New technology comes with unknown obstacles and unintended risks requiring accountable design and lifecycle planning to ensure responsible innovation. As artificial intelligence, autonomous intelligent systems (AIS), machine learning, autonomous vehicles, and robotics advance at a rapid pace, careful considerations need to be made during development and implementation regarding humanity. At IEEE SA, our global community has developed resources and standards globally recognized in the area of applied ethics and systems engineering and continue to develop accessible and sustainable approaches and solutions for pragmatic application of AIS principles and frameworks. IEEE SA offers standards, training and education, certification programs, and more, to empower stakeholders designing, developing, and using Autonomous Intelligent Systems (AIS). Global participation is encouraged to offer the broadest regional and cultural perspectives required to best contextualize how AIS systems can avoid risk and offer greatest benefit in operation.
IEEE CertifAIEd™: The Mark of AI Ethics
For assessing ethics of Autonomous Intelligent Systems (AIS) to help protect, differentiate, and grow product adoption.
GET Program for AI Ethics and Governance Standards
IEEE AI Ethics and Governance Standards now available for download at no cost.
Programs and Services
IEEE CertifAIEd™ is a certification program for assessing ethics of Autonomous Intelligent Systems (AIS) to help protect, differentiate, and grow product adoption. The resulting certificate and mark demonstrates the organization’s effort to deliver a solution with a more trustworthy AIS experience to their users.
Artificial Intelligence and Ethics in Design Course Program
This educational program offers 10 courses focused on ethics in design of artificial intelligence systems.
New Program for Free Access to AI Ethics and Governance Standards
Program brings socio-technical standards providing guidance and considerations to aid the development of trustworthy AI to the global community at no cost
Learn more about how to engage with AIS related Communities and Industry Connections Programs.
The Global Initiative on Ethics of Autonomous and Intelligent Systems
This community’s mission is to ensure every stakeholder involved in the design and development of autonomous and intelligent systems is educated, trained, and empowered to prioritize ethical considerations so that these technologies are advanced for the benefit of humanity via publications like Ethically Aligned Design and the IEEE 7000 series.
Pre-Standardization Activities On Industrial AI
Industrial AIS differs from consumer AIS applications. Participants from large and small corporations, academia, industry, and government agencies collaborate to identify possible overlaps between industrial automation and industrial AI requirements and identify potential gaps that need to be bridged by new standards.
AI Systems Governance for Cities
The goal of the AI-Driven Innovation for Cities and People Team is to provide cities a mechanism to support responsible AIS innovation through proper governance mechanisms.
The Open Community for Ethics in Autonomous and Intelligent Systems (OCEANIS)
Socio-technical standards can elevate and further the development of AIS solutions. This forum offers collaboration between relevant national and international organizations to foster locally and globally applicable solutions that support technical, business, and policy decisions.
Children's Tech Design Governance
A group of key industry, government, and policy stakeholders focus on developing standards and establishing frameworks and processes for age appropriate digital services and protecting children’s data.
IEEE CertifAIEd™ Awareness
This 20-minute awareness module to help decision makers and other concerned parties get a general overview of AI ethics’ importance to their business, and how to address it in their AIS with IEEE CertifAIEd™.
AIS Related Standards
IEEE 7000™ IEEE Standard Model Process for Addressing Ethical Concerns during System Design
IEEE 7001™ IEEE Standard for Transparency of Autonomous Systems
IEEE P7002™ IEEE Standard for Data Privacy Process
IEEE P7003™ Algorithmic Bias Considerations
IEEE P7004™ Standard for Child and Student Data Governance
IEEE P7004.1™ Recommended Practices for Virtual Classroom Security, Privacy and Data Governance
IEEE 7005™ IEEE Standard for Transparent Employer Data Governance
IEEE 7007™ IEEE Ontological Standard for Ethically Driven Robotics and Automation Systems
IEEE P7008™ Standard for Ethically Driven Nudging for Robotic, Intelligent and Autonomous Systems
IEEE P7009™ Standard for Fail-Safe Design of Autonomous and Semi-Autonomous Systems
IEEE 7010™-2020 IEEE Recommended Practice for Assessing the Impact of Autonomous and Intelligent Systems on Human Well-Being
IEEE P7010.1™ Recommended Practice for Environmental Social Governance (ESG) and Social Development Goal (SDG) Action Implementation and Advancing Corporate Social Responsibility
IEEE P7011™ Standard for the Process of Identifying and Rating the Trustworthiness of News Sources
IEEE P7012™ Standard for Machine Readable Personal Privacy Terms
IEEE P7014™ Standard for Ethical considerations in Emulated Empathy in Autonomous and Intelligent Systems
IEEE P7015™ Standard for Data and Artificial Intelligence (AI) Literacy, Skills, and Readiness
IEEE P3109™ Standard for Arithmetic Formats for Machine Learning
IEEE 3652.1™-2020 IEEE Guide for Architectural Framework and Application of Federated Machine Learning
IEEE P3127™ Guide for an Architectural Framework for Blockchain-based Federated Machine Learning
IEEE P3187™ Guide for Framework for Trustworthy Federated Machine Learning
IEEE P2986™ Recommended Practice for Privacy and Security for Federated Machine Learning
IEEE P2805.3™ Cloud-Edge Collaboration Protocols for Machine Learning
IEEE 2830™-2021 IEEE Standard for Technical Framework and Requirements of Trusted Execution Environment based Shared Machine Learning
IEEE P3123™ Standard for Artificial Intelligence and Machine Learning (AI/ML) Terminology and Data Formats
IEEE P1900.8™ Standard for Training, Testing, and Evaluating Machine-Learned Spectrum Awareness Models
IEEE P3157™ Recommended Practice for Vulnerability Test for Machine Learning Models for Computer Vision Applications
Ethically Aligned Design (EAD):
- EAD For Business
- EAD, First Edition
- EAD, First Edition – Overview
- Defining A/IS Ethics – Glossary
- AI Ethics for Solutions Developers
- IEEE CertifAIEd™ – Ontological Specification for Ethical Transparency
- IEEE CertifAIEd™ – Ontological Specification for Ethical Algorithmic Bias
- IEEE CertifAIEd™ – Ontological Specification for Ethical Accountability
- IEEE CertifAIEd™ – Ontological Specification for Ethical Privacy
- AI Ethics Support Badge
Children’s Data Governance:
- IEEE SA Children’s Data Governance Applied Case Study Report
- Applied Case Studies for Designing Trustworthy Digital Experiences for Children
8 Examples of Protecting Children’s Data Privacy and Fostering a Positive Experience
Measuring What Matters in the Era of Global Warming and the Age of Algorithmic Promises
Report: Decoupling Human Characteristics from Algorithmic Capabilities
Report: Addressing Ethical Dilemmas in AI: Listening to Engineers
The IEEE CertifAIEd Framework for AI Ethics Applied to the City of Vienna
How To Make Autonomous Systems More Transparent and Trustworthy
Measurementality, is a series of podcasts, webinars, and reports created by IEEE SA in collaboration with The Radical AI Podcast and explores what measurements of success we’re optimizing for AIS development.
Webinar: Is it Technically Possible to Make the World Age Appropriate
Today, one in three people online is under 18. There is an urgent need to address the vulnerabilities and evolving capacities associated with children and their online experiences.
IEEE Course Program on AI Standards
The purpose of this course series is to provide instructions for a comprehensive approach to creating ethical and responsible digital ecosystems.
IEEE Course Program on Artificial Intelligence and Ethics in Design
Responsible artificial intelligence, law, compliance, and ethics in artificial intelligence and practical applied ethics for use in the responsible design of artificial intelligence systems.