Salesforce Trusted AI Principles Quiz & Flashcards

Questions and Answers

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. (correct)

Prioritize model fine-tuning over data quality improvements.

Cloud Kicks discovered multiple variations of state and country values in contact records. Which data quality dimension is affected by this issue?

Accuracy

Consistency (correct)

Usage

What is a sensitive variable that can lead to bias?

Education level

Country

Gender (correct)

What type of bias results from data being labeled according to stereotypes?

Association Signup and view all the answers

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

Model accuracy Signup and view all the answers

What is a crucial factor a developer should consider when selecting a dataset for training an AI model?

Age of dataset Signup and view all the answers

What is an implication of user consent in regard to AI data privacy?

AI infringes on privacy when user consent is not obtained. Signup and view all the answers

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

Consent Signup and view all the answers

Which feature should Cloud Kicks use to remove multiple records for the same customer?

Duplicate management Signup and view all the answers

What data quality dimension is affected when employees use different methods to capture product category?

Consistency Signup and view all the answers

What is a key benefit of effective interaction between humans and AI systems?

Leads to more informed and balanced decision-making Signup and view all the answers

How does data quality impact the trustworthiness of AI-driven decisions?

High-quality data improves the reliability and credibility of AI-driven decisions, fostering trust among users. Signup and view all the answers

Which type of bias is most likely to be encountered when recommending products based on historical purchase data?

Societal Signup and view all the answers

Which Einstein capability uses emails to create content for Knowledge articles?

Discover Signup and view all the answers

What is financial status?

An immutable trait that includes attributes like income level, wealth, or financial stability. Signup and view all the answers

Which approach aligns with Salesforce's Trusted AI Principle of Inclusivity?

Test with diverse and representative datasets appropriate for how the model will be used. Signup and view all the answers

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 developed. Signup and view all the answers

How can Cloudy Computing enhance its AI practices while adhering to Salesforce's Trusted AI Principles?

Soliciting independent feedback from external ethics experts, customers, and advisory boards. Signup and view all the answers

Which well-established Salesforce model should guide the creation of reliable AI solutions?

Ethical AI Practice Maturity Model. Signup and view all the answers

Which Salesforce Trusted AI Principle highlights the significance of designing AI models to reduce bias for everyone potentially affected?

Inclusiveness Signup and view all the answers

When should the use of natural language processing (NLP) for automated customer service be disclosed to the customer?

At the outset of their conversation with AI. Signup and view all the answers

How should a financial institution adhere to Salesforce's Trusted AI Principle of Transparency when executing a campaign for preapproved credit cards?

Clarify how risk factors like credit score may influence customer eligibility. Signup and view all the answers

What action should Cloudy Computing take when faced with irregularities in a dataset for an AI model?

Investigate the data inconsistencies and implement data quality methods. Signup and view all the answers

What is a fundamental element of a data management strategy?

Naming conventions Signup and view all the answers

Which data quality aspect should be employed to assess future dates of birth identified in a data quality evaluation?

Validity Signup and view all the answers

What does 'data completeness' mean when discussing data quality?

The extent to which all necessary data points exist within the dataset. Signup and view all the answers

Which aspect ensures accurate data for a custom service analytics application analyzing cases in Salesforce?

Consistency Signup and view all the answers

What is the most likely process to assist a team in improving the quality of lead data in their CRM system?

Review and update missing lead information Signup and view all the answers

Which Salesforce field type should an administrator use to capture a customer's preferred name?

Text Signup and view all the answers

How does data quality influence the ethical use of AI applications?

Good data quality is crucial to guarantee impartial and equitable AI decisions, uphold ethical standards, and prevent discrimination. Signup and view all the answers

What is the expected outcome of high-quality data on customer relationships?

Improved customer trust and satisfaction. Signup and view all the answers

What advantage does a diverse, well-rounded, and extensive dataset offer in AI?

Model precision. Signup and view all the answers

What should Cloudy Computing do first to prepare its data for use with AI?

Determine data availability. Signup and view all the answers

What could be a potential result of inadequate data quality?

Unintentional reinforcement of biases in AI systems due to flawed data. Signup and view all the answers

Which field type should a Salesforce administrator use to capture an order's destination country to ensure data quality?

Picklist Signup and view all the answers

How does the 'right of least privilege' reduce the risk of handling sensitive personal data?

By limiting how many people have access to data. Signup and view all the answers

What is one way to achieve transparency in AI?

