SALESFORCE-AI-ASSOCIATE SIMULATIONS PDF, RELIABLE SALESFORCE-AI-ASSOCIATE EXAM ONLINE

Salesforce-AI-Associate Simulations Pdf, Reliable Salesforce-AI-Associate Exam Online

Salesforce-AI-Associate Simulations Pdf, Reliable Salesforce-AI-Associate Exam Online

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Salesforce Certified AI Associate Exam Sample Questions (Q77-Q82):

NEW QUESTION # 77
Cloud Kicks relies on data analysis to optimize its product recommendation; however, CK encounters a recurring Issue of Incomplete customer records, with missing contact Information and incomplete purchase histories.
How will this incomplete data quality impact the company's operations?

  • A. The diversity of product recommendations Is Improved.
  • B. The response time for product recommendations is stalled.
  • C. The accuracy of product recommendations is hindered.

Answer: C

Explanation:
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 # 78
What are the key components of the data quality standard?

  • A. Accuracy, Completeness, Consistency
  • B. Reviewing, Updating, Archiving
  • C. Naming, formatting, Monitoring

Answer: A

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 # 79
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 # 80
Cloud Kicks uses Einstein to generate predictions out is not seeing accurate results?
What to a potential mason for this?

  • A. Too much data
  • B. Poor data quality
  • C. The wrongproduct

Answer: B

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 # 81
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. Flagsensitive variables and their proxies to prevent discriminatory lending practices.

Answer: C

Explanation:
"Flagging sensitive variables and their proxies to prevent discriminatory lending practicesis 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 variablesthat 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 # 82
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