
Explore the global AI regulatory landscape, key regulations and frameworks, and practical implementation tips to govern AI risks and drive responsible innovation.
Explore ai basics, ai risks, and why regulations and frameworks for ai governance and security matter for preventing biased decisions and real-world examples of ai failures.
Explore the global landscape of ai frameworks and regulations, including OECD principles, ISO standards, and the NIST risk management framework, to govern ai development.
Explore the EU AI Act’s risk-based framework that classifies AI into minimal, limited, high, and unacceptable risk, with high-risk conformity and global benchmarking against GDPR.
Explore a practical case study on enforcing the EU AI Act by inventorying and classifying AI systems, assessing high-risk tools, implementing governance, gap analysis, documentation, training, and transparent deployment monitoring.
Explore the NIST AI risk management framework overview, detailing foundational concepts and core practices for identifying, assessing, and mitigating AI risks, guiding governance and trustworthy AI.
Apply the NIST RMF case study to govern, map, measure, and manage AI risk through governance, mapping, measuring, and policies, with training that drives cultural change.
Explore ISO 4201 AI management system, a standardized AI management framework with risk-based controls, plan do check act, and third-party certification, aligned with EU act and other ISO standards.
Apply the pdca cycle to implement ISO 42001 AI management systems, from scoping and impact risk assessments to controls, audits, and continual improvement for trusted, responsible AI.
Learn Google's secure AI framework (SAIF) and its core elements: security foundations, threat detection and response, automated defenses, platform controls, adaptive mitigations, and contextual AI risk to secure AI systems.
See how a global bank uses the Google secure ai framework to deploy ai-powered chatbots with natural language processing, backed by risk assessment and strong data security.
Discover the AWS generative AI security scoping matrix, detailing five deployment scopes and the governance, risk management, and controls needed to secure public, enterprise, and foundation models.
Learn how to apply multiple AI governance frameworks—EU AI regulation, ISO 44201, ISO 27001, and Google Safe—by focusing on trustworthiness, risk management, and governance.
Apply an AI governance framework within your company, using standards like Google or ISO, to implement governance and risk management while staying updated on industry trends.
In the rapidly advancing domain of Artificial Intelligence, navigating the complex web of frameworks and regulations is crucial for ensuring ethical deployment and governance. This comprehensive course provides an in-depth exploration of key AI frameworks and regulations, including the EU AI Act, NIST AI RMF, Google's SAIF, and ISO 42001, equipping you with the knowledge to navigate the legal and ethical landscape of AI development and deployment.
What You Will Learn
The critical role and implications of AI regulations and frameworks in the modern technological landscape.
Detailed insights into major AI regulations and frameworks: the EU AI Act, NIST AI RMF, Google's SAIF, and ISO 42001.
The process of aligning AI projects with international standards and legal requirements.
Case studies demonstrating the application and impact of these frameworks and regulations.
Course Outline
Introduction to AI Regulations and Frameworks
Overview of AI and its transformative potential.
The importance of ethical and regulatory frameworks in AI.
Diving Deep into AI Frameworks and Regulations
Understanding the EU AI Act: Scope, requirements, and implications.
Exploring the NIST AI RMF: Principles, practices, and application.
Google's SAIF: A model for secure AI development.
ISO 42001: Creating an AI Management System
Case Studies
Analysis of successful and challenging implementations of AI regulations.
Lessons learned from real-world applications.
Who Should Take This Course
This course is tailored for individuals keen on mastering the legal and ethical dimensions of AI, including:
AI and Machine Learning Engineers
Data Scientists
Legal Professionals in Technology
Cybersecurity Professionals
Policy Makers and Regulators
Ethical AI Advocates
Prerequisites
A foundational understanding of AI concepts and technologies is recommended, but no prior knowledge of specific regulations or legal frameworks is required.
Join us on this journey to demystify the complex landscape of AI regulations and frameworks, ensuring your AI initiatives are not only innovative but also responsible and compliant.
Instructor
Taimur Ijlal is a multi-award winning, information security leader with over 20+ years of international experience in cyber-security and IT risk management in the fin-tech industry. Strong knowledge of ISO 27001, PCI DSS, GDPR, Cloud Security, DevSecOps and winner of major industry awards in the Middle East such as CISO of the year, CISO top 30, CISO top 50 and Most Outstanding Security team.