AI Risk Atlas Prototype/Demo — Unofficial independent experiment. Not an official xAI product. Scores can be wrong.

Risk Atlas
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15automated residualNeeds reviewAbove working threshold (12)

Concentrated AI rents and a permanent underclass

Owner · Governments, tax authorities, lab boards

CapabilityImpact domainHarm-adjacent

Statement (NASA form)

Given that the largest productivity gains are accruing to model owners and a thin layer of complementary labour, while entry-level work is already closing, there is a possibility of a durable split between people who own or steer the models and people who do not resulting in entrenched inequality, lost mobility, and a politics that treats AI as an occupying interest.

Condition
the largest productivity gains are accruing to model owners and a thin layer of complementary labour, while entry-level work is already closing
Departure
a durable split between people who own or steer the models and people who do not
Impact
entrenched inequality, lost mobility, and a politics that treats AI as an occupying interest

VC + institute corroboration

Experimental share of compiled public capital that names this risk. Not a certified residual.

No compiled dollar or public database record is tagged to this card yet. That is a gap, not a clean bill.

Worst scenario
4×3
Likely × Major
Urgency
3
Priority · This quarter
Inherent composite
15
Worst 12 + urgency
Residual composite
15
Need ≤ 12

Amodei’s ‘the pie may grow, but fewer people could share it’ is the risk statement in plain language. Combined with the hiring-freeze signal, this is not only a labor-market story. It is a civic one: a generation that never got a first job will not treat the labs as neutral infrastructure.

EconomicRightsCivicFoundationsTrainingFinanceEducationGovConsumer

Pathway fragment

Simple upstream → via → downstream notes. Not a causal graph. Experimental.

Upstream
  • Concentrated model rents
  • No public claim on surplus
Via
  • Wage share falls
  • Access becomes a caste
Downstream
  • Permanent excluded class
  • Political rupture

Assumptions · Tax and ownership mitigations are evidence only — not landed.

Human calibration

Override is stored on this desk only. It does not make the score official.

Failure scenarios

Each scenario has its own likelihood and consequence. The risk takes the most severe cell. Residual applies implemented mitigations to every scenario, then re-ranks.

A decade of wage suppression in exposed occupations

4Likely3Major12

Median outcomes fall even as GDP attributed to AI rises.

A locked-out cohort becomes a political bloc

3Probable3Major9

Policy swings toward punitive control or indiscriminate slowdown.

State capture by a handful of model owners

3Probable4Critical12

The same firms that run the models write the rules that govern them.

Examples

Permanent underclass framing

If gains flow mainly to owners and a specialised caste, displaced workers face lower wages and less mobility while owners capture the upside.

The closed front door

The same firms that capture the rents have already stopped hiring the people who would have shared them.

Political follow-through

Rate hikes for data centres and lost graduate placement will not stay in separate conversations.

Contributing signals

X posts on the desk that evidence this risk. A signal can contribute to more than one risk.

Permanent-underclass framing next to the 50% estimate.

Measured hiring collapse for the most exposed graduates.

Mitigations

Residual assumes only items marked in place. Highlighted rows are the remaining work needed to reach a composite of 12.

ProposedOn the pathGovernments and public capital

Broader ownership of the complementary stack

Public or cooperative compute, data trusts, and licensing that is not a monopoly rent.

Governments and public capital · expedited 6 months · normal 2 years · −1 L · −1 C · −0 U