Artificial Intelligence Governance Professional (AIGP)
Embrace AI’s benefits and reduce risk by taking IAPP TRAINING
Protect your enterprise with trustworthy
AI governance
Artificial intelligence’s promise is tempered by persistent concerns about bias, data use, privacy and copyright. Despite those concerns, pressure to implement AI applications often outweighs enterprise’s abilities to weigh and reduce risk.
IAPP training provides the knowledge to meet your AI governance challenges. Our training programs develop professionals with the knowledge to reduce risk, improve compliance and increase brand loyalty by implementing appropriate controls and procedures. We can tailor programs to meet your enterprise’s specific learning needs through
in-person and online instruction. Embrace AI’s transformative potential by exploring your IAPP training options today.
Artificial Intelligence Governance Professional training is designed for any professional tasked with developing AI governance and risk management in their operations. It provides baseline knowledge and strategies for responding to complex risks associated with the evolving AI landscape. The AIGP curriculum was developed by a panel of
AI and governance experts.
It teaches AI’s technological foundations and development cycle, existing and emerging laws, risk management strategies and much more. It is excellent preparation for anyone pursuing IAPP Artificial Intelligence Governance Professional certification.
AI GOVERNANCE PROFESSIONAL TRAINING
This training teaches critical artificial intelligence governance concepts that are also integral to the AIGP certification exam. While not purely a “test prep” course, this training is appropriate for professionals who plan to certify, as well as for those who want to deepen their AI governance knowledge. Both the training and the exam are based on the same body of knowledge.
Module 1: Foundations of artificial intelligence
Defines AI and machine learning, presents an overview of the different types of AI systems and their use cases, and positions AI models in the broader socio-cultural context.
Defines AI and machine learning, presents an overview of the different types of AI systems and their use cases, and positions AI models in the broader socio-cultural context.
Module 2: AI impacts on people and responsible AI principles
Outlines the core risks and harms posed by AI systems, the characteristics of trustworthy AI systems, and the principles essential to responsible and ethical AI.
Outlines the core risks and harms posed by AI systems, the characteristics of trustworthy AI systems, and the principles essential to responsible and ethical AI.
Module 3: AI development life cycle
Describes the AI development life cycle and the broad context in which AI risks are managed.
Describes the AI development life cycle and the broad context in which AI risks are managed.
Module 4: Implementing responsible AI governance and risk management
Explains how major AI stakeholders collaborate in a layered approach to manage AI risks while acknowledging AI systems’ potential societal benefits.
Explains how major AI stakeholders collaborate in a layered approach to manage AI risks while acknowledging AI systems’ potential societal benefits.
Module 5: Implementing AI projects and systems
Outlines mapping, planning and scoping AI projects, testing and validating AI systems during development, and managing and monitoring AI systems after deployment.
Outlines mapping, planning and scoping AI projects, testing and validating AI systems during development, and managing and monitoring AI systems after deployment.
Module 6: Current laws that apply to AI systems
Surveys the existing laws that govern the use of AI, outlines key GDPR intersections, and provides awareness of liability reform.
Surveys the existing laws that govern the use of AI, outlines key GDPR intersections, and provides awareness of liability reform.
Module 7: Existing and emerging AI laws and standards
Describes global AI-specific laws and the major frameworks and standards that exemplify how AI systems can be responsibly governed.
Describes global AI-specific laws and the major frameworks and standards that exemplify how AI systems can be responsibly governed.
Module 8: Ongoing AI issues and concerns
Presents current discussions and ideas about AI governance, including awareness of legal issues, user concerns, and AI auditing and accountability issues.
Presents current discussions and ideas about AI governance, including awareness of legal issues, user concerns, and AI auditing and accountability issues.
Artificial Intelligence Governance Professional (AIGP)
Prepare for Your AIGP Exam
With the expansion of AI technology, there is a need for professionals in all industries to understand and execute responsible AI governance. The AIGP credential demonstrates that an individual can ensure safety and trust in the development and deployment of ethical AI and ongoing management of AI systems. These documents, as well as additional certification resources, can be found here.
