Guidance for integration and responsible use with Azure Cognitive Service for language
Microsoft wants to help you responsibly develop and deploy solutions that use Azure Cognitive Service for language. We are taking a principled approach to upholding personal agency and dignity by considering the fairness, reliability & safety, privacy & security, inclusiveness, transparency, and human accountability of our AI systems. These considerations are in line with our commitment to developing Responsible AI.
This article discusses Azure Cognitive Service for language features and the key considerations for making use of this technology responsibly. Consider the following factors when you decide how to use and implement AI-powered products and features.
When you're getting ready to deploy AI-powered products or features, the following activities help to set you up for success:
Understand what it can do: Fully assess the capabilities of any AI model you are using to understand its capabilities and limitations. Understand how it will perform in your particular scenario and context.
Test with real, diverse data: Understand how your system will perform in your scenario by thoroughly testing it with real life conditions and data that reflects the diversity in your users, geography and deployment contexts. Small datasets, synthetic data and tests that don't reflect your end-to-end scenario are unlikely to sufficiently represent your production performance.
Respect an individual's right to privacy: Only collect data and information from individuals for lawful and justifiable purposes. Only use data and information that you have consent to use for this purpose.
Legal review: Obtain appropriate legal advice to review your solution, particularly if you will use it in sensitive or high-risk applications. Understand what restrictions you might need to work within and your responsibility to resolve any issues that might come up in the future. Do not provide any legal advice or guidance.
System review: If you're planning to integrate and responsibly use an AI-powered product or feature into an existing system of software, customers or organizational processes, take the time to understand how each part of your system will be affected. Consider how your AI solution aligns with Microsoft's Responsible AI principles.
Human in the loop: Keep a human in the loop, and include human oversight as a consistent pattern area to explore. This means constant human oversight of the AI-powered product or feature and maintaining the role of humans in decision-making. Ensure you can have real-time human intervention in the solution to prevent harm. This enables you to manage where the AI model doesn't perform as required.
Security: Ensure your solution is secure and has adequate controls to preserve the integrity of your content and prevent unauthorized access.
Customer feedback loop: Provide a feedback channel that allows users and individuals to report issues with the service once it's been deployed. Once you've deployed an AI-powered product or feature it requires ongoing monitoring and improvement – be ready to implement any feedback and suggestions for improvement.
Learn more about Responsible AI
- Microsoft Responsible AI principles
- Microsoft Responsible AI resources
- Microsoft Azure Learning courses on Responsible AI
- Transparency note for Azure Cognitive Service for language
- Transparency note for Named Entity Recognition and Personally Identifying Information
- Transparency note for the health feature
- Transparency note for Key Phrase Extraction
- Transparency note for Language Detection
- Transparency note for Question answering
- Transparency note for Summarization
- Transparency note for Sentiment Analysis
- Data Privacy and Security for Azure Cognitive Service for language