PL-600 · Question #211
You conduct an initial discovery meeting with a manufacturer. The manufacturer plans to modernize its current sales order system by using Microsoft Power Platform and AI-generated product…
The correct answer is C. Which data do you plan to use to train and use with AI? D. Which privacy or residency concerns does the company have? To assess risk factors for using AI-generated product suggestions, it is crucial to understand the data sources used for AI training and any associated data privacy or residency concerns.
Question
Options
- AWhich type of access will users require for the application?
- BWhat is the budget for implementing and maintaining the solution?
- CWhich data do you plan to use to train and use with AI?
- DWhich privacy or residency concerns does the company have?
- EHow will the company capture feedback to improve accuracy of the AI model?
How the community answered
(37 responses)- A8% (3)
- B11% (4)
- C78% (29)
- E3% (1)
Why each option
To assess risk factors for using AI-generated product suggestions, it is crucial to understand the data sources used for AI training and any associated data privacy or residency concerns.
User access types are important for application security but are not directly related to the specific risk factors of using data with AI-generated suggestions.
Budget is a project management concern, not a direct risk factor for the data used in AI suggestions.
Understanding 'which data you plan to use to train and use with AI' is critical for identifying potential biases, data quality issues, and intellectual property concerns that could significantly impact the reliability and fairness of AI-generated product suggestions.
Asking about 'privacy or residency concerns' directly addresses legal and ethical risks associated with handling customer data, especially when used for AI, ensuring compliance with regulations like GDPR or CCPA and preventing potential data sovereignty issues.
Capturing feedback for AI model improvement is a best practice for model accuracy and refinement, but it's a mitigation strategy rather than an initial question to identify inherent risk factors of the data itself.
Concept tested: AI data risk assessment
Source: https://learn.microsoft.com/en-us/power-platform/guidance/responsible-ai-overview
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