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Home Salesforce Certified AI Associate

Salesforce Certified AI Associate Exam Practice Questions (P. 3)

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Question #11
In the context of Salesforce's Trusted AI Principles, what does the principle of Empowerment primarily aim to achieve?
  1. A
    Empower users of all skill levels to build AI applications with clicks, not code.
  2. B
    Empower users to solve challenging technical problems using neural networks.
  3. C
    Empower users to contribute to the growing body of knowledge of leading AI research.

Correct Answer:
A
chatbot-img GPT-4o - Answer
The Empowerment principle within Salesforce's Trusted AI Principles is designed to democratize AI technology. It emphasizes simplifying AI development so that individuals, regardless of their tech expertise, can create AI solutions. This approach highlights an inclusive perspective, ensuring that AI tools are accessible to a broad audience through user-friendly interfaces that require minimal coding skills.

Question #12
Cloud Kicks wants to use an AI model 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?
  1. A
    Age
  2. B
    Reliability
  3. C
    Volume

Correct Answer:
B
chatbot-img GPT-4o - Answer
Absolutely, reliability is crucial in this scenario. When predicting shoe demand based on historical sales and regional characteristics, the consistency, accuracy, and trustworthiness of your data are imperative. A robust dataset ensures that the predictions made by the AI model are dependable and can be acted upon with confidence. Remember, the input data's quality directly influences the output accuracy. Trustworthy data leads to reliable predictions.

Question #13
A financial institution plans a campaign for preapproved credit cards.
How should they implement Salesforce's Trusted AI Principle of Transparency?
  1. A
    Communicate how risk factors such as credit score can impact customer eligibility.
  2. B
    Flag sensitive variables and their proxies to prevent discriminatory lending practices.
  3. C
    Incorporate customer feedback into the model’s continuous training.

Correct Answer:
B
chatbot-img GPT-4o - Answer
Flagging sensitive variables and their proxies is key to uphold the Salesforce Trusted AI Principle of Transparency. This step effectively addresses transparency by making clear which variables influence decision-making, helping to avoid biased outcomes. By focusing on these adjustments, the institution ensures equity and clarity in how decisions are derived, aligning with the essence of transparent AI practices.

Question #14
What is a key challenge of human-AI collaboration in decision-making?
  1. A
    Leads to more informed and balanced decision-making
  2. B
    Creates a reliance on AI, potentially leading to less critical thinking and oversight
  3. C
    Reduces the need for human involvement in decision-making processes

Correct Answer:
B
chatbot-img GPT-4o - Answer
The main issue with having AI in decision-making is its tendency to foster over-reliance. When humans depend too much on artificial intelligence, it can seriously dial down their critical thinking skills and even lessen how thoroughly they oversee projects and processes. This can be quite risky in scenarios that demand nuanced human judgment.

Question #15
Which best describes the difference between predictive AI and generative AI?
  1. A
    Predictive AI and generative AI have the same capabilities but differ in the type of input they receive; predictive AI receives raw data whereas generative AI receives natural language.
  2. B
    Predictive AI uses machine learning to classify or predict outputs from its input data whereas generative AI does not use machine learning to generate its output.
  3. C
    Predictive AI uses machine learning to classify or predict outputs from its input data whereas generative AI uses machine leaning to generate new and original output for a given input.

Correct Answer:
C
chatbot-img GPT-4o - Answer
Both predictive and generative AI deploy machine learning; however, they cater to different needs. Predictive AI is all about using data to foresee outcomes or classify information. On the flip side, generative AI goes a step further by creatively producing new, original content based on the input it's fed. Each plays a unique role tailored to specific applications, making understanding their distinctions crucial for proper implementation in AI projects.

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