IEEE CertifAIEd™ Product Certification

While autonomous intelligent systems (AIS) provide countless opportunities to significantly increase productivity and improve the quality of life, this rapidly evolving technology is faced with many challenges and barriers to success.

How do you address the concerns that this technology is being deployed without proper AI ethical considerations when there is no generally accepted test or standard approach?

IEEE CertifAIEd is a certification program for assessing the ethics of Autonomous Intelligent Systems (AIS) to help protect, differentiate, and grow product adoption. The resulting certificate and mark are a demonstration of an AIS product’s ethical implications to deliver solutions and peace of mind to developer organizations.

The IEEE CertifAIEd program has been designed on the basis of input provided by global stakeholders since 2018 through an open process. The goal of this program is to help individuals and stakeholders learn techniques and tools to help organizations develop and implement AI technologies in a responsible and ethical manner. This program directly addresses the global need to drive the ethical, safe, and responsible development and use of products and systems using AI techniques.

The IEEE CertifAIEd Program offers benefits to organizations by helping them:

• Assess the ethicality of your AIS
• Demonstrate ethical consideration
• Address legislation and regulatory mandates
• Reduce liability and risk
• Differentiate your product
• Grow product adoption

The IEEE CertifAIEd Assessment process is a collaboration between an organization’s development team and IEEE authorized experts and consists of four core phases:

• Soft or socio-technical attributes are difficult to demonstrate compliance to the marketplace without broadly accepted and proven certification schemes from recognized entities.
• AI Ethics expertise available to large companies is not necessarily available to small and mid-size enterprises; increasing the competitive gaps and challenging resource prioritization to earn compliance where necessary.
• Research has shown bias in AI-based systems producing detrimental results to people of color, gender, and more. The negative brand perception and impact can easily extend into the millions in loss of revenues and business. Further, the trusted relationship with an Entity’s stakeholders are not easily repaired.