In the Azure Developers JavaScript Day 2024, Maya Shavin a Senior Software Engineer at Microsoft, presented a session called "Have a safe coffee chat with your documentation using Azure AI Services". And she introduced innovative approaches for integrating AI technologies to ensure the safety of document-based Q&A systems.
Let's dive into the content!
What was covered during the session?
Now let's talk about what was covered during the session! If you wish, you can watch the video of the session at the link below:
Introduction to AI-Powered Safety in Documentation
Maya opened her presentation by introducing her background in Microsoft's industrial AI division, where she focuses on incorporating AI technologies into industry-specific applications. With over a decade of experience in both Front-End and Back-End development, she also highlighted her contributions to the Tech Community as an author and Community Organizer.
Concept of Document Q&A Assistant
Maya described the document Q&A assistant as a straightforward interaction system where an AI, not a human, responds to user queries. The system processes in two primary phases:
- Injection Phase: here, documents are uploaded, segmented, indexed with metadata and stored in a searchable database.
- Query Phase: the phase where the AI retrieves and summarizes relevant document sections in response to user queries.
The Importance of Content Moderation
A significant portion of her talk focused on content moderation, crucial for preventing inappropriate or harmful content from undermining the AI system's integrity. She explained how AI responses could potentially reflect, or be influenced by, the offensive content within user inputs. To combat this, Microsoft promotes responsible AI practices structured around in:
- Fairness: AI systems should treat all people fairly.
- 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.
- Transparency: AI systems should be understandable.
- Accountability: People should be accountable for AI systems.
For more information on Microsoft's Responsible AI Practices, visit the link.
Azure AI Content Safety
Maya introduced Azure AI Content Safety, a pivotal service for detecting harmful content in both user inputs and AI-generated responses. This service supports multiple programming languages and offers a studio experience for testing various content sensitivity levels. Its primary features include:
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Text Analysis API: Scans text for sexual content, violence, hate, and self-harm with multi-severity levels.
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Image Analysis API: Scans images for sexual content, violence, hate, and self-harm with multi-severity levels.
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Text Blocklist Management APIs: The default AI classifiers are sufficient for most content safety needs; however, you might need to screen for terms that are specific to your use case. You can create blocklists of terms to use with the Text API.
To understand how Azure AI Content Safety works, there's a video below about the service:
Demonstrating Azure AI Content Safety in Action
Maya demonstrated how to integrate Azure AI Content Safety into a JavaScript project. She showcased a function that analyzes content and adjusts responses based on predefined sensitivity levels, thus preventing the system from providing harmful output.
This function works by categorizing content into several types of sensitive material—like hate speech, sexual content, and violence—and filtering them accordingly.
She also mentioned the use of the Azure AI Content Safety SDK for JavaScript/TypeScript, which you can find at the link
Comparing Azure AI Content Safety and Azure OpenAI Content Filters
Maya also compared the Azure AI Content Safety with OpenAI’s content filtering features. She highlighted that while Azure AI Content Safety is versatile and can be integrated into various AI workflows, OpenAI's content filtering is bundled with their services and might not incur additional costs.
However, Azure AI Content Safety offers more control over the moderation process and supports more languages.
Final Thoughts and Steps Forward
Concluding her talk, Maya stressed the ongoing need for manual oversight in content moderation to ensure that AI interactions remain appropriate and effective. She encouraged attendees to implement Azure AI content safety in their projects to enhance the security layers of their AI applications.
Maya Shavin’s session provided valuable insights into the mechanisms of safeguarding AI-driven document assistants, ensuring that they operate within the realms of safety and ethics dictated by modern AI standards.
Azure Developers JavaScript Day Cloud Skills Challenge
Don't forget to participate in the Azure Developers JavaScript Day Cloud Skills Challenge to test your knowledge and skills in a series of learn modules and learn more about Azure services and tools. As I mentioned in the previous articles, besides the challenge is over, you can still access the content and learn more about the topics covered during the event.
Link to the challenge: JavaScript and Azure Cloud Skills Challenge
Additional Resources
If you want to learn more about Azure AI Content Safety Services, especially if you're JavaScript Developer, you can access the following resources:
- Azure AI Content Safety
- Azure AI Content Safety SDK for JavaScript/TypeScript
- Documentation - Azure AI Content Safety REST client library for JavaScript - version 1.0.0
Stay Tuned!
If you wish, you can follow what happened during the two days of the event via the playlist on YouTube. The event was full of interesting content and insights for JavaScript developers!
If you are a JavaScript/TypeScript developer, follow me on Twitter or LinkedIn Glaucia Lemos for more news about the development and technology world! Especially if you are interested in how to integrate JavaScript/TypeScript applications with the Azure, Artificial Intelligence, Web Development, and more!
And see you in the next article!