Renewal Salesforce Certified AI Associate Exam (SU23) Salesforce-AI-Associate Exam

NEW QUESTION 1
How is natural language processing (NLP) used in the context of AI capabilities?

• A. To cleanse and prepare data for AI implementations
• B. To interpret and understand programming language
• C. To understand and generate human language

Answer: C

Explanation:
“Natural language processing (NLP) is used in the context of AI capabilities to understand and generate human language. NLP can enable AI systems to interact with humans using natural language, such as speech or text. NLP can also enable AI systems to analyze and extract information from natural language data, such as documents, emails, or social media posts.”

NEW QUESTION 2
What should be done to prevent bias from entering an AI system when training it?

• A. Use alternative assumptions.
• B. Import diverse training data.
• C. Include Proxy variables.

Answer: B

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 and patterns 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 3
What is a potential source of bias in training data for AI models?

• A. The data is collected in area time from sources systems.
• B. The data is skewed toward is particular demographic or source.
• C. The data is collected from a diverse range of sources and demographics.

Answer: B

Explanation:
“A potential source of bias in training data for AI models is that the data is skewed toward a particular demographic or source. Skewed data means that the data is not balanced or representative of the target population or domain. Skewed data can introduce or exacerbate bias in AI models, as they may overfit or underfit the model to a specific subset of data. For example, skewed data can lead to bias if the data is collected from a limited or biased demographic or source, such as a certain age group, gender, race, location, or platform.”

NEW QUESTION 4
What is the rile of data quality in achieving AI business Objectives?

• A. Data quality is unnecessary because AI can work with all data types.
• B. Data quality is required to create accurate AI data insights.
• C. Data quality is important for maintain Ai data storage limits

Answer: B

Explanation:
“Data quality is required to create accurate AI data insights. Data quality is the degree to which data is accurate, complete, consistent, relevant, and timely for the AI task. Data quality can affect the performance and reliability of AI systems, as they depend on the quality of the data they use to learn from and make predictions. Data quality can also affect the accuracy and validity of AI data insights, as they reflect the quality of the data used or generated by AI systems.”

NEW QUESTION 5
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?

• A. Redesign the lead conversion process,
• B. Review and update missing lead information.
• C. Prioritize active leads quarterly.

Answer: B

Explanation:
To enhance the quality of lead data in their CRM system, the most effective process is to review and update missing lead information. This process involves identifying incomplete records and filling in missing details, which can significantly improve the accuracy and usefulness of lead data. Accurate and complete lead information is crucial for effective lead scoring, prioritization, and follow-up, enhancing overall sales performance. Salesforce CRM offers data quality tools and features that assist in regularly reviewing and maintaining the accuracy of lead data. Information on managing lead data quality in Salesforce can be found at Salesforce Lead Management.

NEW QUESTION 6
Which action introduces bias in the training data used for AI algorithms?

• A. Using a large dataset that is computationally expensive
• B. Using a dataset that represents diverse perspectives and populations
• C. Using a dataset that underrepresents perspectives and populations

Answer: C

Explanation:
Introducing bias in training data for AI algorithms occurs when the dataset used underrepresents certain perspectives and populations. This type of bias can skew AI predictions, making the system less fair and accurate. For example, if a dataset predominantly contains information from one demographic group, the AI's performance may not generalize well to other groups, leading to biased or unfair outcomes. Salesforce discusses the impact of biased training data and ways to mitigate this in their AI ethics guidelines, which can be explored further in the Salesforce AI documentation on Responsible Creation of AI.

NEW QUESTION 7
Which Einstein capability uses emails to create content for Knowledge articles?

• A. Generate
• B. Discover
• C. Predict

Answer: A

Explanation:
“Einstein Generate uses emails to create content for Knowledge articles. Einstein Generate is a natural language generation (NLG) feature that can automatically write summaries, descriptions, or recommendations based on data or text inputs. For example, Einstein Generate can analyze email conversations between agents and customers and generate draft articles for the Knowledge base.”

