Microsoft Responsible AI
Principles and approach
We're committed to developing AI systems in a way that is transparent, reliable, and worthy of trust.
The Microsoft Responsible AI Standard
Explore guidance from Microsoft on how to design, build, and test AI systems.
Principles
Defining what’s important
We've identified six principles that we believe should guide AI development and use.
Fairness
AI systems should treat all people fairly.
How might an AI system allocate opportunities, resources, and information in ways that are fair to the humans who use it?
How might an AI system allocate opportunities, resources, and information in ways that are fair to the humans who use it?
Reliability and safety
AI systems should perform reliably and safely.
How might a system function well for people across different use conditions and contexts, including ones that it wasn’t originally intended for?
How might a system function well for people across different use conditions and contexts, including ones that it wasn’t originally intended for?
Privacy and security
AI systems should be secure and respect privacy.
How might a system be designed to support privacy and security?
How might a system be designed to support privacy and security?
Inclusiveness
AI systems should empower everyone and engage all people, regardless of their backgrounds. How might a system be designed to be inclusive for people of all abilities?
Transparency
AI systems should be understandable.
How can we ensure that people correctly understand the capabilities of a system?
How can we ensure that people correctly understand the capabilities of a system?
Accountability
People should be accountable for AI systems. How can we create oversight so that humans can be accountable and in control?
How Microsoft implements responsible AI
Explore how Microsoft empowers employees across the organization to be champions of responsible AI.
- We set rules for enacting responsible AI and clearly define roles and responsibilities for teams involved.
- We foster readiness to adopt responsible AI practices, both within our company and with our customers and partners.
- We review sensitive use cases to ensure we are upholding our responsible AI principles.
- We work to shape new laws and standards to help ensure that the promise of AI is realized for society at large.
- Researchers in Aether, Microsoft Research, and our engineering teams keep our Responsible AI Standard on the leading edge.
- Teams conduct rigorous AI research, including on transparency, fairness, human-AI collaboration, privacy, security, safety and the impact of AI on people and society.
- Our researchers actively participate in broader discussions and debates to ensure that our responsible AI program integrates big-picture perspectives and input.
- Engineering teams define and operationalize a tooling and system strategy for using AI responsibly.
- Engineering leaders identify and implement engineering practices that integrate responsible AI into everyday work.
- Engineering teams implement compliance tooling to help monitor and enforce responsible AI rules and requirements.
Responsible AI Transparency Report
Explore the inaugural report to see how Microsoft builds responsible AI systems, supports customers, and grows a stronger AI community.
30 responsible AI tools with over 100 features
16.6% growth in responsible AI community members
33+ Transparency Notes since 2019
Transparency documents
Transparency documents
Understand how our AI technology works, so you can create a system that fits your needs.
Azure AI Face
Enhance efficiency, security, and customer experiences with systems that analyze people’s faces.
Anomaly Detector
Analyze time series data using timestamps and numerical metrics to receive the anomalous status of each data point along with contributing variables.
Azure AI Search
Get AI-enhanced tools, APIs, and SDKs for building rich search experiences for diverse content in web, mobile, and enterprise apps.
Speech to text
Convert spoken audio into text to support more than 140 locales (part of Azure AI services).
Spatial Analysis
Enable advanced natural language video search using vector-based matching on vision and speech transcripts.
Custom named entity recognition
Use machine learning in a cloud-based API service to build models for extracting domain-specific entities from unstructured text.
Pronunciation Assessment
Evaluate speech pronunciation in multiple languages for feedback on accuracy, fluency, vocabulary, grammar, and topic understanding.
Text to speech
Convert written text into high-quality speech audio while supporting prebuilt, custom neural voices and offering visual capabilities with synthetic video avatars.
Frequently asked questions
- AI principles are guidelines designed to ensure the responsible development and deployment of AI technologies. These principles are crucial because they help mitigate risks, promote ethical practices, and maximize the benefits of AI for society.
The Responsible AI Standard at Microsoft consolidates essential practices to ensure compliance with emerging AI laws and regulations. - Microsoft offers a range of tools and practices to help organizations practice responsible AI.
Additionally, the Responsible AI Standard at Microsoft helps define product development requirements for responsible AI. - Transparency Notes are created to help customers better understand the inner workings of AI technologies and make more informed decisions about their use. They are part of the Responsible AI Standard and are intended to support responsible AI development by providing insights into how AI systems are governed, mapped, measured, and managed.
Microsoft also offers the Responsible AI Transparency Report, which provides insights into how Microsoft builds apps with generative AI, oversees the deployment of those apps, supports customers as they build their own AI apps, and fosters a responsible AI community.
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AI policy and regulation
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