ISO for Artificial Intelligence: ISO 42001 and beyond

Covers Other ISO standards of relevance : ISO 23053, ISO 5338, ISO 38507, ISO 24027, ISO 24028, ISO 24029

What you'll learn
What is ISO 42001
Why we need ISO 42001
What are the other ISO standards that influence AI deployment
What are the AI lifecycle processes
What are the steps in ML pipeline that align with AI lifecycle processes
What are the best practices in managing risks in AI deployment
What are the guidelines to reduce bias in AI systems
What are the best practices to improve the robustness of neural networks
What are the building blocks of AI governance, as per ISO standards

Requirements
Knowledge and/or experience in machine learning and artificial intelligence will be significantly advantageous.

Description
ISO 42001 is the first ISO standard defining a certifiable management system for AI. As a certifiable AI standard, it helps provide organisations with a mark of trustworthiness in AI use. This can help promote commercial scalability – vital for encouraging growth and expansion, because organization around the world are looking at making AI trustworthy through reputed standards like ISO. ISO 42001 focuses on managing AI responsibly at an organizational level, providing a framework for implementing effective AI governance and management systems.In this course, we’ll cover both AI concepts and the ISO standards relevant to AI. This course is taught by an IT veteran who has rich experience in AI deployments in large MNCs and Small and medium businesses.While ISO 42001 is the primary certifiable standard and our focus area, we cover other related standards since they address critical aspects of AI and are equally important.ISO 23053: Offers a structured framework for building and maintaining ML-centric AI systems, ensuring consistency and reliability throughout their lifecycle.ISO 5338: Provides a holistic lifecycle model for AI systems, complementing ISO 23053 by covering broader AI scenarios, including non-ML methods and extended operational phases.ISO 38507: Addresses AI governance, data governance, and risk management, offering a foundation for ethical and responsible AI system deployment.ISO TR 24027: Focuses on identifying, assessing, and mitigating bias in AI systems, promoting fairness and equity in AI outcomes. TR stands for technical report and we will explain that when we cover bias.ISO TR 24028: Explores trustworthiness in AI, addressing principles like transparency, reliability, and ethical considerations to build user confidence.ISO 24029: Provides guidance for evaluating the robustness of neural networks, ensuring they perform reliably under various conditions, including adversarial scenarios.Together, these standards form a comprehensive ecosystem for developing, deploying, and managing AI systems responsibly.

Who this course is for
CxO's
Senior Managers
IT Professionals
Machine Learning enthusiasts
Data Science professionals
Students