What is an example of a Microsoft responsible AI principle?
Answer(s): C
Correct:* AI systems should be secure and respect privacy.* AI systems should treat people fairly.Incorrect:* AI systems should be in the public domain.* AI systems should make personal details accessible.* AI systems should NOT reveal the details of their design.* AI systems should protect the interests of developers.* AI systems should use black-box models.Note:Responsible AI principles*-> Fairness: AI systems should treat all people fairly.AI systems should treat everyone equally and provide the same recommendations to all individuals. Fairness in AI systems prevents discrimination based on personal characteristics.* Reliability and safety: AI systems should perform reliably and safely.*-> Privacy and security: AI systems should be secure and respect privacy.* Inclusiveness: AI systems should empower everyone and engage people.* Etc.
https://learn.microsoft.com/en-us/azure/cloud-adoption-framework/strategy/responsible-ai
Which statement is an example of a Microsoft responsible AI principle?
Answer(s): A
The statement "AI systems must be transparent and inclusive" is an example of a Microsoft responsible AI principle. These two principles are part of a larger set of guiding principles that Microsoft uses to ensure AI systems are developed and used ethically, including Fairness, Reliability and Safety, Privacy and Security, and Accountability.Transparency: This principle involves clearly documenting the purpose, process, and limitations of AI systems to help users understand their behaviorInclusiveness: This principle focuses on ensuring that AI systems are accessible, usable, and beneficial to a diverse range of people, empowering global communities and avoiding discrimination
https://www.microsoft.com/en-us/ai/principles-and-approach
You need to convert receipts into transactions in a spreadsheet. The spreadsheet must include the date of the transaction, the merchant, the total spent, and any taxes paid.Which Azure AI service should you use?
Answer(s): B
Azure AI Document Intelligence can convert receipts into structured data, including merchant name, transaction date, total spent, and tax, which can then be exported to a spreadsheet. It uses a prebuilt model specifically for receipts to extract this key information and returns it as structured JSON, which can be further processed and used to populate a spreadsheet.
https://learn.microsoft.com/en-us/azure/ai-services/document-intelligence/prebuilt/receipt
You plan to create an AI application by using Azure AI Foundry. The solution will be deployed to dedicated virtual machines.Which deployment option should you use?
Answer(s): D
Deployment optionsAzure AI Foundry provides several deployment options depending on the type of models and resources you need to provision. The following deployment options are available:* Standard deployment in Azure AI Foundry resources* Deployment to serverless API endpoints* Deployment to managed computesServerless API endpointThis deployment option is available only in Azure AI hub resources. It allows you to create dedicated endpoints to host the model, accessible through an API. Azure AI Foundry Models support serverless API endpoints with pay-as-you-go billing, and you can create only regional deployments for serverless API endpoints.Incorrect:[Not C]Managed compute does not support Foundry models.
https://learn.microsoft.com/en-us/azure/ai-foundry/concepts/deployments-overview
HOTSPOT (Drag and Drop is not supported)Select the answer that correctly completes the sentence.Hot Area:
Box: reliability and safetyWhen developing an AI system for self-driving cars, the Microsoft __________ principle for responsible AI should be applied to ensure consistent operation of the system during its lifespan.The Microsoft Reliability and Safety principle for responsible AI should be applied to self-driving cars to ensure consistent operation and mitigate risks. This principle mandates that AI systems must be developed to be dependable and perform as intended, even when facing unexpected situations, making it crucial for a system where a minor error could have severe outcomes.Consistent operation: Self-driving car AI must operate reliably and consistently under both normal and unexpected conditions.Robust safety measures: The principle requires rigorous testing and validation to ensure the system responds safely to edge cases and avoids unexpected performance failures.Preventing harm: The goal is to avoid creating harm by developing the system in alignment with its design ideas and values, which includes resisting manipulation.
https://support.microsoft.com/en-us/topic/what-is-responsible-ai-33fc14be-15ea-4c2c-903b-aa493f5b8d92
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