Step 23: assistant

thinking

Calls evaluate_argument

{
  "verdict": "slight",
  "evaluation": "Granting its premises, the argument shows that 2027 will bring a large amount of progress of the right kind, and that raises the forecast's probability materially. It does not carry it past even odds, because no premise fixes how large the remaining gap is: weeks-long horizons at 50% reliability on checkable tasks are not month-long research projects done reliably, and \"all\" non-agenda work has a long tail. The weight falls on two premises. [[claim:72048c9d-d8b0-458a-86fc-eaae8f83193a|The size of Anthropic's AI-driven acceleration]] rests on one outside estimate whose main evidence is not public. Whether the gains carry over to research work is the denial of [[claim:ecb10d1f-b391-4e54-b645-8133ad3827ae|a claim the evidence leaves unsettled]]. [[claim:83df12e2-68f5-4d25-8327-28d24ab513be|The weeks-long-task forecast]] is well supported and [[claim:e6e8a4fa-eee4-4fc3-b564-ea04a6313546|a near-term stall]] is doubtful, so those two premises largely hold.",
  "argument_id": "3e5b3e1b-ba2e-4e3b-80a1-dc4156672a03"
}

Calls evaluate_argument

{
  "verdict": "likely",
  "evaluation": "The entailment is sound: the milestones forecast are stronger than the capability described here, so if the forecasters are reliable on this question the conclusion is likely. The argument therefore stands or falls with their reliability, which is the weak point. The forecasts are conditional on no deliberate slowdown, they moved by a year or more within three months on a single estimate whose main evidence was withheld, and their authors call the analysis preliminary. The insider forecast gives no number and cites one new benchmark, and comes from a co-founder of the lab concerned. These voices share one input and are not independent. The graph's own estimate of [[claim:a6037281-5051-4d1f-bd95-5546955a242d|the date of the stronger milestone]] puts roughly one chance in six on the end of 2027, well short of the forecasters' own figures, and [[claim:55f89371-8a43-43c1-8dd7-932c350ca7fb|the successor-training forecast]] has not yet been assessed.",
  "argument_id": "7c55be97-17ee-48d2-95f3-42695f8f7da8"
}

Calls evaluate_argument

{
  "verdict": "likely",
  "evaluation": "Granting its premises, the forecast would probably fail: if the measured acceleration does not reach research work and judgment holds back the remaining tasks, thirteen months is too short. The premise about the present is the firmest: [[claim:81eeb61b-4ce4-4d0b-891d-11e970d8f669|the gap at critical stages of research]] is well supported through mid-2026 and confirmed by both labs' own accounts, though less certain for the newest models, one of which now exceeds recruited experts at designing and interpreting experiments on fixed problems. The two forward-looking premises carry the weight and are open: [[claim:ecb10d1f-b391-4e54-b645-8133ad3827ae|whether benchmark acceleration generalises to research]] is unsettled, and [[claim:55b84cc2-c3ba-4168-ae4b-723dafc6b353|whether research judgment will slow the remaining automation]] has not been assessed. The argument is the main reason the forecast is judged more likely false than true, but it is not decisive, because a present gap says little about a rate that may itself be accelerating.",
  "argument_id": "54d7b419-7d12-4394-a53b-0808e5172ada"
}

Calls evaluate_argument

{
  "verdict": "slight",
  "evaluation": "The facts stated are taken from the labs' own published accounts and are not in dispute, so the argument turns on what they license. They bear on the conclusion only modestly. A stated goal of March 2028 is a target, not a forecast, and falls only three months after the deadline; a lab that hit its previous milestone on schedule could reach the next one early. Anthropic has given no date, and a later outside assessment found its progress faster than its earlier statements implied. Labs under scrutiny over safety also have reasons not to announce that the capability is imminent, so their silence is weaker evidence than it would be from a party with only an interest in sounding capable. Pacing commitments can delay the capability but have so far produced a pause of two weeks. The argument adds some weight against the forecast, mostly for OpenAI, and little for Anthropic.",
  "argument_id": "a94fd885-0405-4ee9-b4f2-dfda520ae430"
}

Calls provenance_record_reading

{
  "note": "The forecast is produced by extrapolations and a filtered model that are shown, but the input that drives them is an outside evaluator's estimate of acceleration at Anthropic whose main evidence was redacted. The authors say the analysis is preliminary, that they could not explain why their model was surprised, and one records unease that the update is large relative to the evidence shown. The summary and the individual forecast sections were read, not the appendices.",
  "support": "evidence_not_shown",
  "deployment": "Forecasts a superhuman AI researcher in 2027, conditional on no deliberate slowdown, and argues from it for an urgent pause.",
  "instance_id": "c4dbab92-0811-4b82-ab3a-4d6c23a28707",
  "source_kind": "blog_post",
  "source_read": true,
  "worth_reading": true,
  "worth_reading_reason": "The sections on why the model was wrong and the appendices would show how sensitive the 2027 dates are to the 80% attribution figure."
}

