selekoa

A documentary history of machine intelligence.

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Comparison · 18 questions · 7 frameworks

Compare frameworks

What does each developer’s safety framework say on the same questions, edition by edition?

Each row is one question, worded so that it fits every framework. Each column is one framework, showing its latest edition unless you choose another. A cell gives what that edition says on the question, with the page, or records that no passage was found in a stated search. Six questions give the edition’s own words; the other twelve give Selekoa’s paraphrase, marked as such. The questions are Selekoa’s. An edition’s own terms, such as “ASL” or “Critical Capability Level”, appear only in quotation marks.

A status records what an edition states. It does not show implementation, compliance or effectiveness, and a shared row does not make two provisions equivalent.

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What the statuses mean

Stated
A passage meets the question’s criterion as worded, however conditional or narrow its scope. The condition or scope is in the note.
Stated, partly
A passage has what the criterion asks for, but in a weaker form than the criterion’s own words: for example, no named person or body where the question asks for one, or a “may” where it asks for a statement that something will happen.
Not found in the recorded search
No passage meeting the criterion was found. The record lists the sections read, the search terms and every passage set aside, with the reason. It does not show that the developer lacks the practice, or that a provision was deleted.
Does not apply
The question does not apply: the edition is the first in its framework, so there is no earlier edition to change from.
Limits of this comparison
  • Conditions that matter are in each cell’s note. A “stated” cell can carry conditions as important as those of a “stated, partly” one.
  • The page compares and does not rank. There are no scores or totals, and columns are in a fixed order.
  • Six questions, on required actions, who decides and exceptions, quote the edition. The other twelve, on risk domains, thresholds, evaluation timing, reporting and revision, give a paraphrase with the page, because quoting them as well would exceed Selekoa’s quotation limit for most editions. A paraphrase states what the passage says, in other words; read the edition at that page before relying on it.
  • Passages were selected, checked and placed under each question by machine, and checked by a reviewer from a different model family. The maintainer decided the borderline cases.
Editions shown: the latest of each framework
Edition shown for each framework

Risk domains coveredAutonomy, self-improvement or AI research and development

Criterion: The edition names autonomous operation, replication, self-improvement, AI research and development automation, or loss of control through such capabilities as a tracked domain. Overlap rule: autonomy, self-replication and AI research and development are recorded here; loss of control or misalignment defined through deception or undermining human oversight is recorded under “Other named domains”.

  1. Anthropic · Responsible Scaling Policyv3.4 · effective 2026-07-08

    Edition textArchived copy, captured 2026-07-10

    Stated

    • Paraphrase: The “Automated R&D in key domains” row of the threshold table concerns AI systems capable of fully automating, or dramatically speeding up, the work of large teams of leading human researchers in domains where rapid progress could threaten international security or quickly disrupt the global balance of power.

      PDF p. 8, §1, threshold table, row 'Automated R&D in key domains', left column, first sentence

    Note: Named as a threshold row on automated R&D in key domains; the edition says its evaluations will for now focus on AI R&D. Autonomous, goal-directed operation appears as part of the “Misaligned AI systems in high-stakes settings” row (see “Other named domains”). No separate threshold for autonomous replication is set.

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  2. Google DeepMind · Frontier Safety Frameworkv3.1 · published 2026-04-17

    Edition textArchived copy, captured 2026-04-23

    Stated

    • Paraphrase: The edition says Google DeepMind has determined, on early research, that significant or severe risks from future models may be likeliest in CBRN, cyber, harmful manipulation, and in “machine learning R&D and misalignment”.

      PDF p. 5 (printed p. 5), §1.3.1 Risk Identification, fourth sentence

    Note: Machine learning R&D is tracked in a combined “ML R&D and Misalignment” domain with ML R&D acceleration level 1 and ML R&D automation level 1 (Table 3.2.2.a, PDF p. 15) and the “Stealth and Situational Awareness TCL” (PDF p. 14).

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  3. Meta · Frontier AI / Advanced AI Scaling Frameworkv2.0 · published 2026-04-08

    Edition textArchived copy, captured 2026-04-08

    Stated

    • Paraphrase: The edition says the Framework currently concentrates on catastrophic risk in three areas: chemical and biological, cybersecurity, and “Loss of Control”.