Communicate AI goals and objectives with those involved prior to all interactions. Signup and view all the answers

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. Signup and view all the answers

What is an example of Salesforce's Trusted AI Principle of Inclusivity in practice?

Testing models with diverse datasets. Signup and view all the answers

How will the incomplete data quality impact the company's operations?

The accuracy of product recommendations is hindered. Signup and view all the answers

Which primary role does data quality play in a healthcare company's AI application?

Enhanced accuracy and reliability of medical predictions and diagnoses Signup and view all the answers

What can happen if an organization experiences low data quality?

Loss of revenue, diminished customer service, and damage to reputation Signup and view all the answers

What is the possible outcome of poor data quality?

Biases in data can be inadvertently learned and amplified by AI systems. Signup and view all the answers

Which data quality dimension is crucial for forecasting shoe demand based on historical sales data?

Age Signup and view all the answers

Which fundamental data quality aspect should a developer prioritize to guarantee the efficiency of their AI models?

Consistency Signup and view all the answers

What data quality aspect should Cloudy Computing prioritize to enhance the predictive accuracy of its AI model?

Accuracy Signup and view all the answers

What data quality aspect is confirmed by assessing null values?

Completeness Signup and view all the answers

Which area of AI is best suited for deploying a chatbot to handle common queries?

Natural language processing Signup and view all the answers

Which type of AI focuses on very specific tasks?

Narrow AI Signup and view all the answers

What kind of AI employs machine learning to generate fresh and unique output based on a provided input?

Generative Signup and view all the answers

How does an organization benefit from using AI to personalize the shopping experience of online customers?

Customers are more likely to be satisfied with their shopping experience. Signup and view all the answers

What are three frequently employed examples of AI in CRM?

Predictive scoring, forecasting, recommendations Signup and view all the answers

What AI tools could the business analyst employ to address their requirements?

Lead Scoring, Opportunity forecasting, and Case Classification Signup and view all the answers

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

Various AI applications applicable in Salesforce Signup and view all the answers

What is a key characteristic of machine learning in the context of AI capabilities?

Utilizes algorithms to learn from data and make decisions Signup and view all the answers

What are some significant advantages of AI in enhancing customer experiences within CRM?

Improves case handling by organizing and monitoring customer support issues, recognizing subjects, and summarizing case solutions Signup and view all the answers

What are some key benefits of AI in improving customer experiences in CRM?

Streamlines case management by categorizing and tracking customer support cases, identifying topics, and summarizing case resolutions Signup and view all the answers

In the realm of AI capabilities, what is the primary function of computer vision?

Analyzing and comprehending visual information Signup and view all the answers

How can AI increase customer email engagement for Cloudy Computing's email campaign?

Create personalized emails Signup and view all the answers

What constitutes the foundational components of AI systems?

Algorithms, data, and computational resources Signup and view all the answers

What AI application would offer the greatest benefits for a sales manager looking to improve Salesforce operations?

Prioritizing leads and predicting sales opportunities Signup and view all the answers

What is the involvement of humans in AI-powered CRM procedures?

Humans have a crucial role in supervising AI-powered CRM processes, adding context, and making ultimate decisions Signup and view all the answers

To avoid introducing unintended bias to an AI model, which type of data should be omitted?

Demographic Signup and view all the answers

Which Einstein feature offers the most suitable solution for a service leader planning to use AI for customer queries?

Automated Chatbots Signup and view all the answers

Which functionality provides the best solution for a marketing manager wanting to engage better with customers?

Journey Optimization Signup and view all the answers

What is the best method to safeguard customer data privacy?

Track customer data consent preferences. Signup and view all the answers

Which features of Einstein enhance sales efficiency and effectiveness?

Opportunity Scoring, Lead Scoring, Account Insights Signup and view all the answers

What step should be followed to build and apply reliable generative AI while considering Salesforce's safety guidelines?

Establish safeguards to mitigate harmful content and safeguard Personally Identifiable Information (PII) Signup and view all the answers

Which capability should Cloudy Computing use to enhance its sales processes and customer support?

Einstein Lead Scoring and Case Classification Signup and view all the answers

Which statement best reflects Salesforce's commitment to honesty in training AI models?

Guarantee proper consent and transparency when employing AI-generated responses Signup and view all the answers

What constitutes an instance of ethical debt?

Introducing an AI feature after identifying a detrimental bias Signup and view all the answers

In what way does AI aid in the process of lead qualification?

