ISO/IEC 42001 — AI Management (Awareness)

By the end

What you'll build

• Describe the stages of an AI system lifecycle and the main risk at each stage
• Ask useful governance questions before an AI system is procured or built
• Identify where human oversight is required in a proposed AI-supported process
• Recognise signs of bias, drift or unsafe reliance in an AI output you receive
• Explain data provenance and why training data sources matter
• Follow the correct internal route to raise a concern about an AI system's behaviour

Curriculum

What's inside

6 modules · 35 lessons

1. 01

   Why AI needs management

   6 lessons
   • What makes AI systems different from ordinary software to govern
   • AI, machine learning and automation: useful distinctions
   • Where the risk sits: data, model, deployment, use
   • Roles people play in an AI system without noticing
   • What responsible AI means in operational terms
   • + 1 more lesson
2. 02

   The AI lifecycle

   6 lessons
   • Purpose, data, build, deploy, monitor: the questions at each stage
   • Defining intended purpose and out-of-scope use
   • Data provenance, quality and consent
   • Testing and validation before release
   • Monitoring, drift and retirement
   • + 1 more lesson
3. 03

   Risks and impacts

   6 lessons
   • Recognising bias and unfair outcomes in a system you use
   • Transparency, explainability and their limits
   • Security and misuse of AI systems
   • Over-reliance and automation complacency
   • Impact on people affected by an automated decision
   • + 1 more lesson
4. 04

   Oversight and control

   6 lessons
   • Designing meaningful human oversight rather than a rubber stamp
   • Approval gates for new AI use cases
   • Third-party and vendor-supplied AI considerations
   • Documentation an AI system should carry
   • Incident handling when an AI system misbehaves
   • + 1 more lesson
5. 05

   Working with AI responsibly

   6 lessons
   • Everyday rules for using AI tools at work
   • What information should never go into a general-purpose tool
   • Checking output before you act on it
   • Attribution, confidentiality and intellectual property care
   • Raising a concern about an AI system
   • + 1 more lesson
6. 06

   Practice and check

   5 lessons
   • Signals in an AI systemmatch pairs
   • Introducing an AI tool into a real decisionsequence order
   • AI management: the exact wordfill blank
   • The shortlisting assistantscenario
   • Course quizquiz

The shape of it

How this course works