[Dec 27, 2023] Get New Salesforce-AI-Associate Practice Test Questions Answers
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NEW QUESTION # 40
Which data does Salesforce automatically exclude from marketing Cloud Einstein engagement model training to mitigate bias and ethic...
- A. Geographic
- B. Geographic
- C. Cryptographic
Answer: A
Explanation:
Explanation
"Demographic data is the data 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 # 41
What are the key components of the data quality standard?
- A. Reviewing, Updating, Archiving
- B. Naming, formatting, Monitoring
- C. Accuracy, Completeness, Consistency
Answer: C
Explanation:
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 and valid 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 # 42
How does a data quality assessment impact business outcome for companies using AI?
- A. Accelerates the delivery of new AI solutions
- B. Provides a benchmark for AI predictions
- C. Improves the speed of AI recommendations
Answer: B
Explanation:
Explanation
"A data quality assessment impacts business outcomes for companies using AI by providing a benchmark for AI predictions. A data quality assessment is a process that measures and evaluates the quality of data for a specific purpose or task. A data quality assessment can help identify and address any issues or gaps in the data quality dimensions, such as accuracy, completeness, consistency, relevance, and timeliness. A data quality assessment can impact business outcomes for companies using AI by providing a benchmark for AI predictions, as it can help ensure that the predictions are based on high-quality data that reflects the true state or condition of the target population or domain."
NEW QUESTION # 43
What is a key benefit of effective interaction between humans and AI systems?
- A. Alerts humans to the presence of biased data
- B. Leads to more informed and balanced decision making
- C. Reduces the need for human involvement
Answer: B
Explanation:
Explanation
"A key benefit of effective interaction between humans and AI systems is that it leads to more informed and balanced decision making. Effective interaction means that humans and AI systems can communicate and collaborate with each other in a clear, natural, and respectful way. Effective interaction can help leverage the strengths and complement the weaknesses of both humans and AI systems. Effective interaction can also help increase trust, confidence, and satisfaction in using AI systems."
NEW QUESTION # 44
A consultant conducts a series of Consequence Scanning workshops to support testing diverse datasets.
Which Salesforce Trusted AI Principles is being practiced>
- A. Accountability
- B. Inclusivity
- C. Transparency
Answer: B
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 # 45
What is the most likely impact that high-quality data will have on customer relationships?
- A. Improved customer trust and satisfaction
- B. Increased brand loyalty
- C. Higher customer acquisition costs
Answer: A
Explanation:
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 # 46
An administrator at Cloud Kicks wants to ensure that a field is set up on the customer record so their preferred name can be captured.
Which Salesforce field type should the administrator use to accomplish this?
- A. Text
- B. Multi-Select Picklist
- C. Rich Text Area
Answer: A
Explanation:
Explanation
"A text field type should be used to capture the customer's preferred name. A text field type allows the user to enter any combination of letters, numbers, or symbols. A text field type can be used to store names, addresses, phone numbers, or other personal information."
NEW QUESTION # 47
In the context of Salesforce's Trusted AI Principles what does the principle of Empowerment primarily aim to achieve?
- A. Empower users to solve challenging technical problems using neural networks.
- B. Empower users to off all skill level to build AI application with clicks, not code.
- C. Empower users to contribute to the growing body of knowledge of leading AI research.
Answer: B
Explanation:
Explanation
"The principle of Empowerment primarily aims to achieve empowering users of all skill levels to build AI applications with clicks, not code. Empowerment is one of the Trusted AI Principles that states that AI systems should be designed and developed with respect for the empowerment and education of humans. Empowering users means enabling users to access, use, and benefit from AI systems regardless of their technical expertise or background. For example, empowering users means providing tools and platforms that allow users to build AI applications with clicks, not code, such as Einstein Prediction Builder or Einstein Discovery."
NEW QUESTION # 48
What Is a benefit of data quality and transparency as it pertains to bias in generated AI?
- A. Chances of bias are aggravated
- B. Chances of bIas and mitigated
- C. Chances of bias are remove
Answer: B
Explanation:
Explanation
"Data quality and transparency can help mitigate the chances of bias in generative AI. Data quality means that the data is accurate, complete, consistent, relevant, and timely for the AI task. Data quality can help mitigate bias by ensuring that the generative AI model learns from a balanced and representative sample of the target population or domain. Data transparency means that the data sources, methods, and processes are clear and open to inspection and verification. Data transparency can help mitigate bias by allowing users to understand and evaluate the data used or generated by the generative AI model."
NEW QUESTION # 49
A system admin recognizes the need to put a data management strategy in place.
What is a key component of data management strategy?
- A. Data Backup
- B. Naming Convention
- C. Color Coding
Answer: A
Explanation:
Explanation
Data Backup is a key component of a data management strategy. A data backup is a process of creating and storing copies of data in a separate location or device to prevent data loss or damagein case of a disaster, accident, or malicious attack. A data backup can help ensure data availability, reliability, and security by allowing data to be restored or recovered in the event of a data breach, corruption, or deletion. A data management strategy should include a data backup plan that defines the frequency, scope, method, and location of data backups, as well as the roles and responsibilities of the data backup team.
