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Risk Academy, led by the Nexus Consortium · Course catalogue · Governance, Policy and International Affairs

Law and Regulation

Contracts, intellectual property and licensing

Contracts, intellectual property and licensing, taught twice over: as the working methods of the field and as its frontier since 2024, with labs on the Academy's tools, open data and the Nexus Standards.

Core course Frontier course

The discipline

01Core course · L2 Intermediate

Contracts, intellectual property and licensing: foundations and practice

This area covers how contracts and clauses allocate risk, and the licensing of data, software, models and names: indemnities, force majeure, liability, open and commercial licences, intellectual property and trademarks.

Level
L2 Intermediate
Study time
about 24 hours (planning estimate)
Status
In authoring
Prerequisites
An L1 course in the area, or an entry review

Why now

The ruling shapes how model distribution and licensing risk is assessed under UK law, while leaving training questions open. Courts and Tribunals Judiciary (England and Wales), Getty Images -v- Stability AI [2025] EWHC 2863 (Ch), 4 November 2025

Learning outcomes

  1. Define force majeure and the other key terms of the discipline and use them correctly in a written case
  2. Explain contracts and clauses for risk and force majeure and hardship with a worked example and its source
  3. Apply the discipline's method to a documented case and explain each result with its source
  4. Analyse a named case against liability and indemnity, stating evidence, date and limits

Modules

  1. Contracts and clauses for risk
    • Contracts and clauses for risk
    • Force majeure and hardship
    • Liability and indemnity
  2. Data and software licensing
    • Data and software licensing
    • Model and content licensing
    • Intellectual property
  3. Trademarks and public names
    • Trademarks and public names
    • Licence compliance in practice
  4. Lab: the discipline's method
    • A commercial contract caps the supplier's liability at a multiple of the annual fee; when a breach causes a loss, the recoverable amount is the smaller of the loss and the cap, and the residual falls on the customer, its insurer or the carve-outs the drafting decided.
    • Work the method through a documented case and explain each result
    • Read the method's sources and stated values

Labs with Academy tools

Nexus Standards

Teaches

  • NS-14 Conformance and crosswalk to external standards
  • NRS-P6 Data responsibility, rights and licensing
  • NRS-A5 Built-in licensing and rights
  • NRS-E7 Rails: agreements, obligations and lawful handoffs
  • NRS-P7 Public procurement and contracting risk

Relies on

  • NS-1 The UNI and the artefact catalogue
  • NS-16 UNI application profile (how articles, documents, code, data, APIs and interfaces carry the UNI)
  • NRS-C1 Risk vocabulary and ontology
  • NRS-C2 Risk assessment method
  • NRS-C4 Risk data model, identifiers and exchange
  • NRS-C16 Risk-informed decisions
  • NRS-P3 Institutional governance, integrity and enterprise risk

Assessment

  • 40%Lab recordWork the discipline's method through a documented case and explain each result with its source and date
  • 40%Case memoApply the discipline's methods to a named place or organisation, stating evidence and limits
  • 20%Key terms checkShort answers on the key terms, marked against the definitions

Delivery

  • Self-paced online, with the labs in the browser
  • Cohort study over six to eight weeks, with a weekly lab review
  • Co-delivered with a partner institution, inside its own courses

Partner on this course

  • Co-teach a module and bring a current case from your work
  • Host a cohort for your learners, with your own schedule and review
  • Contribute a lab: a dataset your institution publishes openly, or a model
  • Review the course content and its references before it opens
  • Translate the course and adapt its cases to your region

How institutions and experts take part

In the Academy LMS

Course on the learning platform
Intermediate, 4 topics
Cohort group
A community group for each cohort of learners
Achievement
Recorded on completion of the assessed work

Open now in this discipline

References

  1. Courts and Tribunals Judiciary (England and Wales), Getty Images -v- Stability AI [2025] EWHC 2863 (Ch), 4 November 2025
  2. Williamson, Transaction-Cost Economics: The Governance of Contractual Relations, 1979
  3. Hart and Moore, Incomplete Contracts and Renegotiation, 1988
  4. Macaulay, Non-Contractual Relations in Business: A Preliminary Study, 1963
02Live map

Urban signals in Italy

Night-time lights, population density, nitrogen dioxide and urban heat, over Italy.

The interactive map needs JavaScript; the layer list and sources are below.

Layers 2

Urban signals

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.

Urban signals, framed on Italy.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
  • OMI nitrogen dioxide (Aura) and OMPS aerosol index (Suomi NPP), NASA; distributed by the NASA GES DISC; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • 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).
  • Air quality forecast, 5 days, PM2.5 (CAMS via Open-Meteo): Contains modified Copernicus Atmosphere Monitoring Service information 2026.
  • Past year, daily temperature and sunshine (NASA POWER): These data were obtained from the NASA Langley Research Center (LaRC) POWER Project funded through the NASA Earth Science/Applied Science Program..
  • Weather data by Open-Meteo.com (https://open-meteo.com/), licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/).
  • Optional layers (14 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
  • Nitrogen dioxide, lower atmosphere column: OMI Aura, NASA GES DISC · 10 Oct 2026
  • Land surface temperature, day, 8-day composite: VIIRS NOAA-20 Level 3, 8-day, NASA LANCE · 14 Sep 2026
  • Flood water, 3-day composite: VIIRS Global Flood Product, NASA LANCE · 14 Oct 2026

03How learning runs

How learning runs, as a process you can run

Select a scenario and press Play: course, pathway, practice, faculty, cells and record.

04What is changing

Frontier course · L3 advanced, programme courses and standards

Contracts, intellectual property and licensing: frontier methods

The methods, data, tools and studies that changed contracts, intellectual property and licensing between 2024 and 2026, taught by reproducing them on open data.

