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Salesforce Certified AI Associate Exam Sample Questions (Q33-Q38):
NEW QUESTION # 33
Cloud Kicks relies on data analysis to optimize its product recommendation; however, CK encounters a recurring Issue of Incomplete customer records, withmissing contact Information and incomplete purchase histories.
How will this incomplete data quality impact the company's operations?
Answer: C
Explanation:
"The incomplete data quality will impact the company's operations by hindering the accuracy of product recommendations. Incomplete data means that the data is missing some values or attributes that are relevant for the AI task. Incomplete data can affect the performance and reliability of AI models, as they may not have enough information to learn from or make accurate predictions. For example, incomplete customer records can affect the quality of product recommendations, as the AI model may not be able to capture the customers' preferences, behavior, or needs."
NEW QUESTION # 34
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?
Answer: C
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 # 35
What are some of the ethical challenges associated with AI development?
Answer: B
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 themodels, the design choices made by the developers, or the interpretation of the results by the users. Lack of transparency can make it difficult to understand how and why AI systems make certain decisions, which can affect trust, accountability, and fairness."
NEW QUESTION # 36
What is the rile of data quality in achieving AI business Objectives?
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 # 37
A financial institution plans a campaign for preapproved credit cards?
How should they implement Salesforce's Trusted AI Principle of Transparency?
Answer: A
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 # 38
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