WorksheetsVichu AI Associate Exam
Total questions: 79
Worksheet time: 40mins
Which best describes the difference between predictive AI and generative AI?
Predictive AI uses machine learning to classify or predict outputs from its input data whereas generative AI does not use machine learning to generate its output.
Predictive AI uses machine learning to classify or predict outputs from its input data whereas generative AI uses machine learning to generate new and original output for a given input.
Predictive AI and generative AI have the same capabilities but differ in the type of input they receive; predictive AI receives raw data whereas generative AI receives natural language.
What is an implication of user consent in regard to AI data privacy?
AI operates independently of user privacy and consent.
AI ensures complete data privacy by automatically obtaining user consent.
AI infringes on privacy when user consent is not obtained.
What are predictive analytics, machine learning, natural language processing (NLP), and computer vision?
Different types of data models used in Salesforce
Different types of automation tools used in Salesforce
Different types of AI that can be applied in Salesforce
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 scoring and opportunity forecasting
Sales dashboards and reporting
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
Cloud Kicks plans to use automated chat as its primary support channel. Which Einstein feature should they use?
Discovery
Bots
Next Best Action
Cloud Kicks discovered multiple variations of state and country values in contact records. Which data quality dimension is affected by this issue?
Consistency
Accuracy
Usage
Cloud Kicks' latest email campaign is struggling to attract new customers. How can AI increase the company's customer email engagement?
Create personalized emails
Resend emails to inactive recipients
Remove invalid email addresses
What is the significance of explainability of trusted AI systems?
Increases the complexity of AI models
Enhances the security and accuracy of AI models
Describes how AI models make decisions
What is a benefit of data quality and transparency as it pertains to bias in generative AI?
Chances of bias are aggravated.
Chances of bias are removed.
Chances of bias are mitigated.
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
Ensuring transparency in AI-driven recommendations and predictions
Safeguarding fundamental human rights and protecting sensitive data
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?
Financial status
Nickname
Email address
What is a key challenge of human-AI collaboration in decision-making?
Creates a reliance on AI, potentially leading to less critical thinking and oversight
Leads to more informed and balanced decision-making
Reduces the need for human involvement in decision-making processes
Which statement exemplifies Salesforce's honesty guideline when training AI models?
Minimize the AI model's carbon footprint and environmental impact during training.
Choose smaller better-trained models instead of larger more sparsely trained models.
Ensure appropriate consent and transparency when using AI-generated responses.
What is a potential outcome of using poor-quality data in AI applications?
AI models are less accurate but easier to train.
AI models may produce biased or erroneous results.
AI model training becomes slower and less efficient.
In the context of Salesforce's Trusted AI Principles, what does the principle of Responsibility primarily focus on?
Providing a framework for data model accuracy
Ensuring ethical use of AI
Outlining the technical specifications for AI integration
What is the best method to safeguard customer data privacy?
Track customer data consent preferences.
Archive customer data on a recurring schedule.
Protect customer data with encrypted access.
What are some of the ethical challenges associated with AI development?
Striving for model explainability
Testing models with diverse datasets
What is an example of Salesforce's Trusted AI Principle of Inclusivity in practice?
Working with human rights experts
Striving for model explainability
Testing models with diverse datasets
What are the three commonly used examples of AI in CRM?
Einstein Bots, face recognition, recommendations
Predictive scoring, forecasting, recommendations
Predictive scoring, reporting, Einstein Bots
What is a sensitive variable that can lead to bias?
Education level
Country
Gender
What is a potential source of bias in training data for AI models?
The data is collected from a diverse range of sources and demographics.
The data is skewed toward a particular demographic or source.
The data is collected in real time from source systems.
What are the potential consequences of an organization suffering from poor data quality?
Low employee morale, stock devaluation, and inability to attract top talent
Revenue loss, poor customer service, and reputational damage
Technical debt, monolithic system architecture, and slow ETL throughput
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 frequently asked questions. Which field of AI is most suitable for this scenario?
Predictive analytics
Natural language processing
Computer vision
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.
Determine data availability.
Determine data biases.
What is a benefit of a diverse, balanced, and large dataset?
Model accuracy
Model trainability
Model complexity
Cloud Kicks wants to use AI to enhance its sales processes and customer support. Which capability should they use?
