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Salesforce Certified AI Associate Exam Sample Questions (Q86-Q91):

NEW QUESTION # 86
Cloud Kicks is testing a new AI model.
Which approach aligns with Salesforce's Trusted AI Principle of Incluslvity?

A. Test only with data from a specific region or demographic to limit the risk of data leaks.
B. Rely on a development team with uniform backgrounds to assess the potential societal implications of the model.
C. Test with diverse and representative datasets appropriate for how the model will be used.

Answer: C

Explanation:
Explanation
"Testing with diverse and representative datasets appropriate for how the model will be used aligns with Salesforce's Trusted AI Principle of Inclusivity. Inclusivity means that AI systems should be designed and developed with respect for diversity and inclusion of different perspectives, backgrounds, and experiences.
Testing with diverse and representative datasets can help ensure that the models are fair, unbiased, and representative of the target population or domain."

NEW QUESTION # 87
Cloud Kicks wants to use an AI mode to predict the demand for shoes using historical data on sales and regional characteristics.
What is an essential data quality dimension to achieve this goal?

A. Age
B. Reliability
C. Volume

Answer: B

Explanation:
"Reliability is an essential data quality dimension to achieve the goal of predicting the demand for shoes using historical data on sales and regional characteristics. Reliability means that the data values are trustworthy, credible, and authoritativefor the AI task. Reliable data can improve the accuracy and confidence of AI predictions, as they reflect the true state or condition of the target population or domain. For example, reliable data can help predict the demand for shoes by using verified andvalidated sales and regional data."

NEW QUESTION # 88
What are some of the ethical challenges associated with AI development?

A. Potential for human bias in machine learning algorithms and the lack of transparency in AI decision-making processes
B. Inherent neutrality of AI systems, which eliminates any potential for human bias in decision-making
C. Implicit transparency of AI systems, which makes It easy for users to understand and trust their decisions

Answer: A

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 # 89
What is a Key consideration regarding data quality in AI implementation?

A. Integration process of AI models with Salesforce workflows
B. Data's role in training and fine-tuning Salesforce AI models
C. Techniques from customizing AI features in Salesforce

Answer: B

Explanation:
"Data's role in training and fine-tuning Salesforce AI models is a key consideration regarding data quality in AI implementation. 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's role in training and fine-tuning Salesforce AI models means understanding how data is used to build, train, test, and improve AI models in Salesforce, such as Einstein Prediction Builder or Einstein Discovery."

NEW QUESTION # 90
What are predictive analytics, machine learning, natural language processing (NLP), and computer vision?

A. Different types of data models used in Salesforce
B. Different types of AI that can be applied in Salesforce
C. Different types of automation tools used in Salesforce

Answer: B

Explanation:
Predictive analytics, machine learning, natural language processing (NLP), and computer vision are all types of artificial intelligence technologies that can be applied in Salesforce to enhance various aspects of business operations and customer interactions. Predictive analytics uses historical data to make predictions about future events. Machine learning involves algorithms that can learn from and make decisions based on data.
NLP is concerned with the interactions between computers and humans using natural language, and computer vision interprets and processes visual information from the world to make sense of it in the way humans do.
Salesforce harnesses these AI technologies, particularly through its Einstein platform, to provide powerful tools that help businesses automate tasks, make better decisions, and offer more personalized services. For more on how Salesforce utilizes these AI technologies, you can explore the Einstein AI services documentation at Salesforce Einstein.

NEW QUESTION # 91
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