Latest Salesforce-AI-Associate Actual Free Exam Questions Updated 107 Questions
Free Salesforce-AI-Associate Exam Braindumps certification guide Q&A
Salesforce Salesforce-AI-Associate Exam Syllabus Topics:
| Topic | Details |
|---|---|
| Topic 1 |
|
| Topic 2 |
|
| Topic 3 |
|
| Topic 4 |
|
NEW QUESTION # 13
Which data does Salesforce automatically exclude from marketing Cloud Einstein engagement model training to mitigate bias and ethic...
- A. Cryptographic
- B. Geographic
- C. Geographic
Answer: C
Explanation:
"Demographic data is thedata that Salesforce automatically excludes from Marketing Cloud Einstein engagement model training to mitigate bias and ethical concerns. Demographic data is data that describes the characteristics of a population or a group of people, such as age, gender, race, ethnicity, income, education, or occupation. Demographic data can lead to bias if it is used to discriminate or treat people differently based on their identity or attributes. Demographic data can also reflect existing biases or stereotypes in society or culture, which can affect the fairness and ethics of AI systems. Salesforce excludes demographic data from Marketing Cloud Einstein engagement model training to mitigate bias and ethical concerns by ensuring that the models are based on behavioral data rather than personal data."
NEW QUESTION # 14
What is an example of Salesforce's Trusted AI Principle of Inclusivity in practice?
- A. Testing models with diverse datasets
- B. Working with human rights experts
- C. Striving for model explain ability
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 # 15
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?
- A. Remove biased data.
- B. Determine data outcomes.
- C. Determine data availability.
Answer: C
Explanation:
Explanation
Before using AI to optimize business operations, the company should first assess the availability and quality of its data. Data is the fuel for AI, and without sufficient and relevant data, AI cannot produce accurate and reliable results. Therefore, the company should identify what data it has, where it is stored, how it is accessed, and how it is maintained. This will help the company understand the feasibility and scope of its AI projects.
NEW QUESTION # 16
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. Auto-Generated Sales Tasks
- B. Call Summaries
- C. Sales Dialer
Answer: B
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 # 17
What is the best method to safeguard customer data privacy?
- A. Archive customer data on a recurring schedule.
- B. Automatically anonymize all customer data.
- C. Track customer data consent preferences.
Answer: C
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 preferencesof 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 # 18
What is a possible outcome of poor data quality?
- A. AI predictions become more focused and less robust.
- B. AI models maintain accuracy but have slower response times.
- C. Biases in data can be inadvertently learned and amplified by AI systems.
Answer: C
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 # 19
Which action should be taken to develop and implement trusted generated AI with Salesforce's safety guideline in mind?
- A. Be transparent when AI has created and automatically delivered content.
- B. Develop right-sized models to reduce our carbon footprint.
- C. Create guardrails that mitigates toxicity and protect PII
Answer: C
Explanation:
"Creating guardrails that mitigate toxicity and protect PII is an action that should be taken to develop and implement trusted generativeAI 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. Creatingguardrails 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 AIsystems. Creating guardrails can also help protect PII by masking or anonymizing personal or sensitive information generated by AI systems."
NEW QUESTION # 20
What is the main focus of the Accountability principle in Salesforce's Trusted AI Principles?
- A. Taking responsibility for one's actions toward customers, partners, and society
- B. Safeguarding fundamental human rights and protecting sensitive data
- C. Ensuring transparency In Al-driven recommendations and predictions
Answer: A
Explanation:
"The main focus of the Accountability principle in Salesforce's Trusted AI Principles is taking responsibility for one's actions toward customers,partners, and society. Accountability means that AI systems should be designed and developed with respect for the impact and consequences of their actions on others.
Accountability also means that AI developers and users should be aware of and adhere to the ethical, legal, and regulatory standards and expectations of their industry and domain."
NEW QUESTION # 21
What is the significance of explainability of trusted AI systems?
- A. Enhances the security and accuracy of AI models
- B. Describes how Al models make decisions
- C. Increases the complexity of AI models
Answer: B
Explanation:
The significance of the explainability of trusted AI systems is that it describes how AI models make decisions.
Explainability is crucial for building trust and accountability in AI systems, ensuring that users and stakeholders understand the decision-making processes and outcomes generated by AI. This is particularly important in scenarios where AI decisions impact personal or financial status, such as in credit scoring or healthcare diagnostics. Salesforce emphasizes the importance of explainable AI through its ethical AI practices, aiming to make AI systems more transparent and understandable. More details about Salesforce's approach to ethical and explainable AI can be found in Salesforce AI ethics resources at Salesforce AI Ethics.