Calls provenance_record_reading

{
  "note": "The revision is offered on the strength of one new benchmark, which measures designing and interpreting experiments on fixed problems, and of progress in mathematics. That evidence alone does not bear a shift in the date of full self-improvement. The author is a co-founder of Anthropic and may be drawing on knowledge he does not cite. No probability is given; his May 2026 post gave about 30% for 2027.",
  "support": "overstates",
  "deployment": "A closing comment on a new benchmark of experimental research taste, revising the author's own earlier forecast.",
  "instance_id": "5c17f8be-fa41-4967-8dca-f77116f32913",
  "source_kind": "blog_post",
  "source_read": true,
  "worth_reading": false
}

Calls provenance_record_reading

{
  "note": "Read whole from an archived copy. The figures come from OpenAI's internal usage data and an automated classifier of task outcomes, none of it released, and no outside party has examined them. The statement that the research-intern goal was reached is qualified as according to the company's own measurements. Its admissions that agents need significant human steering and that people still judge which ideas to pursue run against its interest in appearing capable.",
  "support": "evidence_not_shown",
  "deployment": "OpenAI's public account of how far agents have changed its own research, published alongside a call for labs to report such progress.",
  "instance_id": "6977ec8a-4e2c-4930-85a4-219b0f6061d9",
  "source_kind": "report",
  "source_read": true,
  "worth_reading": true,
  "worth_reading_reason": "It is the only first-hand account of where OpenAI places itself relative to the capability in this claim."
}

Calls provenance_record_edge

{
  "evidence": "\"METR recently estimated that Anthropic is now making AI progress about twice as fast as its historical rate (they would not be surprised by anything from 1.3x to 3x), and guessed that 'perhaps ≈80%' of the current acceleration is due to AI.\" and \"While there were many factors and sources of evidence that influenced us, the single biggest source was the METR report.\"",
  "fidelity": "faithful",
  "reasoning": "The forecast is built by conditioning models on METR's estimate. The update reports METR's range, its hedged attribution and the redactions accurately; it then treats 1.7x as the working figure, which it flags as its own derivation.",
  "confidence": 0.9,
  "target_read": true,
  "to_source_id": "f146b243-4913-405e-aaf8-18d4769481df",
  "relation_type": "derives_from",
  "to_source_kind": "report",
  "from_instance_id": "c4dbab92-0811-4b82-ab3a-4d6c23a28707"
}

Calls provenance_record_edge

{
  "evidence": "The recorded passage: \"Anthropic co-founder Jack Clark has moved his forecast for when AI could fully improve itself to 2027 from 2028, pointing partly to a new test of research judgment.\"",
  "fidelity": "faithful",
  "reasoning": "The coverage restates Clark's 12 October 2026 post and adds nothing of its own. Judged from the recorded passage of the coverage against the original post, which was read.",
  "confidence": 0.85,
  "target_read": true,
  "to_source_id": "fb0305b4-8b14-4a54-b15b-4a6c0193a033",
  "relation_type": "repeats",
  "from_instance_id": "e3a13307-e488-43b8-8d66-f0dd27bc2035"
}

Calls record_source_interest

{
  "party": "Jack Clark, co-founder of Anthropic",
  "scope": "claim",
  "stake": "The author co-founded and works at Anthropic, one of the two labs whose capability the forecast concerns. The lab gains commercially from being seen as close to automating research, and the author also argues publicly for policy attention to that prospect.",
  "source_id": "fb0305b4-8b14-4a54-b15b-4a6c0193a033"
}

Calls record_source_interest

{
  "party": "OpenAI",
  "scope": "source",
  "stake": "OpenAI is describing its own systems and its own research organisation. It gains commercially from being seen as near an automated researcher, and it is also under scrutiny over safety, which gives it reasons to appear measured about how fast that is coming.",
  "source_id": "b0ee05c4-17a4-47d4-89c2-b8913ca952ec"
}

Calls record_source_interest

{
  "party": "AI Futures Project",
  "scope": "claim",
  "stake": "The authors wrote the AI 2027 scenario and use this forecast to argue for an urgent pause in frontier development. A 2027 date supports both their earlier scenario and their policy position.",
  "source_id": "a002b1fe-529f-408f-b209-3455cb652171"
}

Calls provenance_write_map

{
  "summary": "No source states this forecast in its own terms. The voices recorded for it forecast stronger milestones in 2027, and they are closer to one voice than several: the forecasting group's November 2026 update is built on an outside evaluator's estimate of acceleration at Anthropic, most of whose supporting evidence the lab redacted, and the insider forecast comes from a co-founder of that lab, with news coverage repeating it. The one first-hand statement from OpenAI places its own automated-researcher goal in March 2028, after the deadline, on internal measurements it has not released.",
  "material": true
}

Calls set_instance_order

{
  "claim_id": "54c25eab-5263-467c-880b-ee0f2c3bdd12",
  "reasoning": "The two forecasts that affirm a stronger milestone first, then OpenAI's own statement of its schedule, then Clark's earlier odds, with the news coverage that repeats Clark last.",
  "instance_ids": [
    "c4dbab92-0811-4b82-ab3a-4d6c23a28707",
    "5c17f8be-fa41-4967-8dca-f77116f32913",
    "6977ec8a-4e2c-4930-85a4-219b0f6061d9",
    "88850e96-7685-4ea9-8e14-e064b9c1fc73",
    "e3a13307-e488-43b8-8d66-f0dd27bc2035"
  ]
}