Evaluates leads using customer information Signup and view all the answers

What data does Salesforce automatically remove from Marketing Cloud Einstein engagement model training to reduce bias and ethical risks?

Demographic Signup and view all the answers

What should be the consultant's top priority when discussing the ethical aspects of data management?

Privacy, bias, compliance, and security Signup and view all the answers

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 Signup and view all the answers

What is the term for bias that imposes the values of a system onto others?

Automation Signup and view all the answers

Which potentially sensitive attribute is an example of an immutable trait?

Financial status Signup and view all the answers

What could be a origin of bias in the training data used for AI models?

The data primarily comes from a specific demographic or source Signup and view all the answers

What is the significance of data protection measures in AI usage?

Safeguards privacy and compliance Signup and view all the answers

Why is the explainability of trusted AI systems important?

Clarifies how AI models reach decisions Signup and view all the answers

What action leads to bias in the training data for AI algorithms?

Employing a dataset that lacks representation from various perspectives and populations Signup and view all the answers

Why is it vital to address privacy issues when handling AI and CRM data?

Guarantees adherence to laws and regulations Signup and view all the answers

What represents a significant obstacle in human-AI cooperation in decision-making?

Encourages dependence on AI, possibly reducing critical thinking and supervision Signup and view all the answers

Can you provide an instance of successful cooperation between humans and AI systems?

Humans and AI collaborate to make well-informed decisions Signup and view all the answers

What is a method for reducing bias and promoting fairness in AI applications?

Continuously auditing and monitoring the data used in AI applications Signup and view all the answers

What purpose do Salesforce's Trusted AI Principles serve within CRM systems?

Guiding the ethical and responsible utilization of AI Signup and view all the answers

What should Cloud Kicks consider doing to minimize potential AI bias?

Implement Salesforce's Trusted AI Principles Signup and view all the answers

Regarding Salesforce's Trusted AI Principles, what is the main emphasis of the Responsibility principle?

Guaranteeing ethical AI usage Signup and view all the answers

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 Signup and view all the answers

What does Salesforce's Trusted AI Principle of Transparency entail?

Providing a clear and comprehensible explanation of AI decisions and actions Signup and view all the answers

Within Salesforce's Trusted AI Principles, what is the primary goal of the Empowerment principle?

Enable users of varying skill levels to create AI applications through user-friendly interfaces, without needing to write code Signup and view all the answers

What is a fundamental aspect to think about when it comes to data quality in AI implementations?

The role of data in training and refining Salesforce AI models Signup and view all the answers

What role does data quality play in accomplishing AI business goals?

Data quality is essential for generating precise AI data insights Signup and view all the answers

What effect does a data quality evaluation have on business results for companies utilizing AI?

Establishes a baseline for AI predictions Signup and view all the answers

What could be a possible explanation for inaccuracies experienced by Cloudy Computing while using Einstein for generating predictions?

Low data quality Signup and view all the answers

What might be a potential explanation for a company with a high data quality score not experiencing the advantages of AI?

The data score might exceed the minimum threshold, but the company isn't using it as a reference for future outcomes Signup and view all the answers

How does data quality and transparency impact bias in generative AI?

It reduces the likelihood of bias Signup and view all the answers

Study Notes

AI Applications for Business Analysts

Business analysts can enhance sales and customer support using AI applications like Lead Scoring, Opportunity forecasting, and Case Classification.
These tools provide data-driven insights, automate tasks, and improve overall decision-making.

Characteristics of Machine Learning

Machine learning utilizes algorithms to learn from data, enabling it to make informed decisions rather than relying on preprogrammed rules.

Function of Computer Vision

Computer vision focuses on analyzing and interpreting visual information, helping AI systems understand visual data.

Foundational Components of AI

AI systems consist of algorithms, data, and computational resources, which are essential for effectively training and executing AI models.

AI in Salesforce Operations

Prioritizing leads and predicting sales opportunities through AI applications significantly benefits sales managers.

AI for Customer Support

Automated chatbots enhance self-service applications by engaging with customers and providing real-time solutions to queries.

AI in Marketing Engagement

Journey Optimization allows marketing managers to tailor, test, and enhance personalized campaign strategies using predictive AI within Salesforce Marketing Cloud.

Enhancing Sales Efficiency

Features like Opportunity Scoring, Lead Scoring, and Account Insights within Einstein contribute to improved efficiency and effectiveness in sales efforts.

AI Capabilities for Sales and Support

Einstein Lead Scoring improves sales processes, while Case Classification enhances customer support efficiency.