NEW QUESTION 8
A consultant conducts a series of Consequence Scanning workshops to support testing diverse datasets.
Which Salesforce Trusted AI Principles is being practiced>

• A. Transparency
• B. Inclusivity
• C. Accountability

Answer: B

Explanation:
“Conducting a series of Consequence Scanning workshops to support testing diverse datasets is an action that practices Salesforce’s Trusted AI Principle of Inclusivity. Inclusivity is one of the Trusted AI Principles that states that AI systems should be designed and developed with respect for diversity and inclusion of different perspectives, backgrounds, and experiences. Conducting Consequence Scanning workshops means engaging with various stakeholders to identify and assess the potential impacts and implications of AI systems on different groups or domains. Conducting Consequence Scanning workshops can help practice Inclusivity by ensuring that diverse datasets are used to test and evaluate AI systems.”

NEW QUESTION 9
What is the most likely impact that high-quality data will have on customer relationships?

• A. Increased brand loyalty
• B. Higher customer acquisition costs
• C. Improved customer trust and satisfaction

Answer: C

Explanation:
“The most likely impact that high-quality data will have on customer relationships is improved customer trust and satisfaction. High-quality data means that the data is accurate, complete, consistent, relevant, and timely for the AI task. High-quality data can improve customer relationships by enabling AI systems to provide personalized and relevant products, services, or solutions that meet the customers’ expectations, needs, and interests. High-quality data can also improve customer trust and satisfaction by reducing errors, delays, or waste in customer interactions.”

NEW QUESTION 10
What is an example of Salesforce's Trusted AI Principle of Inclusivity in practice?

• A. Testing models with diverse datasets
• B. Striving for model explain ability
• C. Working with human rights experts

Answer: A

Explanation:
“An example of Salesforce’s Trusted AI Principle of Inclusivity in practice is testing models with diverse datasets. Inclusivity means that AI systems should be designed and developed with respect for diversity and inclusion of different perspectives, backgrounds, and experiences. Testing models with diverse datasets can help ensure that the models are fair, unbiased, and representative of the target population or domain.”

NEW QUESTION 11
What should an organization do to enforce consistency across accounts for newly entered records?

• A. Merge all duplicate accounts into a single record when duplicate entries are detected.
• B. Input the data exactly as it appears from the source, such as the company’s website or social media,
• C. Implement naming conventions or a predefined list of user-selectable values for organization-wide records.

Answer: C

Explanation:
To ensure consistency across accounts for newly entered records, organizations should implement naming conventions or a predefined list of user-selectable values. This approach standardizes data entry, reducing variations and errors. It also helps in maintaining clean data which is essential for accurate reporting and analytics. Using standardized naming conventions ensures that all users adhere to a consistent format, making it easier to manage and analyze data across the organization. For more information on best practices for data management in Salesforce, refer to Salesforce's documentation on Data Management Best Practices.

NEW QUESTION 12
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?

• A. Enhanced accuracy and reliability of medical predictions and diagnoses
• B. Ensured compatibility of AI algorithms with the system's Infrastructure
• C. Reduced need for healthcare expertise in interpreting AI outouts

Answer: A

Explanation:
“Data quality plays a crucial role in enhancing the accuracy and reliability of medical predictions and diagnoses. Poor data quality can lead to inaccurate or misleading results, which can have serious consequences for patients’ health and well-being. Therefore, it is important to ensure that the data used for AI applications in healthcare is accurate, complete, consistent, and relevant.”

NEW QUESTION 13
Which statement exemplifies Salesforces honesty guideline when training AI models?

• A. Minimize the AI models carbon footprint and environment impact during training.
• B. Ensure appropriate consent and transparency when using AI-generated responses.
• C. Control bias, toxicity, and harmful content with embedded guardrails and guidance.

Answer: B

Explanation:
“Ensuring appropriate consent and transparency when using AI-generated responses is a statement that exemplifies Salesforce’s honesty guideline when training AI models. Salesforce’s honesty guideline is one of the Trusted AI Principles that states that AI systems should be designed and developed with respect for honesty and integrity in how they work and what they produce. Ensuring appropriate consent and transparency means respecting and honoring the choices and preferences of users regarding how their data is used or generated by AI systems. Ensuring appropriate consent and transparency also means providing clear and accurate information and documentation about the AI systems and their outputs.”

NEW QUESTION 14
What is a possible outcome of poor data quality?

