Step 20: tool results

{
  "status": "inconclusive",
  "claim_id": "e4cbf66e-fd61-4ae6-8247-19b9b2fa87c9",
  "assessment": "The only substantive evidence on this question is METR's November 2026 report on a high-access assessment at Anthropic. METR estimates that Anthropic's benchmark progress has run at about 1.9 times its earlier rate since October 2025 (95% interval 1.5 to 2.8). The [[claim:ec9c31d9-8ba5-4107-86f2-25ee089e89a1|acceleration itself]] looks real, although one alternative modelling choice puts it as low as 1.1 times. METR is confident that faster scaling of training compute did not cause it. It guesses that a majority, perhaps about 80%, of [[claim:76cf8c84-c5ec-4277-9539-38e03f8e1a07|the acceleration as of October 2026]] is due to AI assistance, and it judges that the other factors it examined would not explain a sustained acceleration.\n\nThe claim covers the whole period since October 2025, and on that period the evidence is evenly balanced. METR says [[claim:c175bbcd-10be-4d49-89a0-61fe742c0d29|non-AI factors likely played a large role in late 2025]]. It also says that cumulative attribution since October 2025 should be expected to fall below the instantaneous October 2026 figure, because AI's influence has grown over time. And it notes that Anthropic's growth before late 2025 was below the industry frontier, so part of the measured acceleration may be catch-up. If the AI share rose from modest levels in late 2025 to about 80% by late 2026, the cumulative share lands near half. Anthropic's staff had no consensus on attribution. Anthropic redacted METR's detailed cumulative attribution estimates and most of the evidence behind them, so the public must rely on METR's word.\n\nThe evidence clearly favours AI assistance as the main cause of the acceleration in late 2026. Whether it caused most of the acceleration over the whole period since October 2025 is roughly even odds. Publication of METR's redacted cumulative attribution estimate, or an independent decomposition, would settle it.",
  "confidence": 0.65,
  "claim_credence": 0.5,
  "marginal_yield": 0.3,
  "reasoning_trace": "This pass read the METR report (metr.org, 5 November 2026) in full through its methodology appendix. An earlier pass had relied on a secondhand summary.\n\nThe relevant points:\n(1) The executive summary attributes \"a majority of this acceleration today\" to AI, with significant uncertainty, and says \"other causes likely played a large role in acceleration in late 2025.\"\n(2) The attribution section gives a guess of \"perhaps ≈80%\" for the October 2026 (current) acceleration, says AI's contribution \"has grown relatively more important over time,\" and states that the more detailed cumulative and instantaneous estimates were redacted.\n(3) The methodology appendix explicitly separates instantaneous from cumulative attribution and expects cumulative attribution to be lower, \"due to non-AI acceleratory factors in 2025, and due to the growing influence of AI over time.\"\n(4) In its limitations, METR concedes that non-AI factors could explain most of the acceleration, and that a below-frontier historical growth rate could inflate the measured acceleration.\n(5) The AECI acceleration of 1.9x is robust to most specifications, but a complementary log-log link gives 1.1x.\n\nInterest: Anthropic held redaction rights and removed most of the informative evidence. METR took no payment, but its work was done on Anthropic devices with Anthropic-chosen data flows.\n\nWeighing: the phrase \"caused most of Anthropic's capability acceleration since October 2025\" most naturally reads as the cumulative share over the period. METR's figure is instantaneous, and METR itself says the cumulative share is lower by an unstated amount. A simple ramp from about 20–30% to about 80% averages to roughly half. The status therefore stays inconclusive at credence 0.5. Confidence rose slightly because the verdict now rests on a direct reading. Marginal yield is lower because the decisive evidence is redacted and no further public reading is likely to resolve the question."
}