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NEW QUESTION # 59
What is a sensitive variable that car esc to bias?
- A. Country
- B. Gender
- C. Education level
Answer: B
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 # 60
Cloud Kicks wants to implement AI features on its 5aiesforce Platform but has concerns about potential ethical and privacy challenges.
What should they consider doing to minimize potential AI bias?
- A. Integrate AI models that auto-correct biased data.
- B. Implement Salesforce's Trusted AI Principles.
- C. Use demographic data to identify minority groups.
Answer: B
Explanation:
"Implementing Salesforce's Trusted AI Principles is what Cloud Kicks should consider doing to minimize potential AI bias. Salesforce's Trusted AI Principles are a set of guidelines and best practices for developing and using AI systems in a responsible and ethical way. The principles include Accountability, Fairness & Equality, Transparency & Explainability, Privacy & Security, Reliability & Safety, Inclusivity & Diversity, Empowerment & Education."
NEW QUESTION # 61
What is an example of ethical debt?
- A. Violating a data privacy law and falling to pay fines
- B. Launching an AI feature after discovering a harmful bias
- C. Delaying an AI product launch to retrain an AI data model
Answer: B
Explanation:
"Launching an AI feature after discovering a harmful bias is an example of ethical debt. Ethical debt is a term that describes the potential harm or risk caused by unethical or irresponsible decisions or actions related to AIsystems. Ethical debt can accumulate over time and have negative consequences for users, customers, partners, or society. For example, launching an AI feature after discovering a harmful bias can create ethical debt by exposing users to unfair or inaccurate results that may affect their trust, satisfaction, or well-being."
NEW QUESTION # 62
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. Duplication
- B. Consent
- C. Usage
Answer: A
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 # 63
Cloud Kicks wants to implement AI features on its 5aiesforce Platform but has concerns about potential ethical and privacy challenges.
What should they consider doing to minimize potential AI bias?
- A. Integrate AI models that auto-correct biased data.
- B. Implement Salesforce's Trusted AI Principles.
- C. Use demographic data to identify minority groups.
Answer: B
Explanation:
Explanation
"Implementing Salesforce's Trusted AI Principles is what Cloud Kicks should consider doing to minimize potential AI bias. Salesforce's Trusted AI Principles are a set of guidelines and best practices for developing and using AI systems in a responsible and ethical way. The principles include Accountability, Fairness & Equality, Transparency & Explainability, Privacy & Security, Reliability & Safety, Inclusivity & Diversity, Empowerment & Education."
NEW QUESTION # 64
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. Prioritize active leads quarterly.
- B. Review and update missing lead information.
- C. Redesign the lead conversion process,
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 # 65
What are some key benefits of AI in improving customer experiences in CRM?
- A. Improves CRM security protocols, safeguarding sensitive customer data from potential breaches and threats
- B. Streamlines case management by categorizing and tracking customer support cases, identifying topics, and summarizing case resolutions
- C. Fully automates the customer service experience, ensuring seamless automated interactions with customers
Answer: B
NEW QUESTION # 66
What is a key characteristic of machine learning in the context of AI capabilities?
- A. Can perfectly mimic human intelligence and decision-making
- B. Uses algorithms to learn from data and make decisions
- C. Relies on preprogrammed rules to make decisions
Answer: B
Explanation:
Explanation
"Machine learning is a key characteristic of AI capabilities that uses algorithms to learn from data and make decisions. Machine learning is a branch of AI that enables computers to learn from data without being explicitly programmed. Machine learning algorithms can analyze data, identify patterns, and make predictions or recommendations based on the data."
NEW QUESTION # 67
What are some of the ethical challenges associated with AI development?
- A. Inherent neutrality of AI systems, which eliminates any potential for human bias in decision-making
- B. Potential for human bias in machine learning algorithms and the lack of transparency in AI decision-making processes
- C. Implicit transparency of AI systems, which makes It easy for users to understand and trust their decisions
Answer: B
Explanation:
Explanation
"Some of the ethical challenges associated with AI development are the potential for human bias in machine learning algorithms and the lack of transparency in AI decision-making processes. Human bias can arise from the data used to train the models, the design choices made by the developers, or the interpretation of the results by the users. Lack of transparency can make it difficult tounderstand how and why AI systems make certain decisions, which can affect trust, accountability, and fairness."
NEW QUESTION # 68
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 programminglanguage
- 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 # 69
What should organizations do to ensure data quality for their AI initiatives?
- A. Prioritizemodel fine-tuning over data quality improvements.
- B. Rely on AI algorithms to automatically handle data quality issues.
- C. Collect and curate high-quality data from reliable sources.
Answer: C
Explanation:
"Organizations should collect and curate high-quality data from reliable sources to ensure data quality for their AI initiatives. High-quality data means that the data is accurate, complete, consistent, relevant, and timely for the AI task. Reliable sources mean that the data is trustworthy, credible, and authoritative. Collecting and curating high-quality data from reliable sources can improve the performance and reliability of AI systems."
NEW QUESTION # 70
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 Process Maturity Model
- B. Ethical AI Prediction Maturity Model
- C. Ethical AI practice Maturity Model
Answer: A
Explanation:
"The Ethical AI Process Maturity Model is the established Salesforce Ethical Maturity Model that the Cloud technical team should use toguide 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 # 71
A business analyst (BA) is preparing a new use case for Al. They run a report to check for null values in the attributes they plan to use.
Which data quality component Is the BA verifying by checking for null values?
- A. Duplication
- B. Completeness
- C. Usage
Answer: B
Explanation:
By checking for null values, a business analyst (BA) is verifying the data quality component of completeness.
Completeness refers to the absence of missing values or gaps in the data, which is essential for the accuracy and reliability of reports and analytics used in AI models. Null values can indicate incomplete data, which may adversely affect the performance of AI applications by leading to incorrect predictions or insights.
Salesforce emphasizes the importance of data completeness for effective data analysis and provides tools for data quality assessment and improvement. Details on handling data completeness in Salesforce can be explored at Salesforce Help Data Management.
NEW QUESTION # 72
What is a key benefit of effective interaction between humans and AI systems?
- A. Alerts humans to the presence of biased data
- B. Reduces the need for human involvement
- C. Leads to more informed and balanced decision making
Answer: C
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 # 73
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: B
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 # 74
Cloud Kicks uses Einstein to generate predictions out is not seeing accurate results?
What to a potential mason for this?
- A. The wrongproduct
- B. Too much data
- C. Poor data quality
Answer: C
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 dataquality 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 # 75
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 Process Maturity Model
- B. Ethical AI Prediction Maturity Model
- C. Ethical AI practice Maturity Model
Answer: A
Explanation:
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 # 76
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Salesforce-AI-Associate Dumps Updated Nov 12, 2024 WIith 103 Questions: https://drive.google.com/open?id=12qwpGya005OMHD3Bz7BP2cPAYaQP0_RB