Einstein Lead Scoring and Case Classification
Einstein Next Best Action and Case Auto Response Rules
Sales Path and Automated Case Escalations
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
A Salesforce administrator creates a new field to capture an order's destination country. Which field type should they use to ensure data quality?
Picklist
Address
Text
Cloud Kicks wants to use Einstein Prediction Builder to determine a customer's likelihood of buying specific products; however, data quality is a concern. How can data quality be assessed quickly?
Build a Data Management Strategy.
Run reports to explore the data quality.
Leverage data quality apps from AppExchange.
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 of all skill levels to build AI applications with clicks, not code.
Empower users to contribute to the growing body of knowledge of leading AI research.
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
A business analyst (BA) is preparing a new use case for AI. 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?
Duplication
Usage
Completeness
Cloud Kicks wants to evaluate its data quality to ensure accurate and up-to-date records. Which type of records negatively impact data quality?
Structured
Complete
Duplicate
How does a data quality assessment impact business outcomes for companies using AI?
Accelerates the delivery of new AI solutions
Provides a benchmark for AI predictions
Improves the speed of AI recommendations
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?
Redesign the lead conversion process.
Review and update missing lead information.
Prioritize active leads quarterly.
What should organizations do to ensure data quality for their AI initiatives?
Collect and curate high-quality data from reliable sources.
Prioritize model fine-tuning over data quality improvements.
Develop AI algorithms to automatically handle data quality issues.
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 AI application to benefit a population
Using data that contains more examples of minority groups than majority groups
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 frequently asked questions. Which field of AI is most suitable for this scenario?
Natural language processing
Predictive analytics
Computer vision
The Cloud Kicks 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 solutions?
Ethical AI Process Maturity Model
Ethical AI Prediction Maturity Model
Ethical AI Practice Maturity Model
A sales manager wants to improve their processes using AI in Salesforce. Which application of AI would be most beneficial?
Sales dashboards and reporting
Lead scoring and opportunity forecasting
Data modeling and management
What can bias in AI algorithms in CRM lead to?
Personalization and targeted marketing changes
Advertising cost increases
Ethical challenges in CRM systems
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 picklist. Which dimension of data quality is affected in this scenario?
Completeness
Consistency
Accuracy
Which dimension of data quality is affected in this scenario?
Completeness
Consistency
Accuracy
What is the most likely impact that high-quality data will have on customer relationships?
Higher customer acquisition costs
Increased brand loyalty
Improved customer trust and satisfaction
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 of all skill levels to build AI applications with clicks, not code.
Cloud Kicks wants to use AI to enhance its sales processes and customer support. Which capability should they use?
Dashboard of Current Leads and Cases
Einstein Lead Scoring and Case Classification
Sales Path and Automated Case Escalations
Why is it critical to consider privacy concerns when dealing with AI and CRM data?
Confirms the data is accessible to all users
Ensures compliance with laws and regulations
Increases the volume of data collected
How does AI within CRM help sales representatives better understand previous customer interactions?
Provides call summaries
Triggers personalized service replies.
Creates, localizes, and translates product descriptions
A service leader wants to use AI to help customers resolve their issues quicker in a guided self-serve application. Which Einstein functionality provides the best solution?
Bots
Recommendation
Case Classification
Which data does Salesforce automatically exclude from Marketing Cloud Einstein engagement model training to mitigate bias and ethical risks?
Geographic
Demographic
Cryptographic
Cloud Kicks wants to use Einstein Prediction Builder to determine a customer's likelihood of buying specific products; however, data quality is a concern. How can data quality be assessed quickly?
Run reports to explore the data quality.
Leverage data quality apps from AppExchange.
Build a Data Management Strategy.
What role does data quality play in the ethical use of AI applications?
High-quality data is essential for ensuring unbiased and fair AI decisions, promoting ethical use, and preventing discrimination.
High-quality data ensures the presence of demographic attributes required for personalized campaigns.
Low-quality data reduces the risk of unintended bias as the data is not overfitted to demographic groups.
What is the role of data quality in achieving AI business objectives?
Data quality is unnecessary because AI can work with all data types.
Data quality is important for maintaining AI data storage limits.
Data quality is required to create accurate AI data insights.
What is a potential source of bias in training data for AI models?
The data is collected in real time from source systems.
The data is skewed toward a particular demographic or source.
