AI Ethics
Assessor Training

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Learn how to address social responsibility in autonomous intelligent systems while improving your current business model: join a community of like-minded AI Ethics experts in mastering the IEEE CertifAIEd™ approach. 

Training objectives

This course has been developed for IEEE CertifAIEd Authorized Assessors who perform assessments or review cases for certification in AI Ethics.

Participants will learn to assess Autonomous and Intelligent Systems (AIS) for their conformity to ethical privacy, transparency, accountability, and algorithmic bias criteria required by the IEEE CertifAIEd Program.
This training is an integral first step to become recognized as an IEEE CertifAIEd Authorized Assessor.

Who is the training for?

There are no prerequisites for attending the training, however, participants with a background in ethics, artificial intelligence, standards, certification programs and conformity assessment will benefit most.

Participation is encouraged for those interested in advancing their knowledge in AI Ethics Certification, including: 
Compliance Officers, Governance Managers, Business Analyst, AI Engineer, Machine Learning Engineer, Data Analyst, Data Engineer, Data Scientist, Data Architect, Product Managers, Technology Consultants, Data Protection Managers, Quality Managers, Risk Managers, Software Developers, System Administrators, Purchasing Managers, Management Consultants, Information Security Managers, Process Auditors

Why CertifAIEd™ training?

This training is developed as a part of IEEE’s approach to Ethics in AIS. 
Participants will learn about the importance of a mark that distinguishes achieving ethical criteria for AIS products, services, and systems, how to assess the ethicality of an AIS, and how to get it recognized in the field with a mark of ethics that meet ethical criteria.
  • IEEE CertifAIEd offers a comprehensive suite of criteria to evaluate and assess AIS products, services, or systems against specific ethical requirements to foster trust and advance technology for the benefit of humanity.
  • It offers a framework to contextualise AI Ethics criteria for an application helping to deliver a more trustworthy experience for users.

Successful completion of the IEEE CertifAIEd  Authorized Assessor training is an essential aspect of becoming an IEEE CertifAIEd Authorized Ecosystem Collaborator.

Training outcomes

From initial awareness to in-depth understanding of certification criteria, the methodology and the ecosystem, you will:
  • undergo training in the key principles of AI Ethics and the IEEE CertifAIEd criteria and certification process
  • obtain a deep understanding of how to scrutinize products, services, and systems from an ethical perspective
  • learn about the importance of having a mark that distinguishes AIS products, services, and systems that meet ethical criteria
  • gain knowledge of the fundamental concepts and processes that are the basis of profiling, assessment, and certification activities
Upon successful completion of the training and exam, trainees are eligible to apply to become IEEE CertifAIEd Authorized Assessors. They will then have to fulfill the Assessor Ethics Competence requirements.
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Training content

Module 1
Module 2
Module 3
Module 4
  • Why act now & Background of the CertifAIEd program
  • Introduction of the IEEE AI Ethics Certification System
  • Transparency Criteria
  • Use Case Analysis for Transparency
  • Learning Check for Transparency
  • Accountability Criteria
  • Use Case Analysis for Accountability
  • Algorithmic Bias Criteria
  • Use Case Analysis for Algorithmic Bias
  • Learning Check for Accountability and Algorithmic Bias
  • Ethical Privacy Criteria
  • Use Case Analysis for Ethical Privacy
  • Additional Use Case Analysis for “selected criteria”
  • Q&A session for any open issues
  • Learning Check for Privacy
  • Introduction to Assessment and Certification
  • Assessment Tools and Resources
  • Simulation of an Assessment
  • Final Exam-Virtual Environment Setup
  • Conducting Practical Check
  • Closing the Training and the Next Steps

Training delivery

The sessions are designed as Virtual Instructor-Led Training (VILT) and include online training, interactive learning, self-study assessments on real-life cases, and learning checks during and at the end of the course.

Instructor-led training sessions will take place between:
09:00 am - 05:30 pm UTC (Coordinated Universal Time)
09:00 am – 05:30 pm CST (China Standard Time)
09:00 am - 05:30 pm EST (Eastern Standard Time)

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Training instructors


Prof. Ali Hessami

Ali Hessami is currently the Director of R&D and Innovation at Vega Systems, London, UK. He has an extensive track record in systems assurance and safety, security, sustainability, knowledge assessment/management methodologies. 


Patricia Shaw

CEO and Founder of Beyond Reach Consulting Limited, UK
Trish advises and trains organisations internationally on Responsible AI (AI/data ethics, policy, governance), and Corporate Digital Responsibility.


Ruth Lewis

BsC Electrical Engineering, Graduate Diploma Digital Communications, MsC Strategic Foresight
Principal of Technology Foresight
Ruth is an experienced strategic IT consultant, qualified futurist and professional engineer with 30+ years of experience. She is the Chair of the IEEE Society on Social Implications of Technology (SSIT) Standards Committee.

What does our Alumni say about the training?

#unique | #comprehensive | #practical #whatweneednow

AIOps/MLOps Engineer, 
AI Entrepreneur
LAMIC Research Group
Manager Technologie & Innovation
OVE Österreichischer Verband für Elektrotechnik
Doruk Ozulu
Managing Director EFOSS Consulting, Trade and Industrial Corp.

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