AI in Salesforce and Trusted Principles
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Which customer information should be accessible on the Salesforce Platform for transparency regarding predictions made by Prediction Builder?

  • 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 was created (correct)
  • A detailed user manual of the Prediction Builder features and functions
  • A marketing article of the product that clearly outlines the product’s capabilities and features

    • Which Salesforce field type is most appropriate for capturing a customer’s preferred name?

  • Rich Text Area
  • Multi-Select Picklist
  • Text (correct)
  • Checkbox

    • What type of bias occurs when data is labeled based on stereotypes?

  • Interaction
  • Societal (correct)
  • Association
  • Cultural

    • Which attribute is classified as an example of an immutable trait?

    <p>Financial status</p> Signup and view all the answers

    What distinguishes generative AI from predictive AI?

    <p>Generative AI creates new content based on existing data while predictive AI analyzes existing data</p> Signup and view all the answers

    What is a potential outcome of maintaining poor data quality in AI models?

    <p>Biases in data may be learned and amplified by AI systems</p> Signup and view all the answers

    Which field type should a Salesforce administrator select to capture an order's destination country while ensuring data quality?

    <p>Picklist</p> Signup and view all the answers

    What does user consent imply regarding AI data privacy?

    <p>AI infringes on privacy when user consent is not obtained</p> Signup and view all the answers

    What is an essential data quality dimension for predicting shoe demand based on historical sales data?

    <p>Reliability</p> Signup and view all the answers

    How can a financial institution implement Salesforce's Trusted AI Principle of Transparency?

    <p>Communicate how risk factors such as credit score can impact customer eligibility.</p> Signup and view all the answers

    What is a key challenge of human-AI collaboration in decision-making?

    <p>Creates a reliance on AI, potentially leading to less critical thinking and oversight.</p> Signup and view all the answers

    Which statement best describes the difference between predictive AI and generative AI?

    <p>Predictive AI predicts outputs, while generative AI creates original outputs.</p> Signup and view all the answers

    What best defines machine learning?

    <p>AI that improves its own capabilities through experience.</p> Signup and view all the answers

    Which Salesforce Ethical Maturity Model should the Cloud Kicks team use to develop trusted AI solutions?

    <p>Ethical AI Practice Maturity Model</p> Signup and view all the answers

    What is a potential source of bias in training data for AI models?

    <p>The data is outdated and not representative of current trends.</p> Signup and view all the answers

    What is one of the goals of empowering users to build AI applications?

    <p>To enable users of all skill levels to create AI applications easily.</p> Signup and view all the answers

    Which data quality dimension should be assessed to reduce communication inefficiencies?

    <p>Duplication</p> Signup and view all the answers

    What is a potential outcome of using poor-quality data in AI applications?

    <p>AI models may produce biased or erroneous results.</p> Signup and view all the answers

    What role does data quality play in the ethical use of AI applications?

    <p>High-quality data is essential for ensuring unbiased and fair AI decisions.</p> Signup and view all the answers

    Which field of AI is most suitable for implementing a chatbot to deflect incoming customer inquiries?

    <p>Natural language processing</p> Signup and view all the answers

    What data does Salesforce automatically exclude from Marketing Cloud Einstein engagement model training to mitigate bias?

    <p>Demographic</p> Signup and view all the answers

    Which statement exemplifies Salesforce's honesty guideline when training AI models?

    <p>Ensure appropriate consent and transparency.</p> Signup and view all the answers

    What are some of the ethical challenges associated with AI development?

    <p>Potential for human bias in machine learning algorithms.</p> Signup and view all the answers

    What is one way to achieve transparency in AI?

    <p>Allow users to give feedback on AI inferences.</p> Signup and view all the answers

    What should a company prioritize first when preparing its data for AI?

    <p>Determine data availability</p> Signup and view all the answers

    In the scenario of Cloud Kicks recommending shoes based on purchase history, what type of bias is most likely encountered?

    <p>Confirmation</p> Signup and view all the answers

    What is a key characteristic of machine learning within AI capabilities?

    <p>It uses algorithms to learn from data and make decisions</p> Signup and view all the answers

    Which of the following is a commonly used example of AI in customer relationship management (CRM)?

    <p>Predictive scoring, forecasting, recommendations</p> Signup and view all the answers

    How does testing with diverse and representative datasets align with inclusivity in AI development?

    <p>It reduces the likelihood of biased outcomes</p> Signup and view all the answers

    How will incomplete data quality impact Cloud Kicks' product recommendations?

    <p>The accuracy of product recommendations is hindered</p> Signup and view all the answers

    What method can quickly assess data quality for Einstein Prediction Builder?

    <p>Run reports to explore the data quality</p> Signup and view all the answers

    Which type of AI can enhance customer service agents' email responses by analyzing the written content of previous emails?

    <p>Natural language processing</p> Signup and view all the answers

    What is a benefit of a diverse, balanced, and large dataset?

    <p>Model accuracy</p> Signup and view all the answers

    What are predictive analytics, machine learning, natural language processing (NLP), and computer vision?

    <p>Different types of AI that can be applied in Salesforce</p> Signup and view all the answers

    What is one technique to mitigate bias and ensure fairness in AI applications?