Level
L3 Advanced
Study time
about 28 hours (planning estimate)
Status
Planned
Prerequisites
Contracts, intellectual property and licensing: foundations and practice; Working knowledge of a scripting language (Python or R) for the labs

Why now

The ruling shapes how model distribution and licensing risk is assessed under UK law, while leaving training questions open. Courts and Tribunals Judiciary (England and Wales), Getty Images -v- Stability AI [2025] EWHC 2863 (Ch), 4 November 2025

Learning outcomes

  1. Explain what changed in contracts, intellectual property and licensing since 2024 and cite the studies, data or rules behind each change
  2. Reproduce UK High Court dismissed Getty's secondary copyright claim against Stability AI on open data and state the uncertainty of the result
  3. Evaluate a 2024 to 2026 study: its question, data, method, limits and what it changes for practice
  4. Design an analysis that combines a frontier method with the faculty's instruments, and justify each choice

Modules

  1. UK High Court dismissed Getty's secondary copyright claim against Stability AI
    • The court held that a model such as Stable Diffusion, which does not store or reproduce the copyright works, is not an infringing copy, dismissing secondary infringement.
    • The ruling shapes how model distribution and licensing risk is assessed under UK law, while leaving training questions open.
    • Courts and Tribunals Judiciary (England and Wales), 4 November 2025
  2. US Copyright Office reported on copyrightability of AI outputs
    • Part 2 of the Copyright Office report on copyright and AI, published 29 January 2025, addresses whether outputs created using generative AI can be protected by copyright.
    • Whether AI-assisted outputs are protectable affects ownership clauses, warranties and the value of generated content in contracts.
    • US Copyright Office, 29 January 2025
  3. New EU Product Liability Directive covers software
    • Directive (EU) 2024/2853 replaces the 1985 regime and treats software, including AI systems, as a product for no-fault liability, excluding free and open-source software supplied outside commercial activity.
    • Software suppliers face strict liability exposure, so contracts, insurance and indemnity allocation need review.
    • Publications Office of the European Union (EUR-Lex), 18 November 2024
  4. Open Source Initiative released the Open Source AI Definition 1.0
    • The OSI released version 1.0 of the Open Source AI Definition, requiring access to training data information, complete code and model parameters under approved terms for a system to qualify as open source AI.
    • It gives a reference point for judging licence claims about models and for setting procurement and reuse conditions.
    • Open Source Initiative, 28 October 2024
  5. Reproduction lab
    • Extend the discipline's method with one frontier method and compare its results
    • State the uncertainty and the limits of the result
    • Peer review against a shared checklist
  6. Technology that helps and the risks it carries
    • Foresight tools and regulatory sandboxes.
    • Threats to information integrity, and AI in public decisions.

Labs with Academy tools

Nexus Standards

Teaches

  • NS-14 Conformance and crosswalk to external standards
  • NRS-P6 Data responsibility, rights and licensing
  • NRS-A5 Built-in licensing and rights
  • NRS-E7 Rails: agreements, obligations and lawful handoffs
  • NRS-P7 Public procurement and contracting risk

Relies on

  • NS-1 The UNI and the artefact catalogue
  • NS-16 UNI application profile (how articles, documents, code, data, APIs and interfaces carry the UNI)
  • NRS-C1 Risk vocabulary and ontology
  • NRS-C2 Risk assessment method
  • NRS-C4 Risk data model, identifiers and exchange
  • NRS-C16 Risk-informed decisions
  • NRS-P3 Institutional governance, integrity and enterprise risk

Assessment

  • 50%Method reproductionReproduce one frontier method on open data and state the uncertainty of the result
  • 30%Study reviewA critical review of a 2024 to 2026 study: question, data, method, limits, what it changes
  • 20%Peer reviewReview two other learners' reproductions against a shared checklist

Delivery

  • Self-paced online, with the labs in the browser
  • Cohort study over six to eight weeks, with a weekly lab review
  • Co-delivered with a partner institution, inside its own courses

Partner on this course

  • Co-teach a module and bring a current case from your work
  • Host a cohort for your learners, with your own schedule and review
  • Contribute a lab: a dataset your institution publishes openly, or a model
  • Review the course content and its references before it opens
  • Translate the course and adapt its cases to your region

How institutions and experts take part

In the Academy LMS

Course on the learning platform
Expert, 6 topics
Cohort group
A community group for each cohort of learners
Achievement
Recorded on completion of the assessed work

Open now in this discipline

References

  1. Courts and Tribunals Judiciary (England and Wales), Getty Images -v- Stability AI [2025] EWHC 2863 (Ch), 4 November 2025
  2. US Copyright Office, Copyright and Artificial Intelligence, Part 2: Copyrightability, 29 January 2025
  3. Publications Office of the European Union (EUR-Lex), Directive (EU) 2024/2853 on liability for defective products, 18 November 2024
  4. Open Source Initiative, The Open Source Initiative Announces the Release of the Industry's First Open Source AI Definition, 28 October 2024
  5. Williamson, Transaction-Cost Economics: The Governance of Contractual Relations, 1979
  6. Hart and Moore, Incomplete Contracts and Renegotiation, 1988
  7. Macaulay, Non-Contractual Relations in Business: A Preliminary Study, 1963
05Take part

Take part in the work

Start from who you are.

06Questions

Questions, answers and key terms

Is the course 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; it 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 course?
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. For organisations.

Key terms

Term

Force majeure

A contract clause that excuses performance when extraordinary events prevent it.

Term

Open licence

A licence that lets others use, share and adapt a work under stated conditions.

Term

Indemnity

A promise to compensate another party for specified losses.

Term

Trademark clearance

Checking that a proposed name does not conflict with existing marks before 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.

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