AI in Lead Qualification

AI analyzes customer data and evaluates leads, streamlining the qualification process by prioritizing those most likely to convert.

Ethical Concerns in AI

Crucial ethical aspects in AI data management include privacy, bias, compliance, and security to ensure responsible usage.

Automation Bias

This bias occurs when an AI system imposes its values on others, exemplified by biased outcomes in decision-making scenarios.

Sources of Training Data Bias

Bias can emerge from training data that is derived predominantly from a single demographic or source, affecting model performance.

Importance of Data Protection

Implementing data protection measures safeguards privacy and ensures compliance with legal standards.

Explainability in AI Models

Explainability is vital for understanding AI decision-making processes, enhancing trust in AI systems.

Addressing Bias in AI Models

Continuously auditing and monitoring data used in AI applications is essential in reducing bias and promoting fairness.

Salesforce's Trusted AI Principles

These principles guide the ethical use of AI, emphasizing responsibility, accountability, transparency, empowerment, and inclusivity.

Addressing AI Bias and Ethical Concerns

Implementing Salesforce's Trusted AI Principles helps minimize bias and ethical issues in AI applications, ensuring responsible AI deployment.

Responsibility in AI Utilization

The Responsibility principle ensures ethical and accountable usage of AI across systems and applications.

Accountability in AI Operations

Accountability within Salesforce's AI Principles emphasizes personal responsibility towards stakeholders in AI decision-making.

Transparency in AI Decisions

This principle advocates for clear explanations regarding AI decision-making processes to enhance understanding and trust.

Empowerment through AI

The Empowerment principle focuses on enabling users of all skill levels to create AI applications easily without coding.

Data Quality's Role in AI

High data quality is crucial for AI training, significantly affecting predictions and the effectiveness of AI models.

Impact of Data Quality on Business Goals

Ensuring high-quality data is essential for accurate AI insights, critical for achieving business objectives.

Evaluating Data Quality

Regular data quality evaluations establish baselines for AI predictions, aiding in improving outcomes.

Data Quality and AI Predictions

Low data quality leads to inaccurate AI predictions, emphasizing the need for reliable data sources.

Understanding the Benefits of High Data Quality

Even with a high data quality score, organizations must utilize it as a reference for future outcomes to realize the benefits of AI.

Data Quality and Bias Reduction

Ensuring high data quality and transparency helps reduce bias in generative AI, although it may not eliminate it entirely.

Incomplete Data Impact on Business Operations

Incomplete customer records hinder accurate product recommendations, impacting customer satisfaction and business operations.

Data Quality in Healthcare AI

High data quality enhances the accuracy and reliability of medical predictions, critical for effective patient care and treatment.### Data Quality in AI Applications
Data quality significantly enhances the accuracy and reliability of medical predictions and diagnoses in AI applications.
Poor data quality can cause loss of revenue, decreased customer service, and reputational damage.

Consequences of Low Data Quality

Inaccurate or incomplete data leads to operational errors and financial losses.
Poor data affects customer service through delays and misinformation, damaging trust and relationships.

Impacts on AI Predictions

Poor data quality can cause AI systems to learn and amplify biases, making outputs unreliable.
The significance of data accuracy directly influences the effectiveness of AI models in making predictions.

Importance of Various Data Quality Dimensions

Age is crucial for forecasting shoe demand, highlighting the importance of timely and relevant data.
Consistency is fundamental, ensuring data across various systems aligns for effective AI performance.
Accuracy is essential for high-quality data, which leads to precise AI model predictions.

Data Quality Aspects in AI Use Cases

Completeness: Assessing null values in data attributes reflects the need for comprehensive datasets.
Natural Language Processing is fundamental for chatbots to understand customer queries efficiently.

Types of AI

Neural Networks: Interconnected nodes mimicking human brain functions, used for pattern recognition and data learning.
Narrow AI: Specializes in specific tasks, in contrast to general AI, which aims for broader capabilities.
Generative AI: Utilizes machine learning to create unique outputs from existing input data.

Enhancing Customer Experience with AI

Personalizing online customer experiences through AI increases satisfaction and boosts loyalty and conversion rates.
Utilized in CRM, AI applications improve predictive scoring, forecasting, and recommendations.

Ethical Considerations in AI Development

Tracking customer data consent preferences is vital for ensuring data privacy and compliance.
Omitting demographic data reduces the risk of bias and aligns with inclusive principles in AI development.