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Salesforce Salesforce-AI-Associate Exam Syllabus Topics:

Topic
Details

Topic 1

Data for AI: Questions about the importance of data quality and different elements or components of data quality are related to this topic.

Topic 2

AI Capabilities in CRM: Get familiar with the benefits of AI and capabilities of CRM.

Topic 3

Ethical Considerations of AI: It delves into the ethical challenges of AI such as human bias in machine learning, lack of transparency, etc. The topic also explains how to apply the Trusted AI Principles of Salesforce to given scenarios.

Topic 4

AI Fundamentals: This topic discusses the major principles and applications of AI within Salesforce. It also focuses on different types of AI and their capabilities.

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Salesforce Certified AI Associate Exam Sample Questions (Q70-Q75):

NEW QUESTION # 70
What can bias in AI algorithms in CRM lead to?

A. Advertising cost increases
B. Ethical challenges in CRM systems
C. Personalization and target marketing changes

Answer: B

Explanation:
Explanation
"Bias in AI algorithms in CRM can lead to ethical challenges in CRM systems. Bias means that AI algorithms favor or discriminate certain groups or outcomes based on irrelevant or unfair criteria. Bias can affect the fairness and ethics of CRM systems, as they may affect how customers are perceived, treated, or represented by AI algorithms. For example, bias can lead to ethical challenges in CRM systems if AI algorithms make inaccurate or harmful predictions or recommendations based on customers' identity or characteristics."

NEW QUESTION # 71
What is an example of ethical debt?

A. Delaying an AI product launch to retrain an AI data model
B. Violating a data privacy law and failing to pay fines
C. Launching an AI feature after discovering a harmful bias

Answer: C

Explanation:
Ethical debt refers to the long-term negative consequences of prioritizing speed or convenience over responsible AI development practices. Ethical debt accumulates when AI systems are deployed despite known ethical concerns, such as bias, privacy violations, or transparency issues.
Option A (Correct): Launching an AI feature after discovering harmful bias is a clear example of ethical debt because it disregards the ethical obligation to ensure fairness and non-discrimination in AI outcomes. Ignoring bias can lead to systemic issues that are difficult and costly to correct later.
Option B (Incorrect): Violating a data privacy law and failing to pay fines is a legal issue rather than an example of ethical debt. While related, ethical debt pertains more to AI decision-making and development choices.
Option C (Incorrect): Delaying an AI product launch to retrain an AI model is a responsible action that helps avoid ethical debt, rather than an example of it. This demonstrates an effort to mitigate bias and improve AI fairness before deployment.

NEW QUESTION # 72
Cloud Kicks wants to improve the quality of its AI model's predictions with the use of a large amount of data.
Which data quality element should the company focus on?

A. Accuracy
B. Location
C. Volume

Answer: A

Explanation:
To improve the quality of AI model predictions, Cloud Kicks should focus on the accuracy of the data.
Accurate data ensures that the insights and predictions generated by AI models are reliable and valid. Data accuracy involves correcting errors, filling missing values, and verifying data sources to enhance the quality of information fed into the AI systems. Focusing on data accuracy helps in minimizing prediction errors and enhances the decision-making process based on AI insights. For more details on the importance of data quality in AI models, Salesforce provides extensive guidance in their documentation, which can be found at Data Quality and AI.

NEW QUESTION # 73
What is a key characteristic of machine learning in the context of AI capabilities?

A. Can perfectly mimic human intelligence and decision-making
B. Relies on preprogrammed rules to make decisions
C. Uses algorithms to learn from data and make decisions

Answer: C

Explanation:
Explanation
"Machine learning is a key characteristic of AI capabilities that uses algorithms to learn from data and make decisions. Machine learning is a branch of AI that enables computers to learn from data without being explicitly programmed. Machine learning algorithms can analyze data, identify patterns, and make predictions or recommendations based on the data."

NEW QUESTION # 74
A consultant conducts a series of Consequence Scanning workshops to support testing diverse datasets.
Which Salesforce Trusted AI Principles is being practiced>

A. Accountability
B. Inclusivity
C. Transparency

Answer: B

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 # 75
......

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