AI News

The AI Prediction Ledger: Who Was Right, Who Was Wrong, and What Comes Next

Kingy.ai accountability project

A public record of AI forecasts

AI leaders make claims that move markets, shape regulation and influence how people plan their careers. This ledger preserves those claims, separates forecasts from warnings, and checks the measurable ones when their deadlines arrive.

Version 1.23 · 100 tracked records · Source/deadline reviews: October 1–2, 2026 · Product checks: October 5, 2026

A growing collection of public assertions, including conditional scenarios and repeated statements. These are not 100 independently verified, unique forecasts. Historical scores remain unchanged.

100Tracked records
14Retained pending statuses
80Unscored review records
5Historical score contributors
The current warnings are on the record. Coxon’s original post reports that AI builders believe AI could kill all humans by the end of the decade, without a numerical probability. Hubinger’s separate post supplies his own greater-than-10% estimate over the next decade. The ledger keeps their attributions separate and does not infer hidden motives from these warnings.

Forecasts need a defined outcome, scope, date and measurement rule. “AGI,” “smarter than humans,” “most code” and “join the workforce” can each shift meaning after the deadline. For the operational evidence behind the agent claims, see Kingy’s State of AI Agents 2026 and the Kingy Score v2 methodology.

Browse the ledger

Statuses are retained historical labels, not fresh outcome findings. Five numeric scores have explicit limitations beside them; one additional historical record is unresolvable. Search a record ID, forecaster or claim. Open a source or correction trail for context.




100 records · Filters require JavaScript

JavaScript is off. The first 20 detailed records appear below; download all 100 records as JSON or CSV.

Jacob Coxon
Former pretraining researcher, Anthropic and OpenAI · September 8, 2026 (Vancouver); September 9 UTC
Pending

Coxon warned that AI builders believe AI could kill all humans by the end of the decade; this post gives no numerical probability.

PendingRiskEnd of the 2020s; qualitative warning attributed to AI buildersNo probability in original post

This is a qualitative warning reporting AI builders’ beliefs. The inspected post supplies no personal Coxon probability, so it cannot support probability calibration. Historical Pending status and score are retained.

Original statement and attribution limits

Sources: Coxon’s original post; Hubinger’s separate numerical post. The numerical estimate is Hubinger’s own. Record 001 remains attributed to Coxon’s qualitative warning; the prior numerical attribution is preserved below and remains unverified. This review makes no new claim about incentives or hidden motives.

Dated source reviews and correction history

Historical v1.5 review: The original AP link could not be accessed. A later original TMZ interview report corroborates the broad estimate but does not verify the original September 8 attribution. Historical record retained; no source replacement or outcome finding. Historical status and score retained; this is not a new calibration verdict.

October 2 v1.6 source repair (supersedes the v1.5 source-access note): Original September attribution unresolved. Coxon’s original X post states a qualitative concern, not the recorded 10% probability. A September 11 original TMZ interview report concerns a later, conditional estimate; it cannot be silently backdated to September 8. Historical status and score retained.

October 2 v1.7 follow-up (supersedes the v1.6 access note): AP’s September 14 report attributes 10% over a decade to social posts, but its linked September 9 report only reproduces qualitative warnings. The original numeric September 8 post remains unlocated. The later September 11 TMZ estimate cannot be silently substituted or backdated. Historical record retained and explicitly unresolved. Historical status and score retained.

October 2 v1.9 original-post correction (supersedes earlier current wording): Coxon’s original public post reports AI builders’ belief that AI could kill all humans by the end of the decade. It supplies no numerical probability. Hubinger’s separately authored quote-post gives his own greater-than-10% estimate over the next decade; record 002 already tracks it. Restore Coxon’s qualitative warning and its stated horizon rather than transferring Hubinger’s number or backdating the later TMZ interview. The former Coxon 10%/September-2036 assertion remains in history and is not verified by this repair. No motive or outcome finding is made.

Evan Hubinger
Alignment science lead, Anthropic · September 2026
Pending

Hubinger personally estimated a greater-than-10% chance that AI kills all humans within the next decade.

PendingRiskApproximately September 2036; relative ten-year horizonProbability supplied

The estimate is unusually explicit but still lacks a published model showing how the number was derived. Keep it as a forecast, not a fact about current systems.

Source and incentive context

Hubinger works for a frontier lab whose public case for safety rules can affect regulation and competition. His technical work on deceptive model behavior is relevant evidence, but employment alone proves neither sincerity nor strategy. Sources: Original Hubinger post; Sleeper Agents paper.

Dated source reviews and correction history

Historical v1.5 review: Linked reporting supports the attribution, but the original X post was not retrieved. Preserve the historical probability and horizon; this is not a fresh primary-post verification. Historical status and score retained; this is not a new calibration verdict.

October 2 v1.6 source repair (supersedes the v1.5 source-access note): The original public post confirms a personal greater-than-10% estimate over the next decade, not a company probability or a claim about present-model danger. The public follow-up distinguishes future superintelligence from present models. September 2036 is approximate, not an exact-day deadline. Historical status and score retained.

Dario Amodei
CEO, Anthropic · October 2024 / March 2025
Pending

Powerful AI could arrive as early as 2026, but could take much longer.

PendingCapabilitiesEarliest possibility: 2026; no firm deadline

The definition is demanding and more useful than a bare AGI label. A fair resolution still needs agreed tests for expert-level performance, autonomous work and reliability across disciplines.

Source and incentive context

Anthropic sells access to frontier models and also argues for stronger frontier-model oversight. Both interests belong in the record. Sources: Machines of Loving Grace; Anthropic submission summary.

Dated source reviews and correction history

October 2 source/deadline review: The essay gives 2026 as an earliest possibility and allows a much longer wait. It does not supply the recorded late-2026/early-2027 cutoff. Historical status and score retained; this is not a new calibration verdict.

Dario Amodei
CEO, Anthropic · May 28, 2025
Pending

AI could eliminate half of entry-level white-collar jobs within one to five years.

PendingJobsDeadline: May 2030

This needs a fixed occupation list and baseline job count. Job openings, employment levels and task automation are different measures and should not be swapped after the deadline.

