AI Associate Exam Questions with
Verified Answers
Question: 1
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. ✔️✔️A
"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."
Question: 2
What can bias in AI algorithms in CRM lead to?
A. Personalization and target marketing changes
B. Advertising cost increases
C. Ethical challenges in CRM systems ✔️✔️C
"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."
Question: 3
What is an example of ethical debt?
A. Violating a data privacy law and falling to pay fines
B. Launching an AI feature after discovering a harmful bias
C. Delaying an AI product launch to retrain an AI data model ✔️✔️B
"Launching an AI feature after discovering a harmful bias is an example of ethical debt. Ethical
debt is a term that describes the potential harm or risk caused by unethical or irresponsible
decisions or actions related to AI systems. Ethical debt can accumulate over time and have
negative consequences for users, customers, partners, or society. For example, launching an AI
feature after discovering a harmful bias can create ethical debt by exposing users to unfair or
inaccurate results that may affect their trust, satisfaction, or well-being."
Question: 4
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. Inclusivity
C. Accountability ✔️✔️B
"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."
,Question: 5
A financial institution plans a campaign for preapproved credit cards?
How should they implement Salesforce's Trusted AI Principle of Transparency?
A. Communicate how risk factors such as credit score can impact customer eligibility.
B. Flag sensitive variables and their proxies to prevent discriminatory lending practices.
C. Incorporate customer feedback into the model's continuous training. ✔️✔️B
"Flagging sensitive variables and their proxies to prevent discriminatory lending practices is 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 variables that 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."
Question: 6
Cloud kicks wants to decrease the workload for its customer care agents by implementing a
chatbot on its website that partially deflects incoming cases by answering frequency asked ✔️✔️
Questions Which field of AI is most suitable for this scenario?
A. Natural language processing
B. Computer vision
C. Predictive analytics ✔️✔️A
"Natural language processing is the field of AI that is most suitable for this scenario. Natural
language processing (NLP) is a branch of AI that enables computers to understand and generate
, natural language, such as speech or text. NLP can be used to create conversational interfaces
that can interact with users using natural language, such as chatbots. Chatbots can help
automate and streamline customer service processes by providing answers, suggestions, or
actions based on the user's intent and context."
Question: 7
What are the key components of the data quality standard?
A. Naming, formatting, Monitoring
B. Accuracy, Completeness, Consistency
C. Reviewing, Updating, Archiving ✔️✔️B
"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."
Question: 8
Which best describes the different between predictive AI and generative AI?
A. Predictive new and original output for a given input.
B. Predictive AI and generative have the same capabilities differ in the type of input they
receive: predictive AI receives raw data whereas generation AI receives natural language.
C. Predictive AI uses machine learning to classes or predict output from its input data whereas
generative AI does not use machine learning to generate its output ✔️✔️A
Verified Answers
Question: 1
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. ✔️✔️A
"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."
Question: 2
What can bias in AI algorithms in CRM lead to?
A. Personalization and target marketing changes
B. Advertising cost increases
C. Ethical challenges in CRM systems ✔️✔️C
"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."
Question: 3
What is an example of ethical debt?
A. Violating a data privacy law and falling to pay fines
B. Launching an AI feature after discovering a harmful bias
C. Delaying an AI product launch to retrain an AI data model ✔️✔️B
"Launching an AI feature after discovering a harmful bias is an example of ethical debt. Ethical
debt is a term that describes the potential harm or risk caused by unethical or irresponsible
decisions or actions related to AI systems. Ethical debt can accumulate over time and have
negative consequences for users, customers, partners, or society. For example, launching an AI
feature after discovering a harmful bias can create ethical debt by exposing users to unfair or
inaccurate results that may affect their trust, satisfaction, or well-being."
Question: 4
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. Inclusivity
C. Accountability ✔️✔️B
"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."
,Question: 5
A financial institution plans a campaign for preapproved credit cards?
How should they implement Salesforce's Trusted AI Principle of Transparency?
A. Communicate how risk factors such as credit score can impact customer eligibility.
B. Flag sensitive variables and their proxies to prevent discriminatory lending practices.
C. Incorporate customer feedback into the model's continuous training. ✔️✔️B
"Flagging sensitive variables and their proxies to prevent discriminatory lending practices is 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 variables that 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."
Question: 6
Cloud kicks wants to decrease the workload for its customer care agents by implementing a
chatbot on its website that partially deflects incoming cases by answering frequency asked ✔️✔️
Questions Which field of AI is most suitable for this scenario?
A. Natural language processing
B. Computer vision
C. Predictive analytics ✔️✔️A
"Natural language processing is the field of AI that is most suitable for this scenario. Natural
language processing (NLP) is a branch of AI that enables computers to understand and generate
, natural language, such as speech or text. NLP can be used to create conversational interfaces
that can interact with users using natural language, such as chatbots. Chatbots can help
automate and streamline customer service processes by providing answers, suggestions, or
actions based on the user's intent and context."
Question: 7
What are the key components of the data quality standard?
A. Naming, formatting, Monitoring
B. Accuracy, Completeness, Consistency
C. Reviewing, Updating, Archiving ✔️✔️B
"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."
Question: 8
Which best describes the different between predictive AI and generative AI?
A. Predictive new and original output for a given input.
B. Predictive AI and generative have the same capabilities differ in the type of input they
receive: predictive AI receives raw data whereas generation AI receives natural language.
C. Predictive AI uses machine learning to classes or predict output from its input data whereas
generative AI does not use machine learning to generate its output ✔️✔️A
