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v2026.11,858 entries · CC-BY 4.0
NIKOLAI elementN1 · Actors, models and scopeProposednikolai-v0.1

Severity threshold

NIKOLAI proposal (unsourced): the quantitative or qualitative harm magnitude that a framework treats as in scope for catastrophic-risk purposes, recorded as a structured value with a magnitude, a unit (deaths, dollars), a "single incident" qualifier where applicable, and any stated exclusions -- not as free prose, since the figures in use differ by an order of magnitude or more across sources.

This is CASRAI's own proposed definition, not a definition any named organisation has agreed to. See what NIKOLAI is and is not.

Source of record

Where this definition comes from

Crosswalk

How named organisations use this concept

Every row below is a shadow mapping. It is CASRAI's own reading of a published document. No lab, evaluator or regulator named here has declared, endorsed, or been consulted on this mapping. That will change only when an organisation files its own Mapping Declaration — see the non-endorsement policy.
OrganisationTheir term, as publishedMatchSource
OpenAI
Preparedness Framework v2 / Frontier Governance Framework
"By 'severe harm' in this document, we mean the death or grave injury of thousands of people or hundreds of billions of dollars of economic damage." (PF fn 1, p.1). FGF: "risks that a model will materially contribute to greater than 50 fatalities or $1 billion of property damages or losses arising from a single incident" (§2.1, p.03).
PF's own "thousands of people" threshold and FGF's "50 fatalities" threshold are two different magnitudes within the same organization's own documents.
exact
confidence: high
OpenAI Preparedness Framework v2
Google DeepMind
Frontier Safety Framework v3.1
"severe" versus "significant" harm are used but not quantified (source brief gap note: "No quantitative definition of 'acceptable' risk, 'severe' versus 'significant' harm, or 'safety buffer'").none
confidence: medium
Google DeepMind Frontier Safety Framework v3.1
xAI
Risk Management Framework, Aug 2025 (superseded) / Frontier AI Framework, 30 Jun 2026
Aug 2025 RMF (superseded): "In this RMF, we particularly focus on requests that pose a foreseeable and non-trivial risk of more than one hundred deaths or over $1 billion in damages from weapons of mass destruction or cyberterrorist attacks on critical infrastructure ('catastrophic malicious use events')." The June 2026 FAIF has no magnitude at all.
This row also cites the current {FAIF26} document as the (magnitude-free) successor. {FAIF26}'s PDF metadata /Title reads "Privileged/Confidential DRAFT working FRAMEWORK DOC"; no xAI statement disambiguating draft vs. final status was found (open [VERIFY] item in the source document's register).
close
confidence: medium
xAI Risk Management Framework, 20 Aug 2025 (superseded)
Meta
Advanced AI Scaling Framework v2
"Catastrophic outcomes: outcomes that would have large scale, devastating, and potentially irreversible harmful impacts on humanity that could plausibly be realized as a direct result of access to Frontier AI in the future." (Appendix I). No numbers given.close
confidence: medium
Meta Advanced AI Scaling Framework v2
California SB 53
SB 53 statute text
"materially contribute to the death of, or serious injury to, more than 50 people or more than one billion dollars ($1,000,000,000) in damage to, or loss of, property arising from a single incident" (22757.11(c)); "The loss of value of equity does not count as damage to or loss of property" (22757.16).exact
confidence: high
California SB 53
Frontier Model Forum
Risk Taxonomy and Thresholds technical report
"Severity and Scale: ... Although no standardized quantitative definition exists across all AI developers, frontier AI frameworks prioritize risks with catastrophic potential, meaning severe harm to many people or large-scale economic damage (i.e., tens of billions of dollars)." (s1.3, p.4). Also cites UK NRR "more than 1,000 fatalities".close
confidence: medium
Frontier Model Forum, Risk Taxonomy and Thresholds technical report
Amazon
Amazon's Frontier Model Safety Framework
"Critical Capability Thresholds describe model capabilities within specified risk domains that could cause severe public safety risks" (s.1, p.2); the CBRN threshold example speaks of a model that "would enable a non-subject matter expert to reliably produce and deploy a CBRN weapon" (s.1, p.2). No numeric death or dollar magnitude anywhere in the Framework.none
confidence: medium
Amazon's Frontier Model Safety Framework

Related, not mapped

Pointers that are not crosswalk claims

These sources mention this concept but do not define or map it clearly enough to count as a crosswalk row — noted here so the research is visible without overstating it as a mapping.

  • Anthropic

    "Catastrophic risk ... refers generally to risks of the most severe potential harms from advanced AI, such as existential threats or fundamental destabilization of global systems. We use this term in its plain meaning rather than adopting any specific statutory definition." (§1, fn 1). The AAF recommends a definition "in line with the definition provided in California SB 53" (p.4, fn 2) -- a pointer to SB 53's definition rather than an independent magnitude.

    Anthropic Risk Report, August 2026 / Advanced AI Framework

Divergence

Where sources materially disagree

"Threshold" itself is a false-friend label across this corpus (see source §4), covering: a capability threshold (PF, FSF, METR, FMF); a risk threshold (Meta); a "systemic risk tier" (EU chapter Measure 4.1); a deployment-acceptance criterion (xAI 2025); a classified designation threshold (EO 14409); an intolerable-risk threshold (Seoul); and an undefined requirement (SB 53). This element specifically concerns the harm-magnitude sense only, not capability or deployment thresholds.

Gap

The figures differ by an order of magnitude or more (more than 50 deaths; more than 100 deaths; "thousands"; more than 1,000). NIKOLAI should record the magnitude as a structured value with units, the "single incident" qualifier and the exclusions, not as prose.

Referenced across the research world

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