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Responsible engineering refers to the principles and practices that help ensure that technology is developed and deployed ethically and sustainably. Responsible engineering in Azure encompasses a broad range of initiatives to create technology that benefits society while minimizing negative impacts. To foster trust and drive positive change in your technology, integrate ethical principles and sustainability into your design and development processes.
Harms modeling
Harms modeling is an informal framework for product teams that examines how technology can negatively affect people's lives in the following areas:
- Injuries
- Denial of consequential services
- Infringement on human rights
- Erosion of democratic and societal structures
Similar to security threat modeling, harms modeling enables product teams to anticipate potential real-world impacts of technology, which is a cornerstone of responsible development.
Responsible AI
Azure responsible AI practices are designed to ensure that AI technologies are developed and deployed ethically, transparently, and with consideration for potential effects on individuals and society.
Transparency documents describe the capabilities and limitations of Microsoft technologies. Transparency documents support responsible AI because they help you ensure that your solutions are ethically sound and align with responsible AI practices.
Azure AI services provides information and guidelines about how to responsibly use AI in applications.
Sustainability
The sustainability workload guidance in the Azure Well-Architected Framework includes recommendations and principles to increase cloud efficiency across Azure workloads. This guidance aligns with the Green Software Foundation for an improved sustainability posture to help create new business value while reducing operational footprint. This guide helps drive innovation responsibly by evaluating the impact that workload design decisions have on the climate. It also provides concrete advice about how to build for a better tomorrow.