Source and incentive context

The forecast came from a direct interview. Anthropic benefits when employers believe its systems can perform valuable work, while stronger displacement expectations may also support regulation and workforce programs. Source: Axios.

Dated source reviews and correction history

October 2 source/deadline review: Original interview reporting supports the forecast. Its one-to-five-year window is still open; causal attribution and a fixed measurement baseline remain necessary. No new outcome resolution. Historical status and score retained; this is not a new calibration verdict.

Dario Amodei
CEO, Anthropic · May 28, 2025
Pending

AI-driven displacement could push US unemployment to 10–20% within one to five years.

PendingJobsDeadline: May 2030

This is measurable, but causation matters. A recession that raises unemployment without demonstrated AI displacement would not satisfy the forecast.

Source and incentive context

Record alongside the entry-level-jobs claim, but score separately because the labor-force consequence can fail even if task automation rises. Source: Axios.

Dated source reviews and correction history

October 2 source/deadline review: Original interview reporting supports the forecast. Its one-to-five-year window is still open; causal attribution and a fixed measurement baseline remain necessary. No new outcome resolution. Historical status and score retained; this is not a new calibration verdict.

Dario Amodei
CEO, Anthropic · March 10, 2025
−65

AI would write 90% of code within three to six months; within twelve months it might write essentially all code.

FalseCodingJune–September 2025; second possibility March 2026 (derived from March 10, 2025)Scope error

The original CFR transcript supports the forecast and its uncertainty, but does not define a code-share denominator. The repository census measures agent-attributed activity, not 90% of all code. The historical False/−65 assessment is retained for traceability and is not newly validated by this review.

Evidence

Open-source research found more than 320,000 agent-attributed commits per month by April 2026, substantial but not evidence that AI wrote 90% of all code. Sources: claim and follow-up review; repository census.

Dated source reviews and correction history

October 2 source/deadline review: Original CFR transcript confirms two time windows and preserves the possibility qualifier for the second. Code volume and population are not defined. The repository census cannot establish an industry-wide share; the historical negative score is retained, not newly validated. Historical status and score retained; this is not a new calibration verdict.

Dario Amodei
CEO, Anthropic · October 2024, reiterated September 2026
Pending

Powerful AI could compress 50–100 years of biological progress into 5–10 years and help cure or prevent most major diseases.

PendingScience5–10 years after powerful AI; conditional

The clock begins only after Amodei’s “powerful AI” threshold, so the medical claim cannot honestly be assigned a fixed deadline until that trigger is resolved.

Source

Machines of Loving Grace; We Must Pace the Frontier.

Dated source reviews and correction history

October 2 source/deadline review: The clock starts after the defined powerful-AI threshold, not at essay publication. No fixed calendar deadline can be inferred. Historical status and score retained; this is not a new calibration verdict.

Sam Altman
CEO, OpenAI · January 6, 2025
+45

The first AI agents could “join the workforce” in 2025 and materially change company output.

Partly supportedJobsDeadline passed

Working agents arrived and enterprise adoption followed. The undefined words “join” and “materially” prevent a clean win, and OpenAI’s strongest quantitative evidence comes from its own users and staff.

Evidence

By mid-2026 OpenAI reported that every internal department used Codex as its primary AI work tool, while external adoption remained uneven. Sources: original prediction; OpenAI usage study; research paper.

Dated source reviews and correction history

October 2 source/deadline review: The precise original prediction is in Reflections, not the blog homepage. Later Codex usage research supports adoption, not a clean resolution of undefined workforce or output thresholds. Preserve the existing score. Historical status and score retained; this is not a new calibration verdict.

Sam Altman
CEO, OpenAI · June 10, 2025
Pending

Systems that can produce novel insights would likely arrive in 2026.

PendingScience2026 forecast year; no exact day specified

Resolution requires a disclosed, independently validated discovery, not a model generating a plausible new sentence or helping a human researcher work faster.

Source

The Gentle Singularity.

Dated source reviews and correction history

October 2 source/deadline review: The original essay supplies forecast years, not precise December deadlines, and retains uncertainty. No independently specified success threshold exists. Historical status and score retained; this is not a new calibration verdict.

Sam Altman
CEO, OpenAI · June 10, 2025
Pending

Robots capable of doing tasks in the real world may arrive in 2027.

PendingRobotics2027 forecast year; no exact day specified

Robots already perform constrained real-world tasks. The claim needs a stronger pre-registered bar, such as generality, autonomy and reliability across unfamiliar environments.

Source

The Gentle Singularity.

Dated source reviews and correction history

October 2 source/deadline review: The original essay supplies forecast years, not precise December deadlines, and retains uncertainty. No independently specified success threshold exists. Historical status and score retained; this is not a new calibration verdict.

Demis Hassabis
CEO, Google DeepMind · April 2025
Pending

AGI with human-level cognitive versatility is five to ten years away.

PendingCapabilitiesWindow: 2030–2035

Hassabis supplied a capability concept and a window, but no public test suite. The ledger will not let a company announcement settle the question on its own.

Source and incentive context

Google DeepMind is pursuing AGI and stands to benefit from confidence in the field’s progress. Hassabis has generally offered a wider window than Amodei. Sources: TIME interview; TIME video.

Dated source reviews and correction history

October 2 source/deadline review: Original interview supports a five-to-ten-year AGI window. Calendar years are approximate conversions from 2025, not exact deadlines. A public capability test is still required. Historical status and score retained; this is not a new calibration verdict.

Shane Legg
Co-founder and chief AGI scientist, Google DeepMind · 2023
Pending

A 50% chance of AGI with broad human cognitive competence by 2028.

PendingCapabilitiesDeadline: 2028Probability supplied

This updates a forecast Legg made in 2011. Scoring requires the operational definition discussed in the source, not whatever system receives an AGI label in 2028.

Source

Dwarkesh Podcast transcript; 2011 forecast record.

