Illustrative: a chain of blocks each linked by hash to the one before, with a Merkle tree under the newest
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.
- 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
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.
- 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
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).
Connected activity in the United Kingdom and Ireland
Night-time lights and population density, the footprint of electrified, connected activity, over the United Kingdom and Ireland.
The interactive map needs JavaScript; the layer list and sources are below.
Layers 2
Connected activity
Keyboard, with the map focused
Hold Ctrl or ⌘ and scroll to zoom
Latest available
NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Blue Marble (NASA) · © OpenStreetMap contributors (ODbL) · Natural Earth
Loading the latest NASA imagery.
Drag to move. Ctrl or ⌘ and scroll, pinch or the buttons to zoom; hover for the values under the pointer; reset returns to the region.
Connected activity, framed on the United Kingdom and Ireland.Satellite and model products as NASA publishes them, each with its own date. They are indicators, not assessments of any place.
Data: NASA GIBS · ASTER GDEM · Blue Marble · © OpenStreetMap contributors · Natural Earth · NASA EONETSources and licences
- We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
- We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
- VIIRS Black Marble night-time lights, NASA Goddard Space Flight Center; distributed by the NASA Level-1 and Atmosphere Archive and Distribution System (LAADS DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
- Center for International Earth Science Information Network (CIESIN), Columbia University. 2018. Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11. NASA Socioeconomic Data and Applications Center (SEDAC). Licensed under CC BY 4.0. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). doi:10.7927/H49C6VHW. CC BY 4.0
- VIIRS near-real-time products (flood, land surface temperature, snow cover, corrected reflectance), NASA LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
- ASTER GDEM is a product of METI and NASA (ASTER Global Digital Elevation Model V003, NASA LP DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). Cite as: NASA/METI/AIST/Japan Spacesystems and U.S./Japan ASTER Science Team (2019). ASTER Global Digital Elevation Model V003. doi:10.5067/ASTER/ASTGTM.003. NASA open data
- Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com. Public domain
- © OpenStreetMap contributors (ODbL), via NASA GIBS (coastlines, boundaries, roads and place names). Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). ODbL
- Blue Marble, NASA Earth Observatory; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
- Context on the globe and flat map: coastlines, boundaries, roads and place names from NASA GIBS reference layers (OpenStreetMap data, ODbL, © OpenStreetMap contributors); Blue Marble imagery as an optional base; 3D terrain and the elevation read-out from the ASTER GDEM elevation colour index (5 m to 200 m classes, exaggerated for legibility). Boundaries are drawn as published and imply no position on any territory.
- Globe: MapLibre GL JS 6.9.1, BSD-3-Clause, © MapLibre contributors.
- Live events: NASA Earth Observatory Natural Event Tracker (EONET); events are indicative and keep their original source links.
- NASA GIBS: We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS).
- Optional layers (3 sources in the layer list: live, forecast, observed and context) print their provider credit on the map and here when switched on; forecasts are model output and derived indices are estimates.
Layers and dates
- Night-time lights, daily: VIIRS Black Marble (VNP46A2), NASA LAADS DAAC · 12 Oct 2026
- Population density, 2020: Population: CIESIN, Columbia University, Gridded Population of the World v4.11 (2018), NASA SEDAC, CC BY 4.0 · static
- True colour: VIIRS NOAA-20 corrected reflectance, NASA LANCE · 13 Oct 2026
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.
Quantities and units
Methods and their limits
Each method is listed with what it assumes and where it fails.
What the field debates
Bodies that set practice, and the data they publish
Bodies and standards are named so learners can find and apply their published work; the Academy teaches their use and links to the publisher, and no affiliation is implied.
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).
At a glance, hub, what is changing now and courses
AI assurance and audit at a glance
risksacademy.comtechnology-digitaldiscipline
- Open, 0
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- Subtopics, 9
Research and tools
Research and preprints as they are published, by discipline, with the faculty's other tools.
The hub lists the newest research and preprints for AI assurance and audit, each with its source and date. Open the research hub
What is changing now
Recent developments in aI assurance and audit, each with its source; sources checked on 16 October 2026.
Courses in this discipline
Courses for this discipline are in development; until they open, study it through the connected courses and open lessons below.
The course catalogue lists every open course of the Academy.
How AI assurance and audit is taught, as a process you can run
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Achievements, where this is practised, practised in and across the ecosystem
Achievements in this discipline
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. How recognition works.
Where the subject is practised
A field platform page on this subject is in development.
The three Foundry systems where it is practised
Across the ecosystem
Take part in Technology and Digital Systems
Start from who you are.
Core references and where to begin
Start with Raji, then National Institute of Standards, then Raji.
Questions, answers and key terms
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Key terms
AI assurance
The processes that build and communicate justified confidence that an AI system meets its requirements.
Impact assessment
A structured analysis of how an AI system may affect individuals, groups and society, as in ISO/IEC 42005:2025.
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.
Assurance case
A structured argument, supported by evidence, that a system is acceptable for a use.
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.
Around AI assurance and audit
Prepare with a related course
Open courses in connected disciplines teach the methods this discipline will build on.