NEW QUESTION # 50
To avoid introducing unintended bias to an AI model, which type of data should be omitted?
- A. Demographic
- B. Transactional
- C. Engagement
Answer: A
Explanation:
Explanation
"Demographic data should be omitted to avoid introducing unintended bias to an AI model. 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."
NEW QUESTION # 51
What is a sensitive variable that car esc to bias?
- A. Education level
- B. Country
- C. Gender
Answer: C
Explanation:
Explanation
"Gender is a sensitive variable that can lead to bias. A sensitive variable is a variable that can potentially cause discrimination or unfair treatment based on a person's identity or characteristics. For example, gender is a sensitive variable because it can affect how people are perceived, treated, or represented by AI systems."
NEW QUESTION # 52
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?
- A. Nickname
- B. Financial status
- C. Email address
Answer: B
Explanation:
Explanation
"Financial status is an example of an immutable trait. Immutable traits are characteristics that are inherent, fixed, or unchangeable. For example, financial status is an immutable trait because it is determined by factors beyond one's control, such as birth, inheritance, or economic conditions. Nickname and email address are not immutable traits because they can be changed by choice or preference."
NEW QUESTION # 53
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?
- A. Usage
- B. Duplication
- C. Consent
Answer: B
Explanation:
Explanation
"Duplication is the data quality dimension that should be assessed to reduce communication inefficiencies.
Duplication means that the data contains multiple copies or instances of the same record or value. Duplication can cause confusion, errors, or waste in data analysis and processing. For example, duplication can lead to communication inefficiencies if customers receive multiple calls or emails from different sources for the same purpose."
NEW QUESTION # 54
What is a potential source of bias in training data for AI models?
- A. The data is collected from a diverse range of sources and demographics.
- B. The data is collected in area time from sources systems.
- C. The data is skewed toward is particular demographic or source.
Answer: C
Explanation:
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 # 55
What are some key benefits of AI in improving customer experiences in CRM?
- A. Streamlines case management by categorizing and tracking customer support cases, identifying topics, and summarizing case resolutions
- B. Improves CRM security protocols, safeguarding sensitive customer data from potential breaches and threats
- C. Fully automates the customer service experience, ensuring seamless automated interactions with customers
Answer: A
Explanation:
Explanation
"Streamlining case management by categorizing and tracking customer support cases, identifying topics, and summarizing case resolutions are some key benefits of AI in improving customer experiences in CRM. AI can help automate and optimize various aspects of customer service, such as routing cases to the right agents, providing relevant information or suggestions, and generating reports or insights. AI can also help enhance customer satisfaction and loyalty by reducing wait times, improving response quality, and providing personalized solutions."
NEW QUESTION # 56
Which type of bias results from data being labeled according to stereotypes?
- A. Association
- B. Interaction
- C. Societal
Answer: C
Explanation:
Explanation
"Societal bias results from data being labeled according to stereotypes. Societal bias is a type of bias that reflects the assumptions, norms, or values of a specific society or culture. For example, societal bias can occur when data is labeled based on gender, race, ethnicity, or religion stereotypes."
NEW QUESTION # 57
A financial institution plans a campaign for preapproved credit cards?
How should they implement Salesforce's Trusted AI Principle of Transparency?
- A. Incorporate customer feedback into the model's continuous training.
- B. Communicate how risk factors such as credit score can impact customer eligibility.
- C. Flag sensitive variables and their proxies to prevent discriminatory lending practices.
Answer: C
Explanation:
Explanation
"Flagging sensitive variables and their proxies to prevent discriminatory lending practices is how they should implement Salesforce's Trusted AI Principle of Transparency. Transparency is one of the Trusted AI Principles that states that AI systems should be designed and developed with respect for clarity and openness in how they work and why they make certain decisions. Transparency also means that AI users should be able to access relevant information and documentation about the AI systems they interact with. Flagging sensitive variables and their proxies means identifying and marking variables that can potentially cause discrimination or unfair treatment based on a person's identity or characteristics, such as age, gender, race, income, or credit score. Flagging sensitive variables and their proxies can help implement Transparency by allowing users to understand and evaluate the data used or generated by AI systems."
NEW QUESTION # 58
What is a potential outcome of using poor-quality data in AI application?
- A. AI model training becomes slower and less efficient
- B. AI models become more interpretable
- C. AI models may produce biased or erroneous results.
Answer: C
Explanation:
Explanation
"A potential outcome of using poor-quality data in AI applications is that AI models may produce biased or erroneous results. Poor-quality data means that the data is inaccurate, incomplete,inconsistent, irrelevant, or outdated for the AI task. Poor-quality data 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. Poor-quality data can also introduce or exacerbate biases or errors in AI models, such as human bias, societal bias, confirmation bias, or overfitting or underfitting."
NEW QUESTION # 59
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