• A. AI models maintain accuracy but have slower response times.
• B. Biases in data can be inadvertently learned and amplified by AI systems.
• C. AI predictions become more focused and less robust.

Answer: B

Explanation:
“A possible outcome of poor data quality is that biases in data can be inadvertently learned and amplified by AI systems. Poor data quality means that the data is inaccurate, incomplete, inconsistent, irrelevant, or outdated for the AI task. Poor data quality can affect the performance and reliability of AI systems, as they may not have enough or correct information to learn from or make accurate predictions. Poor data quality can also introduce or exacerbate biases in data, such as human bias, societal bias, or confirmation bias, which can affect the fairness and ethics of AI systems.”

NEW QUESTION 15
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. Create guardrails that mitigates toxicity and protect PII
• C. Be transparent when AI has created and automatically delivered content.

Answer: B

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 16
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?

• A. Ethical AI Prediction Maturity Model
• B. Ethical AI Process Maturity Model
• C. Ethical AI practice Maturity Model

Answer: B

Explanation:
“The Ethical AI Process Maturity Model is the established Salesforce Ethical Maturity Model that the Cloud technical team should use to guide the development of trusted AI solutions. The Ethical AI Process Maturity Model is a framework that helps assess and improve the ethical and responsible practices and processes involved in developing and deploying AI systems. The Ethical AI Process Maturity Model consists of five levels of maturity: Ad Hoc, Aware, Defined, Managed, and Optimized. The Ethical AI Process Maturity Model can help guide the development of trusted AI solutions by providing a roadmap and best practices for achieving higher levels of ethical maturity.”

NEW QUESTION 17
A sales manager wants to use AI to help sales representatives log their calls quicker and more accurately.
Which functionality provides the best solution?

• A. Call Summaries
• B. Sales Dialer
• C. Auto-Generated Sales Tasks

Answer: A

Explanation:
The best functionality to help sales representatives log their calls quicker and more accurately is the use of AI-generated Call Summaries. This feature leverages AI to analyze voice data from sales calls and automatically generate concise summaries and actionable insights, which are then logged into the CRM system. This not only speeds up the process of recording call details but also enhances the accuracy of the data captured, reducing the likelihood of human error and ensuring that important details are not missed. Salesforce provides AI tools that integrate with telephony solutions to enable these capabilities, enhancing the efficiency of sales operations. For more information on Salesforce AI features like Einstein Call Coaching that support this functionality, visit Salesforce Einstein Call Coaching.

NEW QUESTION 18
What is the best method to safeguard customer data privacy?

• A. Automatically anonymize all customer data.
• B. Track customer data consent preferences.
• C. Archive customer data on a recurring schedule.

Answer: B

Explanation:
“Tracking customer data consent preferences is the best method to safeguard customer data privacy. Data privacy is the right of individuals to control how their personal data is collected, used, shared, or stored by others. Tracking customer data consent preferences means respecting and honoring the choices and preferences of customers regarding their personal data. Tracking customer data consent preferences can help ensure compliance with data privacy laws and regulations, as well as build trust and loyalty with customers.”

NEW QUESTION 19
What can bias in AI algorithms in CRM lead to?

• A. Personalization and target marketing changes
• B. Advertising cost increases
• C. Ethical challenges in CRM systems

Answer: C

Explanation:
“Bias in AI algorithms in CRM can lead to ethical challenges in CRM systems. Bias means that AI algorithms favor or discriminate certain groups or outcomes based on irrelevant or unfair criteria. Bias can affect the fairness and ethics of CRM systems, as they may affect how customers are perceived, treated, or represented by AI algorithms. For example, bias can lead to ethical challenges in CRM systems if AI algorithms make inaccurate or harmful predictions or recommendations based on customers’ identity or characteristics.”

NEW QUESTION 20
Cloud Kicks uses Einstein to generate predictions out is not seeing accurate results? What to a potential mason for this?

• A. Poor data quality
• B. The wrong product
• C. Too much data

Answer: A

Explanation:
“Poor data quality is a potential reason for not seeing accurate results from an AI model. Poor data quality means that the data is inaccurate, incomplete, inconsistent, irrelevant, or outdated for the AI task. Poor data quality 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.”

NEW QUESTION 21
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