Dated source reviews and correction history

October 2 source/deadline review: Interview defines AGI through broad human cognitive competence and gives 50% by 2028; the minimal qualifier is not in the reviewed wording. A single unrealized 50% forecast is not automatically a forecasting error. Historical status and score retained; this is not a new calibration verdict.

Yann LeCun
Then chief AI scientist, Meta · 2024 Hudson Forum; recording published October 13
Pending

Developing the proposed AI capabilities could take years, if not a decade; reaching human-level AI could take years to decades, with substantial uncertainty.

PendingCapabilitiesYears to decades; no firm calendar deadline

The original human-level-AI answer has no firm calendar deadline. The former near-term exclusion and 2027–2034 window are historical paraphrases, not established by this recording. No outcome verdict is assigned.

Source

Original Hudson Forum recording; Lex Fridman transcript.

Dated source reviews and correction history

Historical v1.5 review: The Hudson Forum video was identified but could not be retrieved as a transcript. Existing coverage is not enough for a fresh primary-text correction. The October claim is not interchangeable with the separate March Lex interview. Historical status and score retained; this is not a new calibration verdict.

October 2 v1.6 source repair (supersedes the v1.5 source-access note): The event recording separates the research-program estimate (years, if not a decade) from an explicit human-level-AI answer (years to decades with large uncertainty). It does not establish the recorded 2027–2034 window or a firm ceiling. Recording published October 13, 2024; upload date is not asserted as the speaking date. Historical status and score retained.

Elon Musk
CEO, Tesla and xAI · April 2024
No score

Musk guessed that AI would probably be smarter than any one human around the end of 2025.

UnresolvableCapabilitiesAround end-2025; later answer says within two years from April 2024

No agreed scalar measure of “smarter” exists. Frontier systems exceeded every human on some tests and remained brittle on basic tasks. The deadline passed, but the wording prevents a defensible verdict.

Source

Original NBIM interview recording.

Dated source reviews and correction history

Historical v1.5 review: Original NBIM episode was located, but its spoken forecast was not retrieved in primary text. Preserve wording and historical unresolvable status; do not infer a revised deadline from derivative reports. Historical status and score retained; this is not a new calibration verdict.

October 2 v1.6 source repair (supersedes the v1.5 source-access note): The original NBIM host recording confirms probably around the end of next year, spoken April 8, 2024. A later answer adds within two years and makes the AGI definition explicit. This repairs the source and timing qualifier, not the undefined intelligence outcome. Historical status and score retained.

Elon Musk
CEO, Tesla · April 22, 2019
−100

Tesla would have more than one million robotaxis on the road in 2020.

FalseRoboticsDeadline passedMagnitude and timing error

Tesla reports launching its Robotaxi service in 2025, after the original 2020 forecast. The prior September 2026 fleet-count estimate and derived 99.96% shortfall were not primary-verified in this review and must not be treated as current evidence. Historical score −100 retained.

Evidence

Sources: Autonomy Day transcript; September 2026 fleet report; Tesla 2025 annual filing.

Dated source reviews and correction history

October 2 source/deadline review: Original Autonomy Day speech reproduction supports the 2020 forecast. Tesla reports launching its Robotaxi service in 2025. This supports a missed original launch window, but does not verify the page historical September-2026 fleet count or its error percentage. No new numeric score. Historical status and score retained; this is not a new calibration verdict.

Geoffrey Hinton
AI researcher · 2016
−70

Hinton recalled predicting in 2016 that AI would replace radiologists for reading scans within about five years, possibly ten.

FalseJobs2021; possible ten-year caveat to 2026Mechanism error

AI became valuable in image analysis, but radiologists were not made obsolete. Demand remained high, and Hinton later acknowledged that his forecast was wrong.

Evidence

The American College of Radiology still describes a workforce shortage and AI as a tool to reduce workload. Sources: Hinton retrospective; ACR workforce update.

Dated source reviews and correction history

October 2 source/deadline review: Hinton personally acknowledges the forecast was wrong and clarifies that he meant reading scans, recalling five years, possibly ten. This supports the retrospective, not a universal benchmark comparison. Existing scores remain historical. Historical status and score retained; this is not a new calibration verdict.

Geoffrey Hinton
AI researcher · December 27, 2024
Pending

In response to a question about AI causing human extinction within three decades, Hinton estimated a 10–20% chance.

PendingRiskWithin three decades of December 2024 (approximately 2054)Probability supplied

As with other probabilistic forecasts, one binary outcome cannot establish individual calibration. The value comes from preserving the probability, horizon and subsequent revisions.

Source

Original BBC interview clip.

Dated source reviews and correction history

Historical v1.5 review: The original BBC interview was not retrieved; Forbes coverage could not provide usable primary interview text. Preserve the historical probability and horizon without claiming fresh attribution verification. Historical status and score retained; this is not a new calibration verdict.

October 2 v1.6 source repair (supersedes the v1.5 source-access note): The exact December 2024 BBC interview passage supporting 10–20% over 30 years remains unavailable. Syndicated coverage and a public BBC clip lead do not establish the exact probability passage. No substitution with a later interview. Historical status and score retained.

October 2 v1.7 follow-up (supersedes the v1.6 access note): The broadcaster’s December 27, 2024 public post was retrieved. Its text describes extinction concern within two decades, without the recorded 10–20% probability and 30-year horizon. That excerpt cannot verify the missing numerical passage. The full original Today interview or numerical transcript is still required. Records 017 and 087 overlap; no replacement with later interviews. Historical status and score retained.

October 2 v1.8 original-recording review (supersedes prior source-access notes): The BBC’s own December 27, 2024 video contains the numerical exchange at 00:00–00:20. Javid supplies the extinction-within-three-decades premise; Hinton answers with a 10–20% estimate. The broadcaster’s on-video captions and direct-audio local transcription agree on the key passage. The post’s two-decade description does not replace the spoken thirty-year question. Replace derivative/wrong-source links with the original BBC clip, make the relative horizon explicit, and retain the overlap warning for 017 and 087. These are two ledger records of the same forecast, not independent predictions. This source verification is not an extinction outcome or a new calibration verdict. Historical status and score retained.