    <p>Ongoing auditing and monitoring of data that is used in AI applications</p> Signup and view all the answers

    Which Einstein feature should Cloud Kicks use for automated chat as its primary support channel?

    <p>Bots</p> Signup and view all the answers

    In the context of Salesforce's Trusted AI Principles, what does the principle of Responsibility primarily focus on?

    <p>Ensuring ethical use of AI</p> Signup and view all the answers

    What are the potential consequences of an organization suffering from poor data quality?

    <p>Revenue loss, poor customer service, and reputational damage</p> Signup and view all the answers

    Which type of records negatively impact data quality?

    <p>Duplicate</p> Signup and view all the answers

    Study Notes

    AI in Salesforce

    • Empower users at all skill levels to develop AI applications without writing code.
    • Use AI models to predict shoe demand based on sales and regional data.
    • Ensure data is reliable for accurate predictions.
    • Communicate how factors like credit scores impact customers.
    • Flag sensitive variables to avoid biased lending practices.

    Trusted AI Principles

    • Transparency: Explain how a model works and communicate its rationale.
    • Fairness: Ensure unbiased decisions and avoid discrimination.
    • Accountability: Ensure responsible use of AI.

    AI Challenges and Considerations

    • AI reliance may decrease human critical thinking and oversight.
    • Predictive AI: Analyzes data to predict outcomes.
    • Generative AI: Generates new output based on data.
    • Machine Learning: AI that learns from data and improves over time.

    Ethical AI Maturity Model

    • Ethical AI Process Maturity Model: Use this framework to guide the development of trusted AI solutions.

    Data Quality and Bias in AI

    • Bias: Training data may reflect existing societal biases.
    • Data Quality: Data quality impacts AI model accuracy, fairness, and performance.
    • Using low-quality data can result in biased results.
    • High-quality data promotes unbiased decisions and prevents discrimination.

    AI Applications in Salesforce

    • Use NLP to build chatbots that answer common customer questions.
    • Salesforce automatically excludes sensitive demographic data from AI model training.

    Building Ethical AI Models

    • Use safeguards to prevent biased content.
    • Ensure consent and transparency when using generated responses.
    • Minimize the model’s environmental impact during training.

    AI Transparency

    • Transparency: Provide explanations for AI predictions to users.
    • Fairness: Train AI models using diverse datasets.

    Understanding AI Concepts

    • Predictive AI: Analyzes existing data to predict outcomes.
    • Generative AI: Creates new content based on existing data.

    Data Fields in Salesforce

    • Use the Text field type for capturing preferred names on customer records.

    Bias in AI Training Data

    • Societal Bias: Stems from data labeled according to stereotypes.

    Immutable Traits and Data Privacy

    • Immutable Traits: Avoid using immutable traits unnecessarily in AI applications, such as financial status.
    • Poor data quality can lead to AI systems learning and amplifying bias.

    Data Types in Salesforce

    • Use the Picklist field type to ensure data quality when capturing order destination countries.
    • User consent is crucial for responsible AI use.

    Preparing Data for AI Implementations

    • Step 1: Determine data availability.
    • Step 2: Assess data quality.

    Bias in Recommendation Engines

    • Confirmation Bias: Recommendations may reinforce existing customer preferences.

    AI Capabilities

    • Machine Learning: Uses algorithms to learn from data and make decisions.
    • Natural Language Processing (NLP): Processes and understands human language.

    AI Applications in CRM

    • Predictive Scoring: Predict customer behavior.
    • Forecasting: Predict sales and demand.
    • Recommendations: Generate personalized product recommendations.

    Building Inclusive AI Solutions

    • Test AI models with diverse datasets to ensure inclusivity.

    Impacts of Data Quality

    • Incomplete data can hinder the accuracy of product recommendations.

    Assessing Data Quality

    • Use reports to quickly assess data quality.

    AI in Customer Service

    • Use NLP to personalize email responses for customers.

    AI Datasets

    • Large, diverse, and balanced datasets improve model accuracy.

    Understanding AI Concepts

    • Predictive Analytics: Analyze data to predict future events.
    • Machine Learning: AI that learns from data and improves over time.
    • Natural Language Processing (NLP): Processes and understands human language.
    • Computer Vision: Enables AI to interpret and analyze visual data.

    Mitigating Bias in AI

    • Auditing and Monitoring: Monitor AI systems for bias.

    Salesforce AI Features

    • Einstein Bots: Implement automated chat features.

    AI Responsibility

    • Responsibility: Ensure ethical AI use.

    Consequences of Poor Data Quality

    • Poor data quality can result in revenue loss, poor customer service, and reputational damage.

    AI for Customer Engagement

    • Personalized Emails: Use AI to personalize email campaigns for better engagement.

    Data Quality Issues

    • Duplicate Records: Duplicate records negatively impact data quality.

    Data Quality for AI Effectiveness

    • Consistency: Ensure data is consistent across all systems.

    Preparing Data for AI Models

    • Standardize Data: Standardize data to improve the effectiveness of AI models.

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    Related Documents

    Salesforce Certified AI Associate - Question Set.pdf

    Description

    Explore the integration of AI in Salesforce to predict outcomes and enhance user capabilities without coding. Understand the principles of transparency, fairness, and accountability in AI applications and the importance of ethical considerations in predictive and generative AI models.

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