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| Section | Objectives |
|---|---|
| AI Lifecycle Governance Implementation | - Operational governance controls
|
| Foundations of AI Systems and Governance | - Governance principles and accountability
|
| AI Risk Management and Impact Assessment | - Risk identification and mitigation
|
| Regulatory and Legal Frameworks for AI | - Global AI governance regulations
|
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NEW QUESTION # 160
CASE STUDY
Please use the following to answer the next question:
A small local flower delivery company operates a few stores and has a limited IT budget. To reduce the time spent on customer service, which is a major drain on employee time, the company plans to implement a simple but high-performance generative AI chatbot on its website. The chatbot will provide real-time, fact- based responses to customer inquiries and assist with order processing, helping to reduce incoming phone calls.
The company currently uses a single on-premises server for its order database and email system and has not yet partnered with a cloud provider.
An internal data privacy policy governs the use of customer data. This policy, written before the adoption of AI, allows the use or transfer of customer data beyond name and contact information but requires that all such data be deleted after the order is completed. The company prefers to maintain this policy without changes.
MULTI-SELECT
Please select 3 of the 5 options below. No partial credit will be given.
Which of the following actions would necessitate a change to the company ' s privacy policy?
Answer: A,D,E
Explanation:
A, D, and E introduce processing materially different from the practices described in the existing privacy policy. Storing chatbot inputs for RAG creates an additional retention and reuse purpose that should be addressed through appropriate privacy disclosures and retention controls. Using customer-session information to retrain the underlying model creates a distinct secondary purpose beyond processing an order, even when the data is subsequently deleted. Scanning a customer ' s appearance to infer frustration or confusion introduces an entirely new category of observation and inference, requiring additional transparency, legal- basis analysis, proportionality assessment, and safeguards. By contrast, B involves transferring customer information to a service provider so the requested service can operate, which the existing policy already permits. C involves ordinary contact and delivery information retained through completion of the transaction, which also fits the stated policy.
NEW QUESTION # 161
During the first month when the company monitors the model for bias, it is most important to?
Answer: B
Explanation:
Theinitial deployment phaseof an AI model is critical forpost-deployment monitoring. When tracking for bias, the most important task is tocontinue disparity testingto determine whether outputs differ across protected groups.
From theAI Governance in Practice Report 2024:
"Performance monitoring protocols... should include mechanisms to assess and measure disparities in outcomes across different demographic groups." (p. 12)
"Bias may not be evident during pre-deployment testing but can emerge in real-world use." (p. 41)
* B. Awareness trainingis helpful, but not a technical bias mitigation activity.
* C. Analyzing training datais apre-deploymenttask.
* D. Documenting human decisionsmay support auditability but doesn't detect bias in AI outputs.
NEW QUESTION # 162
A company has developed a proprietary AI model that analyzes consumer online behavior and predicts what prices consumers would be willing to pay for certain products, so that retailers may modify pricing accordingly. To test the model, the company has:
Performed an impact assessment
Conducted repeatability tests
Exposed the model to edge cases and potential malicious input
Conducted adversarial testing to identify security threats
Assessed and mitigated discrimination risks
Which additional responsible AI principle has the company failed to assess?
Answer: D
Explanation:
The correct answer is D because the company has already addressed several key responsible AI principles, including fairness through discrimination risk mitigation, robustness through adversarial and edge-case testing, and reliability via repeatability testing. However, there is no indication that the company has addressed transparency, which involves providing clear information about how the model operates, how pricing decisions are made, and how outputs may affect consumers. Transparency is a critical AI governance principle, especially in consumer-facing applications like dynamic pricing, where decisions can significantly impact individuals. Governance frameworks emphasize that users and stakeholders should be informed about AI-driven decisions and their implications. Without transparency, even technically sound and fair systems may lack trustworthiness and fail to meet regulatory or ethical expectations.
NEW QUESTION # 163
CASE STUDY
Please use the following answer the next question:
Good Values Corporation (GVC) is a U.S. educational services provider that employs teachers to create and deliver enrichment courses for high school students. GVC has learned that many of its teacher employees are using generative Al to create the enrichment courses, and that many of the students are using generative Al to complete their assignments.
In particular, GVC has learned that the teachers they employ used open source large language models ("LLM") to develop an online tool that customizes study questions for individual students. GVC has also discovered that an art teacher has expressly incorporated the use of generative Al into the curriculum to enable students to use prompts to create digital art.
GVC has started to investigate these practices and develop a process to monitor any use of generative Al, including by teachers and students, going forward.
Which of the following risks should be of the highest concern to individual teachers using generative Al to ensure students learn the course material?
Answer: B
Explanation:
The highest concern for individual teachers using generative AI to ensure students learn the course material is model accuracy. Ensuring that the AI-generated content is accurate and relevant to the curriculum is crucial for effective learning. If the AI model produces inaccurate or irrelevant content, it can mislead students and hinder their understanding of the subject matter.
Reference: According to the AIGP Body of Knowledge, one of the core risks posed by AI systems is the accuracy of the data and models used. Ensuring the accuracy of AI-generated content is essential for maintaining the integrity of the educational material and achieving the desired learning outcomes.
NEW QUESTION # 164
You are the chief privacy officer of a medical research company that would like to collect and use sensitive data about cancer patients, such as their names, addresses, race and ethnic origin, medical histories, insurance claims, pharmaceutical prescriptions, eating and drinking habits and physical activity.
The company will use this sensitive data to build an AI algorithm that will spot common attributes that will help predict if seemingly healthy people are more likely to get cancer. However, the company is unable to obtain consent from enough patients to sufficiently collect the minimum data to train its model.
Which of the following solutions would most efficiently balance privacy concerns with the lack of available data during the testing phase?
Answer: A
Explanation:
Using synthetic data allows the company to augment limited real patient data while protecting privacy, efficiently addressing data scarcity during testing.
NEW QUESTION # 165
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