Jensen Huang
CEO, Nvidia · March 2024
Pending

AI could pass every test a human takes in as little as five years, including specialized professional exams.

PendingCapabilitiesAround 2029 as an earliest possibility; not a firm deadline

The claim concerns test performance, not general intelligence or reliable professional practice. Resolution should use a frozen test set and human comparison rule.

Source and incentive context

Nvidia’s revenue is closely tied to demand for AI compute, so forecasts of rapid capability growth have clear commercial relevance. Source: Stanford SIEPR.

Dated source reviews and correction history

October 2 source/deadline review: Event host report says as little as five years, not a guaranteed five-year deadline. The test universe is undefined. Restore possibility language and mark the derived calendar year approximate. Historical status and score retained; this is not a new calibration verdict.

Mark Zuckerberg
CEO, Meta · January / April 2025
+35

An AI coding agent with roughly mid-level-engineer capability would become possible in 2025.

Partly supportedCodingDeadline passed

The Q1 2025 transcript keeps the timing on track: capability may start becoming possible in 2025 and scale in 2026. It does not say the original deadline was shifted. Pull-request studies do not establish broad mid-level engineering equivalence. Historical +35 retained, not newly validated.

Evidence

Sources: Meta Q1 2025 earnings transcript; 2026 coding-agent task study.

Dated source reviews and correction history

October 2 source/deadline review: Q1 transcript describes possible mid-level capability in 2025 scaling into 2026, not a retraction or delayed original deadline. Pull-request acceptance research and METR productivity results do not establish a general engineering-equivalence threshold. Retain historical score with that limitation. Historical status and score retained; this is not a new calibration verdict.

Bill Gates
Microsoft co-founder · February 2025 original Fallon upload
Pending

Gates asked whether people should work two or three days a week as society adapts to AI.

PendingJobsOpen question; no explicit workweek deadline

The source frames the workweek as a question, not a timed prediction. It should not be scored as a failed or successful 2035 forecast. The historical status and score remain unchanged for traceability.

Source

Original Fallon interview recording.

Dated source reviews and correction history

Historical v1.5 review: Original Fallon recording was located but primary transcript/audio was not inspected. The ledger claims and calendar horizons are retained as historical, not freshly verified. For the separately dated 2023 claim, the original Noah interview also remains unverified; comparative superiority is not established by locating a video. Historical status and score retained; this is not a new calibration verdict.

October 2 v1.6 source repair (supersedes the v1.5 source-access note): In the original Fallon interview, Gates asks whether people should work two or three days a week. It is a question about adapting to AI, not a dated two-day-workweek forecast. The preceding decade forecast concerns intelligence, medical advice and tutoring; it must not become a workweek deadline. The original upload is February 2025, not the historical March coverage date. Historical status and score retained.

Download the ledger and inspect historical editorial scores

Use the exports for your own analysis. CSV and JSON contain the same 100 records, source URLs and current editorial status. The chart averages retained historical editorial scores for explicitly approved forecast groups. It is not a probability-calibration chart or a new validation of those scores. Pending, review, unresolvable, unverified and duplicate records do not contribute.

Public data:


Generated in your browser from the same canonical records as the API.

Historical editorial scores

These five numbers remain historical editorial judgments.The published rubric does not provide weights, component assessments or calculation receipts that reproduce the exact scores. The notes below state what the outcome evidence supports and what remains unresolved. Records, scores and display eligibility are unchanged.

Positive scorePartly supportedNegative score

Each bar shows the mean of eligible historical scores from −100 to +100, with n counting distinct approved forecast groups. The October source review did not collectively revalidate these scores. A dashed track means no eligible historical score. Five records currently contribute: 006, 008, 015, 016 and 019. This is an alphabetical display, not a leaderboard or evidence of individual probability calibration.

Which records count, and why others are excluded

Display eligibility is separate from the preserved score. The approved record must still match its reviewed claim, source, horizon, forecaster, topic, status and score. Only False or Partly supported statuses can contribute; the complete score must be an integer from −100 to +100. New or changed records are excluded until explicitly reviewed. Each duplicate group has one designated representative, and each group can contribute at most once.

Approved record Forecaster Retained score
006 Dario Amodei −65
008 Sam Altman +45
015 Elon Musk −100
016 Geoffrey Hinton −70
019 Mark Zuckerberg +35

Records 001 and 064 are explicitly excluded because their superseded historical attributions remain unresolved; 077 is excluded because its current attribution is unverified. Every other non-approved record is excluded by default. Known duplicate/overlapping groups are 009/043; 010/044; 011/071; 012/083; 013/078; 016/086; 017/087; 018/093; 019/095; 020/088; 096/097. A duplicate never acquires eligibility merely by receiving a numeric score.

Approving historical-score display does not newly validate the score. In particular, record 006 still lacks an industry-wide code-share denominator; 015’s former fleet-count/error estimate was not primary-verified; 019 lacks a specified general engineering-equivalence threshold. Their earlier qualifications remain in the ledger. All 100 rows remain available in the exports, including excluded records.

Machine-readable endpoints: JSON API v1 · CSV API v1 · Revision API v1.

Prospective policy · Methodology 1.0 · Published October 2, 2026

Scoring methodology for future assessments

This policy separates whether a forecast came true, how far it missed, and whether its stated probability was accurate. Each future assessment must expose its evidence, inputs and calculation.

Historical records, scores and eligibility remain unchanged. No existing forecast has been rescored under this policy. The current historical chart and API exports retain their existing calculations and contract; publication of this policy does not activate a new scoring engine.

1. Preserve the original forecast

Store the exact quotation, speaker, statement date, primary-source URL and passage or timestamp. Preserve qualifications such as “could,” “probably,” “if,” and “within five to ten years.”

Keep the original statement immutable. Corrections, clarifications and updated forecasts become linked revisions.

Repeated statements about the same event belong to one forecast family. They remain publicly visible but do not create additional votes in aggregate statistics.