The data is collected from a diverse range of sources and demographics.
A system admin recognizes the need to put a data management strategy in place. What is a key component of a data management strategy?
Naming Convention
Data Backup
Color Coding
A data quality expert at Cloud Kicks wants to ensure that each new contact contains at least an email address or phone number. Which feature should they use to accomplish this?
Validation rule
Autofill
Duplicate matching rule
Which best describes the difference between predictive AI and generative AI?
Predictive AI uses machine learning to classify or predict outputs from its input data whereas generative AI does not use machine learning to generate its output.
Predictive AI and generative AI have the same capabilities but differ in the type of input they receive; predictive AI receives raw data whereas generative AI receives natural language.
Predictive AI uses machine learning to classify or predict outputs from its input data whereas generative AI uses machine learning to generate new and original output for a given input.
Cloud Kicks wants to use an AI model 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?
Age
Reliability
Volume
What is a potential outcome of using poor-quality data in AI applications?
AI model training becomes slower and less efficient.
AI models become more interpretable.
AI models may produce biased or erroneous results.
A consultant conducts a series of Consequence Scanning Workshops to support testing diverse datasets. Which Salesforce Trusted AI Principle is being practiced?
Inclusivity
Transparency
Accountability
Which Einstein capability uses emails to create content for Knowledge articles?
Discover
Generate
Predict
What is a key challenge of human-AI collaboration in decision-making?
Reduces the need for human involvement in decision-making processes
Leads to more informed and balanced decision-making
Creates a reliance on Al, potentially leading to less critical thinking and oversight
What should be done to prevent bias from entering an Al system when training it?
Include proxy wvariables.
Import diverse training data.
Use alternative assumptions.
What is a key consideration regarding data quality in Al implementations?
Data's role in training and fine-tuning Salesforce Al models
Integration process of Al models with Salesforce workflows
Techniques for customizing Al features in Salesforce
How does a data quality assessment impact business outcomes for companies using AI?
Provides a benchmark for Al predictions
Improves the speed of Al recommendations
Accelerates the delivery of new AI solutions
Cloud Kicks uses Einstein to generate predictions but is not seeing accurate results. What is a potential reason for this?
The wrong product
Poor data guality
Too much data
What is machine learning?
Al AI that can grow its intelligence
AI that creates new content
A data model used in Salesforce
Which action should be taken to develop and implement trusted generative Al with Salesforce's safety guideline in mind?
Be transparent when Al has created and autonomousty delivered content.
Create guardrails that mitigate toxicity and protect PII.
Develop right-sized models to reduce our carben footprint.
What are the key components of the data quality standard?
Naming, Formatting, Monitoring
Reviewing, Updating, Archiving
Accuracy, Completeness, Consistency
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
A financial institution plans a campaign for preapproved credit cards. How should they implement Salesforce's Trusted AI Principle of Transparency?
Flag sensitive variables and their proxies to prevent discriminatory lending practices.
Incorporate customer feedback into the model's continuous training.
Communicate how risk factors such as credit score can impact customer eligibility.
Which statement exemplifies Salesforce's honesty guideline when training AI models?
Minimize the AI model's carbon footprint and environmental impact during training.
Ensure appropriate consent and transparency when using Al-generated responses,
Control bias, toxicity, and harmful content with embedded guardrails and guidance,
What is the role of Salesforce's Trusted Al Principles in the context of CRM systems?
Guiding ethical and responsible use of AL
Outlining the technical specifications for Al integration
Providing a framework for Al data model accuracy
What is a benefit of data quality and transparency as it pertains to bias in generative AI?
Chances of bias are aggravated.
Chances of bias are mitigated.
Chances of bias are removed.
What is an example of ethical debt?
Launching an Al feature after discovering a harmful bias
Delaying an Al product launch to retrain an AI data model
Violating a data privacy law and failing to pay fines
Which type of bias imposes a system’s values on others?
Automation
Societal
Association
A marketing manager wants to use Al to better engage their customers.
Which functionality provides the best solution?
Bring Your Own Model
Journey Optimization
Einstein Engagement
A business analyst (BA) wants to improve business by enhancing their sales processes and customer support. Which AI applications should the BA use to meet their needs?
Machine learning models and chatbet predictions
Sales data cleansing and customer support data governance
Lead scoring, opportunity forecasting, and case classification
