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GCRI · Artificial Intelligence and Autonomous Systems

Reviewed models and scenarios

Model descriptions for Artificial Intelligence and Autonomous Systems are published here once reviewed, with their assumptions, evidence and validation. They describe models; they are not live simulations.

01Workspace

The workspace for reviewed models and scenarios.

Pipeline

Reviewed models and scenarios · Workspace WS-43 · Example interface, not a record

One stage waitingGCRI · Artificial Intelligence and Autonomous Systems

Stages

  1. Ingest5 sources
  2. Validateschema · licence
  3. Transformversioned
  4. ModelArtificial
  5. Testheld-out
  6. Releasewith limits

Artefacts

Model registryv3.0To checkPublished statistics
Evaluation resultsv5.2OpenASSESSED
Incident logv1.3OpenREPORTED
Usage telemetryv5.3To checkOBSERVED

Compute quota

share used vs alert level

CPU hours39 used of 80 used limitStorage78 used of 90 used limitGPU hours47 used of 70 used limit
Pipeline.Illustrative interface; not live data.

Artificial Intelligence and Autonomous Systems · Pipeline. Pipeline: example names and illustrative values, not a record.

02What is shown

Released, referenced and rights-cleared.

  • Time and space reference for every view.
  • Sources and licence.
  • Uncertainty and known limits.
  • Version and date of release.
03Model classes

The kinds of model AI work relies on.

Model classOpen examplesQuestion it answersValidation
Capability evaluationsOpen evaluation suites such as HELMWhat a model can doHeld-out tests, reproducibility
Red-team evaluationsStructured adversarial testingHow a model can be misused or failCoverage and independent repetition
Socio-technical impact modelsLabour and economic modelsEffects on work and servicesObserved adoption data
Incident analysisOECD AI incidents monitorPatterns of real failuresIncident verification
04Process

How the process runs.

Process explorer · Process

Reviewed models and scenarios: Hazard, exposure, vulnerability

10 steps4 stages

Process

Reviewed models and scenarios: Hazard, exposure, vulnerability

In IPCC AR6 Working Group II, climate risk results from interactions between hazards and a system’s exposure and vulnerability, and responses can add risk.

  1. 01 Drivers

    1. 01HazardDataset · Incident responderThe potential occurrence of a natural or human-induced physical event or trend that may harm people, property, services or ecosystems.
    2. 02ExposureDataset · Incident responderThe presence of people, livelihoods, species, ecosystems, infrastructure or assets in places and settings that could be adversely affected.
    3. 03SensitivityDataset · Incident responderThe degree to which a system or species is affected, either adversely or beneficially, by climate variability or change.
    4. 04Capacity to cope and adaptDataset · Incident responderThe ability of systems, institutions, humans and other organisms to adjust to damage, take opportunities or respond to consequences.
  2. 02 Assessment

    1. 05Risk from responsesComponent · Incident responderRisks from climate responses arise when responses miss their objectives, or from trade-offs or negative side effects.
    2. 06VulnerabilityComponent · Incident responderThe propensity or predisposition to be adversely affected. It includes sensitivity to harm and lack of capacity to cope and adapt.
    3. 07RiskModel · Artificial Intelligence and Autonomous SystemsRisk results from dynamic interactions between hazards and the system’s exposure and vulnerability. Each may be uncertain and change.
  3. 03 Response

    1. 08Risk management and responseStep · Incident responderRisk management is plans, actions, strategies or policies that reduce the likelihood or size of adverse consequences.
    2. 09Residual riskRecord · Incident responderThe climate impact risk that remains after adaptation and mitigation efforts. Adaptation can redistribute risk between areas and groups.
  4. 04 Decision

    1. 10Decision by the responsible partyDecision · Incident responderThe framing names no single decision maker. Decisions on responses rest with the responsible party under its own rules.

Outline of an external standard or method, from its public sources. It describes what the framework says, not a record of any run. It does not show that Nexus or any partner performs, certifies or approves a step. A gate is a step of the method, never a Nexus approval.

05Status

Releases appear as they are reviewed.

Analysis runs in Foundry; reviewed releases are listed here.

06Sources

Where this page’s references lead.

The bodies and documents this page is read against. Status and editions change; each link goes to the issuing body.

07Questions

Questions and answers.

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ReportsContribute

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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.

GCRIArtificial Intelligence and Autonomous SystemsExponential TechnologyLabs Evidence
Artificial Intelligence and Autonomous Systems

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Information and enquiries are open today. An enquiry receives a reference and names the next step; applications, payments, compute allocations and registrations open only when their team, terms and review capacity exist.