2. Define the resolution contract

Before assessing an outcome, specify:

Required resolution contract fields
Field Required definition
Event or quantity Exactly what is predicted
Population Companies, workers, products, countries or other units covered
Measurement Metric, denominator, units and sampling method
Success rule Threshold, comparison operator and required conditions
Deadline Exact date or explicit date interval, with timezone
Human assistance What supervision, intervention or checking is permitted
Conditions Dependencies expressly stated by the forecaster
Evidence Acceptable primary sources and measurement limitations
Review cutoff Latest evidence publication date considered
Probability Explicit numeric probability, if supplied

Do not invent definitions that materially strengthen or weaken the quotation. If “mid-level engineer,” “material productivity improvement,” or another essential term cannot be resolved faithfully, mark the forecast not operationally defined.

Publish the contract before the outcome becomes known wherever possible. Contracts written after relevant outcomes are observable must be labeled retrospective and reported separately from prospective assessments.

3. Assign an evidence-supported outcome

Use these assessment states:

  • Pending: The evaluation window remains open.
  • Met: Evidence establishes every required success condition.
  • Missed: Evidence establishes failure under the stated rule.
  • Mixed: Independent, separately defined subclaims have both met and missed outcomes.
  • Unresolved: The deadline passed, but evidence cannot establish the result.
  • Not operationally defined: Essential terms cannot be measured faithfully.
  • Condition not met: An expressly conditional forecast’s prerequisite did not occur.
  • Attribution unresolved: The original statement cannot be verified.

Missing evidence does not establish a miss. A demonstration, benchmark or adoption statistic earns credit only when it measures the contracted outcome.

Publication dates and observation dates must remain separate. A study published later can establish an earlier outcome through dated observations.

If measurement uncertainty crosses the success threshold, leave the outcome unresolved.

4. Calculate scores by forecast type

Do not blend outcome, timing, magnitude, scope and mechanism into a discretionary number.

Categorical forecasts

For a resolved event:

fulfillment = 1 if met
fulfillment = 0 if missed

All other states receive null, never zero.

For genuinely independent subclaims, publish each result separately. A compound forecast’s fulfillment is:

fulfillment = number of met subclaims / number of subclaims

Use equal weights fixed in the resolution contract. Calculate the compound value only when every subclaim is resolved. Never drop unresolved subclaims and recalculate the denominator.

Conditions defining one event, such as “operating driverless service by the deadline,” are assessed together. They are not split into easy partial-credit items.

Numerical forecasts

For an exact point forecast, publish:

signed_error = predicted_value − observed_value
absolute_error = |predicted_value − observed_value|

Positive signed error means overprediction. Negative means underprediction.

Use percentage points for differences between shares. Publish relative error only when the observed value is nonzero:

relative_absolute_error = absolute_error / |observed_value|

For thresholds such as “at least 90%,” assess the threshold and report the shortfall. Do not treat the threshold as an exact point prediction.

Timing forecasts

For “by deadline” claims, report whether the deadline was met. If qualifying achievement occurs later:

days_late = achievement_date − deadline

If achievement has not been established, report “not established as of [date]”, not an invented completion date. Preserve uncertainty in dates as an interval.

Explicit probability forecasts

For a numeric probability p and resolved binary outcome y:

Brier loss = (p − y)²

Here, y = 1 when the event occurs and 0 otherwise. Lower loss is better. Brier loss measures probability error; calibration concerns how stated probabilities correspond to observed frequencies. MET verification documentation.

Do not translate “confident,” “possible,” or “likely” into invented probabilities.

5. Publish a calculation receipt

Every scored assessment must include:

  • Forecast and forecast-family IDs.
  • Methodology version and frozen resolution contract.
  • Prospective or retrospective designation.
  • Evidence URLs, exact passages, observation dates and publication dates.
  • Observed values, units, uncertainty and limitations.
  • Outcome, formula, inputs and unrounded result.
  • Reviewer, review date and any unresolved disagreement.
  • Previous assessment and explanation of any revision.

A second reviewer should be able to reproduce the result from the receipt. If a material interpretation remains disputed, publish the disagreement and withhold the numeric score.

6. Keep aggregates honest

Count each forecast family once per forecaster. Use the initial forecast; show later updates separately rather than selecting whichever performed best.

Separate categorical fulfillment, numerical error and probability loss. Do not average incompatible units or combine prospective assessments with retrospective ones.

Every summary must show its denominator and counts of pending, unresolved and excluded forecasts. Calibration charts should include only explicit numeric probabilities and resolved binary outcomes, with fixed probability bins and sample counts.

Historical editorial scores retain their existing display and eligibility. They do not enter the new methodology’s aggregates.

7. Worked examples

These are hypothetical calculations, not ledger reassessments.

Hypothetical scoring examples
Forecast Observed result Assessment
At least 90% by deadline Verified share of 60% Missed; 30 percentage-point shortfall
80% probability of launch by deadline Qualifying launch occurred Brier loss: (0.8 − 1)² = 0.04
Three independent milestones Two met; one missed Mixed; fulfillment 2/3
Three independent milestones Two met; one unresolved Overall fulfillment null
Deployment by December 31 Qualifying deployment on January 20 Missed deadline; 20 days late

8. Monthly review and versioning

Each monthly review checks due forecasts and outstanding evidence gaps. Publish only supported assessment changes.

Record every revision with its date, evidence, old value, new value and reason. Evidence corrections remain recoverable. Changes to formulas or resolution rules require a new methodology version and must not silently rewrite earlier assessments.

The ledger measures public claims against evidence. A missed forecast alone does not establish deception, regulatory capture or a coordinated influence operation; those allegations require separate evidence.

Evidence gaps and monthly maintenance

The October 1–2 reviews separate source support from outcome resolution. All historical records and scores remain recoverable. One current attribution and two superseded historical assertions still lack exact original evidence.

  • 077 · Current Hassabis attribution: the cited TIME interview does not establish the exact drugs-and-materials assertion or its former 2025–35 deadline. Needed: an original dated passage with that scope and horizon. This record remains unscored.
  • 001 · Superseded Coxon probability: current qualitative wording is supported. Needed for the old attribution: Coxon’s own September 8/9, 2026 numerical extinction estimate over ten years. Hubinger’s probability and a later interview cannot be substituted.
  • 064 · Superseded Musk Level-5/2021 assertion: current 2019/2020 milestones are supported. Needed for the old attribution: Musk’s original 2019 statement explicitly specifying Level 5 by 2021. The recovered 2021 exchange cannot be backdated.

