Salesforce-AI-Associate Practice Test
Updated On 18-Sep-2025
106 Questions
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 Prediction Maturity Model
B. Ethical AI Process Maturity Model
C. Ethical AI practice Maturity Model
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.”
What is the rile of data quality in achieving AI business Objectives?
A. Data quality is unnecessary because AI can work with all data types.
B. Data quality is required to create accurate AI data insights.
C. Data quality is important for maintain Ai data storage limits
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.”
What role does data quality play in the ethical us of AI applications?
A. High-quality data is essential for ensuring unbased and for fair AI decisions, promoting ethical use, and preventing discrimi…
B. High-quality data ensures the process of demographic attributes requires for personalized campaigns.
C. Low-quality data reduces the risk of unintended bias as the data is not overfitted to demographic groups.
Explanation:
“High-quality data is essential for ensuring unbiased and fair AI decisions, promoting ethical use, and preventing discrimination. High-quality data means that the data is accurate, complete, consistent, relevant, and timely for the AI task. High-quality data can help ensure unbiased and fair AI decisions by providing a balanced and representative sample of the target population or domain. High-quality data can also help promote ethical use and prevent discrimination by respecting the rights and preferences of users regarding their personal data.”
What should an organization do to enforce consistency across accounts for newly entered records?
A. Merge all duplicate accounts into a single record when duplicate entries are detected.
B. Input the data exactly as it appears from the source, such as the company’s website or social media,
C. Implement naming conventions or a predefined list of user-selectable values for organization-wide records.
Explanation:
To ensure consistency across accounts for newly entered records, organizations should implement naming conventions or a predefined list of user-selectable values. This approach standardizes data entry, reducing variations and errors. It also helps in maintaining clean data which is essential for accurate reporting and analytics. Using standardized naming conventions ensures that all users adhere to a consistent format, making it easier to manage and analyze data across the organization. For more information on best practices for data management in Salesforce, refer to Salesforce's documentation on Data Management Best Practices.
What is a societal implication of excluding ethics in AI development?
A. Faster and cheaper development
B. More innovation and creativity
C. Harm to marginalized communities
Explanation:
Excluding ethics in AI development can lead to societal implications such as harm to marginalized communities. When ethical considerations are not integrated into AI development, the resulting technologies may perpetuate or amplify biases, leading to unfair treatment or discrimination against certain groups. This can reinforce existing social inequalities and prevent these communities from benefiting equally from the advancements in AI technology. Salesforce is committed to responsible AI development and emphasizes the importance of ethical considerations in their development practices to prevent such outcomes. Details on Salesforce’s approach to ethical AI and its importance can be found at Salesforce Ethical AI.
| Salesforce-AI-Associate Exam Questions - Home |
| Page 2 out of 22 Pages |