AI Threat · Module 3 · Society and Truth

Inequality and the Concentration of Power

The lesson examines a dystopia that needs only ownership. Participants follow the AI supply chain through six layers, see why the frontier concentrates while capability behind it diffuses, weigh who gains, and learn how states use the chain as strategy. They identify four ways dependence becomes a threat, learn what sovereignty as verifiable properties can and cannot achieve, and build a dependency map with exit plans, the chapter's practical answer to what a single organisation can do.

Lesson 15 of 35Chapter 1575 minutes

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Learning objectives

After the lesson the participant can:

Key concepts

The AI supply chain
Six layers from chip design and accelerators, through chip manufacture, cloud capacity, frontier and open-weight models, and platforms and suites, to the applications of deployers. An organisation's own exit plans and second sources act on the last link.
Forced migration
Models are retired on the provider's schedule, often at shorter notice than a procurement cycle. Deprecating the model on which a high-risk system was evaluated forces re-evaluation and retraining of overseers at a time the deployer did not choose.
Systemic form of T8
When many organisations rely on the same model or cloud region, one failure or faulty update reaches all of them at once. It needs no one's decision, and for an insurer it appears in operations and in correlated claims.
Sovereignty as verifiable properties
From AI Platform and Security: knowing where workloads run, which law governs them, being able to move them and to continue if a provider becomes unavailable. The honest claim is reversibility, not independence.
Dependency classes
Each dependency is classified as reducible, accept and monitor, or unavoidable. The default is reducible unless shown otherwise; accepted dependencies get named monitoring signals such as a deprecation notice or change of ownership.

Interactive exercises

Do them here and get feedback at once. Choose a card and then where it belongs, or drag it.

Interactive exercise 1 · Match

Concentration by layer

Match each layer of the AI supply chain to the concentration the chapter's table records for it.

Interactive exercise 2 · Sort

Classify the dependencies

Sort each dependency in Nordvik Region's dependency map into the class the map gives it.

Teaching plan

12 minThe teacher walks through Table 15.1 layer by layer, then the two counter-forces of falling prices and open-weight models; participants place their own key AI service on the chain.
12 minReview who gains and how states treat the chain as strategy, reporting the supply-chain-risk designation for what it shows about structure, without taking a side.
11 minExplain the four threat mechanisms and the DORA and NIS 2 provisions the chapter cites; discuss what sovereignty designs do and do not change.
30 minExercise in groups: build a dependency map for up to five services following the eight steps of the guide and DEP-NR-2026-01, and count concentration.
10 minStage the debate and review the verdict; compare Nordvik, which holds its weights, with Hansa, which relies on warm second sources.

Discussion

  1. Both camps disagree on how likely a supplier or its home state is to use dependence as leverage. Why does the chapter say an exit plan makes that question less important?
  2. Nordvik pays for reversibility with capability behind the frontier. For which of your services would that trade be acceptable, and for which would it not?
  3. Acemoglu and Johnson argue that gains were widely shared only when workers and citizens had countervailing power. What forms of countervailing power exist around your organisation's use of AI?

Written exercise

Exercise · 30 minutes

A dependency map with exit options

Select up to five AI services in your organisation that support a critical function, decisions about people or special-category data. For each, map the chain downwards: application, model and developer, hosting and region, and accelerator vendor where known, including models embedded in software suites. Record jurisdiction and ultimate owner at each layer. Classify each dependency as reducible, accept and monitor, or unavoidable. For every reducible dependency name a second source and a maximum switch time in working days; for every accepted one name the signals that would bring it back for decision. Count how many services sit behind each provider and flag any provider behind more than a third.

Deliverable: A dependency map with layers, jurisdictions, classes, exit references with switch times, monitoring signals and a concentration count.

Self-test

Choose an answer to see whether it is right, or open the answer below each question.

  1. What does the Commission's proposal for a Cloud and AI Development Act record about the European cloud market?

    Show the answer

    B. EU providers' share fell from 29 to 15 per cent between 2017 and 2022; three non-EU hyperscalers hold over 70 per cent
    The proposal records the shrinking European share, and its recitals state that sovereign versions of hyperscaler offerings do not address extraterritorial law and service disruption.

  2. Which statement about political withdrawal of services does the chapter make for 2026?

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    D. No case has been documented of a US AI or cloud service withdrawn from European customers for political reasons
    States use the supply chain as a lever, so far mainly towards rivals and their own suppliers; the leverage risk for European customers is therefore not yet an observed case.

  3. In Nordvik's dependency map, how is the accelerator layer classified?

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    A. Unavoidable, because all hosting options use non-European accelerators
    Sovereignty designs do not reach the chips. The map shows the audit committee which dependencies have exits, which are accepted with signals and which nobody can avoid.