Remaining manual outcome work includes defining faithful thresholds and populations, checking dated achievement evidence, authenticating original passages, reproducing measurements and obtaining independent review. An expired horizon alone establishes no miss. The five retained historical scores are not reproducible under the old published rubric and remain labeled accordingly.

Monthly review is configured. The existing owner-chat automation is active on a monthly cadence. Its instructions and schedule are unchanged. Configuration does not prove an ordinary scheduler run; the exact next firing timestamp was not exposed. The October reviews and this completion check were manual.

Current citation check: 100 records, 31 distinct source URLs. Direct requests were access-limited for Axios and TIME; their interview text was separately retrieved. A successful URL response is not evidence authentication. Download the dated source-availability report (JSON).

Reviewer resources

Prepare receipts separately from the ledger. A structural pass never replaces source inspection, interpretation, independent reproduction or a publication decision.

Fictional training example · No real assessment or aggregate entry

One forecast, four evidence outcomes

Every person, source, date, observation and review action in this example is invented. Example Labs says on December 15, 2026 that its coding agent will complete at least 90% of a frozen 200-ticket test set without human edits by January 31, 2027.

In this scenario, a contract frozen on December 16 requires each qualifying solution to pass every specified test and security check without human edits by January 31 at 23:59:59 UTC. All 200 tickets remain in the denominator. A fictional report published February 3 may document earlier completion, but success achieved after the deadline does not count.

Alternative scenarios for the same fictional forecast; these are not sequential ledger revisions.
Evidence by the deadline Outcome What can be reported
180 verified qualifying successes; 20 verified nonqualifying tickets Met 180/200 = 90%. Categorical fulfillment: 1. Threshold shortfall: 0 percentage points.
120 verified qualifying successes; 80 verified nonqualifying tickets Missed 120/200 = 60%. Categorical fulfillment: 0. Threshold shortfall: 30 percentage points.
120 verified qualifying successes; 20 verified nonqualifying tickets; 60 unresolved Unresolved Evidence permits 60–90%. Both met and missed remain possible. Fulfillment and scalar success-rate/shortfall results are withheld.
120 verified qualifying successes; 21 verified nonqualifying tickets; 59 unresolved Missed; magnitude unresolved At most 179/200 = 89.5%, below 90%. Categorical fulfillment: 0. Exact success rate and scalar shortfall remain withheld; evidence permits 60–89.5%.

What the fictional reviewers must check

Open the original statement and frozen ticket list; establish who said it and when. Trace each classification to complete dated run records, test results and edit provenance. Confirm the measurement matches the promised population and permitted assistance. Reproduce counts independently, inspect duplicates, and disclose disagreement. A failed attempt does not prove a ticket missed: a retry might have qualified before the deadline.

From the unresolved scenario, proving all 60 remaining tickets qualified establishes met. Proving even one never qualified by the deadline establishes missed, because at most 179 tickets could qualify. Missing logs establish neither success nor failure. The percentage intervals above are logical evidence bounds, not probability estimates.

Keep outcome and numerical uncertainty separate

For an unresolved outcome, calculation results and exact fractions remain null, with a specific withheld_reason. For a proven miss with unresolved magnitude, categorical fulfillment can be 0 while the success-rate and shortfall results remain null. Document the bounds and their derivation in the manual evidence notes. Validator 1.0 does not verify interval reasoning or authenticate the records.

This walkthrough illustrates methodology 1.0. It is not a complete receipt, proof of reviewer approval, a historical reassessment, or permission to publish an assessment. The existing fictional receipt and validator demonstration remain separate examples.

Revision history

Early labels such as “source-verified” and “calibration” are preserved historical publication descriptions, not current verification claims. Later revisions document their limitations and corrected labels.

Published changes get a dated revision; unchanged reviews keep a separate maintenance receipt. Records are never silently overwritten: a changed deadline, score or source stays visible in the revision trail.

