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Risk Academy, led by the Nexus Consortium · Technology and Digital Systems · Department of Artificial Intelligence and Autonomous Systems

Impact assessment, audit and assurance cases for AI systems

AI assurance and audit

Evaluating a model asks what it can do; assuring a system asks whether it is acceptable for a use, and who can show it.

01Scope

What the discipline covers

The subtopics its courses and labs teach.

Courses
In preparation
Levels
In development
Labs
In development
  • AI system impact assessment (ISO/IEC 42005)
  • AI risk management (ISO/IEC 23894 and NIST AI RMF)
  • Auditing AI management systems (ISO/IEC 42006)
  • Conformity assessment under the EU AI Act
  • Assurance cases and evidence
  • Documentation: model cards, system cards and technical files
  • Agentic AI assurance and oversight
  • Red teaming and third-party evaluation
  • Post-market monitoring and incident reporting
02Maps

Build a twin of any place

Search any place or open the world; the layers and generators follow aI assurance and audit on the planet map, the globe and in 3D.

West Cornwall: Goonhilly and the Porthcurno cable landings: a flat plan of the faculty twin. Terrain 0 to 245 m; 4 satellite dishes; 74 communication masts and towers; 12 telephone exchanges; 7 data centres and cable landing stations; 12 aerodromes; 1 telecom offices; Communication line 161 km; 729 known exploited vulnerabilities since 2023-10-17; Night-time lights, VIIRS day-night band: read live when the 3D twin opens. Contours every 25 metres from the elevation grid; communication cables by class; ground infrastructure as marks.
West Cornwall: Goonhilly and the Porthcurno cable landings, United Kingdom. Flat plan of the same data: relief as contours from the inline grid, the mapped ground infrastructure by kind, the mapped cables and the numbers below. The 3D twin opens on devices that can draw it, once its data and code have been checked.
  • Terrain 0 to 245 m
  • 4 satellite dishes
  • 74 communication masts and towers
  • 12 telephone exchanges
  • 7 data centres and cable landing stations
  • 12 aerodromes
  • 1 telecom offices
  • Communication line 161 km
  • 729 known exploited vulnerabilities since 2023-10-17
  • Night-time lights, VIIRS day-night band: read live when the 3D twin opens
Credits and dates per layer are listed under the stage. Relief in the twin is exaggerated ×1.5 for legibility.

Drag to move, right drag or Shift with a drag to turn and tilt, Ctrl with the wheel to zoom. Keyboard: arrows move, Shift with arrows turn and tilt, + and – zoom, 0 resets, V steps through the views, Escape clears.

Flat plan of the same data: relief as contours from the inline grid, the mapped ground infrastructure by kind, the mapped cables and the numbers below. The 3D twin opens on devices that can draw it, once its data and code have been checked.

The boundaries, names and designations shown do not imply any judgement on the legal status of any territory, or any endorsement or acceptance of such boundaries. Countries: Natural Earth (public domain).

03The subject

The subject, methods and measures and debates and bodies

The field and its scope

For auditors, compliance leads, risk officers and conformity assessment bodies who must turn evidence about an AI system into a justified, documented and reviewable judgement.

04The method

From a control list to an audit opinion: what a sample of records can establish

Control coverage is two figures, designed and operating; operating effectiveness is judged from a sample of records, and the sample size bounds the exception rate an auditor can rule out, so the opinion rests on how many records were pulled as much as on what they showed.

Sources: Raji et al., Closing the AI Accountability Gap: Defining an End-to-End Framework for Internal Algorithmic Auditing (2020); Mökander, Schuett, Kirk and Floridi, Auditing large language models: a three-layered approach (2023); Schuett, Three lines of defence against risks from AI (2023); European Parliament and Council, Regulation (EU) 2024/1689 on artificial intelligence (2024).

05At a glance

At a glance, hub, what is changing now and courses

AI assurance and audit at a glance

risksacademy.comtechnology-digitaldiscipline

AI assurance and audit: 0 primary courses open, 0 in preparation and 0 also taught here, across 9 subtopics. Courses: none yet.AI assurance and audit
AI assurance and audit at a glance
  • Open, 0
  • In preparation, 0
  • Subtopics, 9
Course codes from the curriculum; study levels L1 to L4.
Twin builderBuild a twin of any placeWorked example: West Cornwall: Goonhilly and the Porthcurno cable landings · 4 generators · 7 layers · 3 instruments
06Console

How AI assurance and audit is taught, as a process you can run

Press Play to run this process from this page's own data.

Process explorer

How AI assurance and audit is taught

14 steps5 stages

07Learning

Achievements, where this is practised, practised in and across the ecosystem

Achievements in this discipline

  1. Course achievements

    One for each course with this as its primary discipline, earned when you pass the course's assessed activities.

An achievement is a record of the learning completed and assessed here. See how recognition works.

08Take part

Take part in Technology and Digital Systems

Start from who you are.

09References

Core references and where to begin

Start with Raji, then National Institute of Standards, then Raji.

10Questions

Questions, answers and key terms

Is study here free?
Yes. Every course and learning material of Risk Academy, led by the Nexus Consortium, is free to study, self-paced or with a cohort. Ordinary participation has no fee; paid work, internships and fellowships are separate arrangements.
What does completing a course give me?
A completion record: the course, its version, the date and what was assessed, private by default and shared by you. It stacks into discipline, department and programme achievements. A record states what was studied and assessed and does not certify competence. A record is not a licence, a professional title or an employment status.
Where do the data and the places come from?
Every faculty teaches on a twin of a real place built from open data. Each layer carries its provider, licence and date, and every result on the Academy states its source. Maps and figures are indicators for teaching, never an assessment of a place.
How do I take part beyond the courses in aI assurance and audit?
Form a competence cell of three to seven people, study a shared pathway, take a supervised assignment in the National Working Groups, or bring a cohort from your institution. Open the page for organisations.

Key terms

Term

AI assurance

The processes that build and communicate justified confidence that an AI system meets its requirements.

Term

Impact assessment

A structured analysis of how an AI system may affect individuals, groups and society, as in ISO/IEC 42005:2025.

Term

Conformity assessment

The process of demonstrating that a high-risk AI system meets the requirements of the EU AI Act before it is placed on the market.

Term

Assurance case

A structured argument, supported by evidence, that a system is acceptable for a use.

ReportsContribute

Contribute evidence from this page.

Reports is the Consortium's quarterly publication. What you know about this subject can become evidence, a case or a correction in the next edition, credited to you and published under CC BY 4.0 where it is your own work.

Risk Academy
AI assurance and audit

Prepare with a related course

Open courses in connected disciplines teach the methods this discipline will build on.