NEW QUESTION # 22
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?
- A. Sales data cleansing and customer support data governance
- B. Machine learning models and chatbot predictions
- C. Lead scoring, opportunity forecasting, and case classification
Answer: C
Explanation:
"Lead scoring, opportunity forecasting, and case classification are AI applications that can help abusiness analyst improve their sales processes and customer support. Lead scoring can help prioritize leads based on their likelihood to convert, opportunity forecasting can help predict future sales or revenue based on historical data and trends, and caseclassification can help categorize and route cases based on their attributes."
NEW QUESTION # 23
Cloud Kicks is testing a new AI model.
Which approach aligns with Salesforce's Trusted AI Principle of Incluslvity?
- A. Rely on a development team with uniform backgrounds to assess the potential societal implications of the model.
- B. Test only with data from a specific region or demographic to limit the risk of data leaks.
- C. Test with diverse and representative datasets appropriate for how the model will be used.
Answer: C
Explanation:
"Testing with diverse and representative datasets appropriate for how the model will be used aligns with Salesforce's Trusted AI Principle of Inclusivity. Inclusivity means that AI systems should be designed and developed with respect for diversity and inclusion of different perspectives, backgrounds, and experiences.
Testing with diverse and representative datasets can help ensure that the models are fair, unbiased, and representative of the target population or domain."
NEW QUESTION # 24
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?
- A. Consistency
- B. Accuracy
- C. Completeness
Answer: A
Explanation:
Explanation
"Consistency is the dimension of data quality that is affected in this scenario. Consistency means that the data values are uniform and follow a common standard or format across different records, fields, or sources.
Inconsistent data can cause confusion, errors, or duplication in data analysis andprocessing. For example, using different field types for the same attribute can affect the consistency of the data."
NEW QUESTION # 25
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?
- A. Consistency
- B. Age
- C. Duplication
Answer: A
Explanation:
Explanation
"Consistency is the data quality dimension that is essential for creating a custom service analytics application to analyze cases in Salesforce. Consistency means that the data values are uniform and follow a common standard or format across different records, fields, or sources. Consistent data can ensure that the custom application can accurately and efficiently analyze cases and provide meaningful insights."
NEW QUESTION # 26
What are the key components of the data quality standard?
- A. Accuracy, Completeness, Consistency
- B. Naming, formatting, Monitoring
- C. Reviewing, Updating, Archiving
Answer: A
Explanation:
"Accuracy, Completeness, Consistency are the key components of the data quality standard. Data quality standard is a set of criteria or measures that define and evaluate the quality of data for a specific purpose or task. Data quality standard can vary by industry, domain, or application, but some common components are accuracy, completeness, and consistency. Accuracy means that the data values are correct andvalid for the data attribute. Completeness means that the data values are not missing any relevant information for the data attribute. Consistency means that the data values are uniform and follow a common standard or format across different records, fields, or sources."
NEW QUESTION # 27
What is the key difference between generative and predictive AI?
- A. Generative AI creates new content based on existing data and predictive AI analyzes existing data.
- B. Generative AI analyzes existing data and predictive AI creates new content based on existing data.
- C. Generative AI finds content similar to existing data and predictive AI analyzes existing data.
Answer: A
Explanation:
"The key difference between generative and predictive AI is that generative AI creates new content based on existing data and predictive AI analyzes existing data.Generative AI is a type of AI that can generate novel content such as images, text, music, or video based on existing data or inputs. Predictive AI is a type of AI that can analyze existing data or inputs and make predictions or recommendations based on patterns or trends."
NEW QUESTION # 28
What is a benefit of a diverse, balanced, and large dataset?
- A. Training time
- B. Data privacy
- C. Model accuracy
Answer: C
Explanation:
Explanation
"Model accuracy is a benefit of a diverse, balanced, and large dataset. A diverse dataset can capture a variety of features and patterns that are relevant for the AI task. A balanced dataset can avoid overfitting or underfitting the model to a specific subset of data. A large dataset can provide enough information for the model to learn from and generalize well to new data."
NEW QUESTION # 29
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. Accountability
- C. Inclusivity
Answer: C
Explanation:
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 # 30
......
Salesforce-AI-Associate Certification Overview Latest Salesforce-AI-Associate PDF Dumps: https://www.lead1pass.com/Salesforce/Salesforce-AI-Associate-practice-exam-dumps.html
Top Salesforce Salesforce-AI-Associate Exam Audio Study Guide! Practice Questions Edition: https://drive.google.com/open?id=1xnqIaF-xF9Yr72dZPV84xPUzUQXL1Ueg