Version Date Change
1.0 September 14, 2026 Initial source-first ledger with 20 detailed records.
1.1 September 14, 2026 Expanded to 100 source-verified claims, including 80 atomic review-queue records.
1.2 September 14, 2026 Added public CSV/JSON downloads and per-forecaster calibration chart.
1.3 September 14, 2026 Added stable versioned APIs and this auditable revision history.
1.4 October 1, 2026 Manual review of records 041, 042, 077, 079 and 095; corrected attribution and unsupported horizons in four records. No outcome scores changed. The other 95 records did not receive a fresh semantic review.
1.5 October 2, 2026 Remaining 95 records received source/deadline review; 60 records corrected using primary statements or original-interview reporting. Per-record unresolved reasons published. All 100 historical statuses and scores retained, not collectively revalidated. Manual review, not scheduler-run proof.
1.6 October 2, 2026 Manual follow-up of 22 source-repair records: 13 repaired against original posts or host recordings/transcripts; 9 remain explicitly unresolved. Workweek questions, conditional forecasts and approximate horizons corrected. All 100 historical statuses/scores and prior revisions preserved; no new outcome verdict. Not scheduler-run proof.
1.7 October 2, 2026 Manual primary-source search for the nine remaining gaps: 061, 063 and 068 repaired against original spoken recordings; six remain explicitly unresolved. Unsupported release windows and optional-work deadlines removed. Exact prior values, all 100 statuses/scores and all prior revisions preserved; no new outcome verdict. Not scheduler-run proof.
1.8 October 2, 2026 Manual inspection of original BBC Hinton clip and publisher-feed Gates audio: 017/087 source and relative horizon repaired together; 089 conditional workweek scenario restored and unsupported 2035+ deadline removed. Three gaps remain (001, 064, 070). Exact prior values, all 100 statuses/scores and all earlier revisions preserved. Source support only; no new outcome verdict or scheduler-run claim.
1.9 October 2, 2026 Original-source repairs to 001, 064 and 070: Coxon qualitative warning restored without borrowing Hubinger’s probability; Tesla 2019/2020 milestones restored without the unsupported Level-5/2021 paraphrase; November 2019 million-driverless-Teslas statement restored with no calendar deadline. Prior values and display dates preserved; original numerical Coxon and exact Level-5/2021 attributions remain unverified historical tasks. All statuses/scores unchanged.
1.10 October 2, 2026 Archived-primary attribution findings: a September 9 capture preserves Coxon’s qualitative end-of-decade warning without a probability; Tesla’s original January 27, 2021 replay locates the Level-5/2021 question and Musk’s confidence response at 31:57–32:24. Neither verifies the superseded historical assertion. All 100 current records, historical claims, statuses and scores remain unchanged; both historical gaps stay open.
1.11 October 2, 2026 Historical-score display safeguards: explicit reviewed-record eligibility, designated duplicate-group representatives, strict full-string integer scores in −100…+100, eligible status checks and fail-closed exclusion of new/changed records. Historical gaps 001/064 and unverified 077 explicitly excluded. Chart relabeled Historical editorial scores; all 100 records, claims, sources, statuses and scores plus prior history preserved. No new outcome validation or API-contract change.
1.12 October 2, 2026 Published the five historical-score outcome audits beside chart values and in their detailed records, with source links and unresolved resolution requirements. Added consistent row alignment, responsive annotation spacing and room between page sections. All 100 canonical records, historical statuses/scores, eligibility policy and prior revisions preserved. No new outcome verdict or API-contract change.
1.13 October 2, 2026 Published prospective scoring methodology 1.0 for future assessments: frozen resolution contracts, evidence-supported outcome states, type-specific calculations, reproducible receipts, duplicate safeguards and separate prospective aggregates. All 100 records, historical claims, statuses, scores, eligibility, chart calculations and prior history preserved. Policy publication only; no new scoring engine, outcome assessment or API-contract change.
1.14 October 2, 2026 Published versioned assessment receipt downloads beside prospective methodology 1.0: blank JSON template, TXT usage guide and explicitly fictional JSON worked example excluded from real aggregates. All 100 records, historical claims, statuses, scores, eligibility, chart calculations and prior history preserved. Supporting files only; no scoring-engine activation or API-contract change.
1.15 October 2, 2026 Published read-only assessment receipt validator 1.0 and its usage guide beside the receipt templates, with explicit verification limits. Local format, declared-rule and arithmetic checks only; no evidence authentication, server-side validation, scoring-engine activation or historical reassessment. All 100 records, claims, statuses, scores, eligibility, receipt-template files and prior history preserved; API contract unchanged.
1.16 October 2, 2026 Added a reproducible, explicitly fictional validator report with two calculation errors and three incomplete review fields, annotated explanations and separate input/JSON-output/TXT-notes downloads. Existing validator 1.0, receipt downloads, all 100 records, historical scores, eligibility, policy and prior revisions preserved. No real assessment, scoring-engine activation or API-contract change.
1.17 October 2, 2026 Added a short validator troubleshooting section covering common input, calculation, evidence-reference, unresolved-outcome, review-completeness and duplicate-family failures. Documentation only: all 100 records, historical scores, eligibility, validator 1.0, eight published downloads, policy and prior revisions preserved; no API-contract change or reassessment.
1.18 October 5, 2026 Clarified receipt documentation: completeness checks cover only a subset of policy requirements; unresolved receipts still need required attribution, contract and review fields; condition findings use not_met while the overall outcome uses condition_not_met. Published documentation revision 1.1 guides at new URLs and reconciled the stale local publication statement. All 100 records, historical claims, statuses, scores, eligibility, validator 1.0, original eight downloads, methodology and prior revisions preserved; no reassessment or API-contract change.
1.19 October 5, 2026 Published the printable one-page reviewer checklist PDF beside the receipt guides: 12 checkboxes, separate validator completeness and human policy review, reviewer fields and follow-up space. Reviewer aid only; not an assessment or publication approval. All 100 records, historical claims, statuses, scores, eligibility, validator 1.0, methodology, ten existing downloads and prior revisions preserved; no reassessment or API-contract change.
1.20 October 5, 2026 Completed page navigation, high-contrast responsive layout, record permalinks, forecaster filtering and paginated browsing; preserved per-record source/correction history and five historical score limitations. Added a clearly fictional manual-review walkthrough, visible current/historical evidence gaps, source availability report and direct-install SDK package archives. Reconciled the API guide with current claims, timestamp semantics, export limitations and registry authentication status. All 100 canonical records, statuses, scores, historical-score eligibility, prior revisions, methodology 1.0, receipt template 1.0, validator 1.0 and existing download/API-contract bytes unchanged. Monthly automation instructions and cadence unchanged; no new outcome assessment or claim that registry publication succeeded.
1.21 October 5, 2026 Corrected OpenAPI YAML status false from a boolean literal to the intended string in contract patch 1.0.1, with matching SDK 1.0.1 archives. Preserved earlier 1.0.0 contract/archive bytes and API v1/schema 1.0; no endpoint or record changes. Clarified contract descriptions and legacy contract limitations. Fixed page-scoped summary spacing against global theme overrides. All 100 records, historical scores, eligibility, validator and prior revisions unchanged; registry publication remains pending credentials.
1.22 October 5, 2026 SDK packaging patch 1.0.2 aligns the Python runtime version with distribution metadata and bundles the byte-identical standalone client plus OpenAPI 1.0.1. Direct archive installation is documented without implying npm/PyPI publication. Earlier archives remain immutable; SDK 1.0.1 had a stale Python __version__ marker. All API v1 endpoints, contract 1.0.1, 100 records, historical scores, eligibility, validator and prior revisions unchanged.
1.23 October 5, 2026 Mobile API reference tables now scroll horizontally with readable column widths and keyboard focus, instead of squeezing field descriptions into narrow columns. Presentation only: all 100 canonical records, historical scores, eligibility, earlier revisions, API v1/schema 1.0, OpenAPI 1.0.1, SDK 1.0.2 and published download bytes unchanged.
October 1 corrections — preserved prior records

This manual review covers five records. The remaining 95 await a fresh semantic review. Scheduled monthly-run proof remains pending.

