AI capabilities?
To cleanse and prepare data for AI implementations
To interpret and understand programming language
To understand and generate human language
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?
Reduced need for healthcare expertise in interpreting AI outputs
Enhanced accuracy and reliability of medical predictions and diagnosis
Ensure compatibility of AI algorithms with the system's infrastructure
. What are some ethical challenges associated with AI development?
Potential for human bias in machine learning algorithms and lack of transparency in AI-driven decision-making processes
Implicit transparency of AI systems, which make it easy for users to understand and trust their decisions
nherent neutrality of AI systems, which eliminates any potential for human bias in decision making
CloudKicks wants to use AI to enhance its sales processes and customer experience. Which capability should they use?
Dashboard of Current Leads and Cases
Sales path and automation of case escalation
Einstein Lead Scoring and Case Classification
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 beaccessible on the Salesforce Platform?
A marketing article of the product that clearly outlines the oroduct's capabilities and features
An explanation of how Prediction Builder works and a link to Salesforce's Trusted AI Principles
An explanation of the prediction's rationale and a model card that describes how the model wascreated
What is an example of Salesforce's Trusted AI Principle of Inclusivity in practice?
Working with human rights experts
Striving for model explain ability
Testing models with diverse datasets
What is a key challenge of human AI collaboration in decision-making?
Leads to move informed and balanced decision-making
Creates a reliance on AI, potentially leading to less critical thinking and oversight
Reduce the need for human involvement in decision-making processes
A marketing manager wants to use AI to better engage their customers.Which functionality provides the best solution?
Einstein Engagement
Bring Your Own Model
Journey Optimization
What is the key difference between generative and predictive AI?
. Generative AI creates new content based on existing data and predictive AI analyzes existing data.
Generative AI finds content similar to existing data and predictive AI analyzes existing data
Generative AI analyzes existing data and predictive AI creates new content based on existing data.
What can bias in AI algorithms in CRM lead to?
Advertising cost increases
Personalization and target marketing changes
Ethical challenges in CRM systems
How is natural language processing (NLP) used in the context of AI capabilities?
To cleanse and prepare data for AI implementations
To understand and generate human language
To interpret and understand programming language
What is a key benefit of effective interaction between humans and AI systems?
Leads to more informed and balanced decision making
Alerts humans to the presence of biased data
Reduces the need for human involvement
. What is an implication of user consent in regard to AI data privacy?
AI operates Independently of user privacy and consent
AI infringes on privacy when user consent is not obtained.
AI ensures complete data privacy by automatically obtaining user consent
What are the key components of the data quality standard?
Naming, formatting, Monitoring
Accuracy, Completeness, Consistency
Reviewing, Updating, Archiving
A data quality expert at Cloud Kicks want to ensure that each new contact contains at least an email address ...Which feature should they use to accomplish this?
Autofill
Validation rule
Duplicate matching rule
What is a benefit of a diverse, balanced, and large dataset?
Model accuracy
Data privacy
Training time
What is the rile of data quality in achieving AI business Objectives?
Data quality is required to create accurate AI data insights.
Data quality is unnecessary because AI can work with all data types
Data quality is important for maintain Ai data storage limits
What are some key benefits of AI in improving customer experiences in CRM?
Improves CRM security protocols, safeguarding sensitive customer data from potential breachesand threats
Streamlines case management by categorizing and tracking customer support cases, identifyingtopics, and summarizing case resolutions
Fully automates the customer service experience, ensuring seamless automated interactions withcustomers
To avoid introducing unintended bias to an AI model, which type of data should be omitted?
Demographic
Transactional
Engagement