      PDF p. 1 (unnumbered opening page), second paragraph, second sentence

    • Paraphrase: For the outcome “Loss of Control 1”, the edition gives as a threat scenario that AI development speeds up so that new capabilities and behaviours appear faster than the organisation's evaluation processes.

      PDF pp. 22–23, §3.4.3 Loss of Control, table row 'Loss of Control 1', Potential Threat Scenario column

    • Paraphrase: In the same row, the edition lists “Autonomous AI R&D” as an example enabling capability: the ability to complete, autonomously and consistently, tasks representative of a researcher's work to advance AI development.

      PDF pp. 22–23, §3.4.3 Loss of Control, table row 'Loss of Control 1', Example Enabling Capabilities column

    Note: Meta names one domain, Loss of Control, which the edition frames as failures of critical control mechanisms (PDF p. 22). Its outcome Loss of Control 1 rests on autonomous AI research and development and evaluation awareness, which the edition lists as example enabling capabilities of a control failure rather than as domains of their own (PDF pp. 22–23), with capability checkpoints in §4.2.3; it is recorded here. Its outcome Loss of Control 2, AI undermining monitoring, is recorded under “Other named domains” under the “Risk domains covered” overlap rule. Self-exfiltration and autonomous replication appear only as illustrative emerging threat scenarios (PDF p. 38).

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  4. Microsoft · Frontier Governance FrameworkFeb 2026 · revised 2026-02

    Edition textArchived copy, captured 2026-04-24

    Stated

    • Paraphrase: The edition lists “Advanced autonomy” as a tracked high-risk capability: a model's ability to carry out expert-level tasks on its own, AI research and development among them.

      PDF p. 4 (printed p. 3), §2 Capabilities and risks, 'Tracked high-risk capabilities', third bullet

    Note: Advanced autonomy has capability thresholds in Appendix I (PDF p. 14). Loss of control, a separately named tracked capability that the edition defines through deceptive and other mechanisms that undermine human control (PDF p. 4), is recorded under “Other named domains” under the “Risk domains covered” overlap rule.

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  5. OpenAI · Frontier Governance FrameworkMay 2026 edition · published 2026-05-28

    Edition textArchived copy, captured 2026-05-29

    Stated

    • Paraphrase: The edition says its processes for assessing and mitigating systemic risk span key risk categories, among them “cybersecurity”, “CBRN” (chemical, biological, radiological and nuclear), “harmful manipulation” and “loss of control risks”.

      PDF p. 3 (printed p. 01), §1 Introduction, second paragraph, second sentence

    • Paraphrase: The edition says that its loss-of-control risk tiers, apart from those for risks related to AI self-improvement, are still exploratory and may change substantially.

      PDF p. 12 (printed p. 10), §2.4 Risk tiers › 'Loss of control', first paragraph, final sentence

    Note: The domain is framed as loss of control, with a three-tier table; self-improvement is named within it rather than as its own category.

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  6. OpenAI · Preparedness FrameworkVersion 2 · published 2025-04-15

    Edition textArchived copy, captured 2025-04-15

    Stated

    • Paraphrase: The edition lists AI Self-improvement capabilities as a Tracked Category, describing them as capabilities that could also pose new challenges to humans controlling AI systems.

      PDF p. 2 (printed p. 1), opening page, third bullet of the Tracked Categories list

    Note: AI Self-improvement is a Tracked Category. “Long-range Autonomy” and “Autonomous Replication and Adaptation” are named as Research Categories without thresholds (Table 2, PDF p. 8).

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  7. xAI · Frontier AI FrameworkJune 2026 edition · effective 2026-06-30

    Edition textArchived copy, captured 2026-07-16

    Stated

    • Paraphrase: The edition names four primary risk domains, those it considers most likely to lead to significant or severe outcomes in present and future systems: “CBRN Risks”, “Offensive Cybersecurity Risks”, “Loss of Control Risks” and “Harmful Manipulation Risks”.

      PDF p. 2, §2.1 Risk Identification, third paragraph, first sentence

    • Paraphrase: The edition describes loss-of-control risks as those arising when humans can no longer reliably direct, modify or switch off a model.

      PDF p. 1, §1 Introduction, third paragraph, third sentence

    Note: The domain is framed as loss of control (described in the passage paraphrased here); autonomy, replication or automation of AI research and development are not named as separate tracked capabilities. §2.1(b) (PDF p. 4) describes oversight, training against deception and sycophancy, and sandboxed evaluation of agents.

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