Record Prior v1.3 claim and horizon Correction
041 AI agents will do real cognitive work in 2025. Horizon: 2025 Retrospective assertion in the June 2025 essay; excluded from outcome scoring.
042 Writing computer code will never be the same after agents arrive. Horizon: 2025–30 The former 2025–30 range was editorial and is removed. The broad claim has no measurable resolution threshold.
077 AI-designed drugs and materials will produce foundational scientific breakthroughs. Horizon: 2025–35 The linked interview does not substantiate this exact combined claim or the former 2025–35 horizon. Retained for source repair, with no outcome score.
079 Human-level AI will not arrive in the next year or two. Horizon: 2025–26 Corrected against the original transcript at 02:05:37. The former one-or-two-year paraphrase and 2025–26 horizon were unsupported; this is not an outcome resolution.
October 2 corrections — exact prior v1.4 records

All historical scores and statuses are unchanged. The previous full page and registry are archived; corrected current wording does not erase the prior record.

ID Before After
003 “Powerful AI” matching or exceeding Nobel-level experts across most disciplines could arrive in late 2026 or early 2027. | Horizon: Deadline: early 2027 | Source: https://darioamodei.com/essay/machines-of-loving-grace | Status: pending | Score: Pending Powerful AI could arrive as early as 2026, but could take much longer. | Horizon: Earliest possibility: 2026; no firm deadline | Source: https://darioamodei.com/essay/machines-of-loving-grace | Status: pending | Score: Pending
006 AI would write 90% of code within three to six months and nearly all code within a year. | Horizon: Deadline passed | Source: https://traictory.com/news/2026-08-30-amodei-90-percent-code-prediction | Status: false | Score: −65 AI would write 90% of code within three to six months; within twelve months it might write essentially all code. | Horizon: June–September 2025; second possibility March 2026 (derived from March 10, 2025) | Source: https://www.cfr.org/event/ceo-speaker-series-dario-amodei-anthropic | Status: false | Score: −65
007 Powerful AI could compress 50–100 years of biological progress into 5–10 years and help cure or prevent most major diseases. | Horizon: | Source: https://darioamodei.com/essay/machines-of-loving-grace | Status: pending | Score: Pending Powerful AI could compress 50–100 years of biological progress into 5–10 years and help cure or prevent most major diseases. | Horizon: 5–10 years after powerful AI; conditional | Source: https://darioamodei.com/essay/machines-of-loving-grace | Status: pending | Score: Pending
008 The first AI agents could “join the workforce” in 2025 and materially change company output. | Horizon: Deadline passed | Source: https://blog.samaltman.com/ | Status: partly | Score: +45 The first AI agents could “join the workforce” in 2025 and materially change company output. | Horizon: Deadline passed | Source: https://blog.samaltman.com/reflections | Status: partly | Score: +45
009 Systems that can produce novel insights would likely arrive in 2026. | Horizon: Deadline: December 2026 | Source: https://blog.samaltman.com/the-gentle-singularity | Status: pending | Score: Pending Systems that can produce novel insights would likely arrive in 2026. | Horizon: 2026 forecast year; no exact day specified | Source: https://blog.samaltman.com/the-gentle-singularity | Status: pending | Score: Pending
010 Robots capable of doing tasks in the real world may arrive in 2027. | Horizon: Deadline: December 2027 | Source: https://blog.samaltman.com/the-gentle-singularity | Status: pending | Score: Pending Robots capable of doing tasks in the real world may arrive in 2027. | Horizon: 2027 forecast year; no exact day specified | Source: https://blog.samaltman.com/the-gentle-singularity | Status: pending | Score: Pending
012 A 50% chance of “minimal AGI” by 2028. | Horizon: Deadline: 2028 | Source: https://www.cognitiverevolution.ai/2028-agi-new-architectures-and-aligning-superhuman-models-with-shane-legg-deepmind-founder-on-the-dwarkesh-podcast/ | Status: pending | Score: Pending A 50% chance of AGI with broad human cognitive competence by 2028. | Horizon: Deadline: 2028 | Source: https://www.cognitiverevolution.ai/2028-agi-new-architectures-and-aligning-superhuman-models-with-shane-legg-deepmind-founder-on-the-dwarkesh-podcast/ | Status: pending | Score: Pending
016 Hospitals should stop training radiologists because deep learning would outperform them within five years. | Horizon: Deadline: 2021 | Source: https://www.valence.co/ai-and-the-workforce/ai-unpacked-with-geoffrey-hinton | Status: false | Score: −70 Hinton recalled predicting in 2016 that AI would replace radiologists for reading scans within about five years, possibly ten. | Horizon: 2021; possible ten-year caveat to 2026 | Source: https://www.valence.co/ai-and-the-workforce/ai-unpacked-with-geoffrey-hinton | Status: false | Score: −70
018 Within five years, AI could pass every test a human takes, including specialized professional exams. | Horizon: Deadline: March 2029 | Source: https://siepr.stanford.edu/news/nvidias-jensen-huang-incredible-future-ai | Status: pending | Score: Pending AI could pass every test a human takes in as little as five years, including specialized professional exams. | Horizon: Around 2029 as an earliest possibility; not a firm deadline | Source: https://siepr.stanford.edu/news/nvidias-jensen-huang-incredible-future-ai | Status: pending | Score: Pending
021 Powerful AI will match or exceed Nobel-level ability in biology. | Horizon: 2026–27 | Source: https://darioamodei.com/essay/machines-of-loving-grace | Status: review | Score: Review Powerful AI will match or exceed Nobel-level ability in biology. | Horizon: Conditional powerful-AI definition; no fixed arrival deadline | Source: https://darioamodei.com/essay/machines-of-loving-grace | Status: review | Score: Review
022 Powerful AI will match or exceed Nobel-level ability in computer science. | Horizon: 2026–27 | Source: https://darioamodei.com/essay/machines-of-loving-grace | Status: review | Score: Review Powerful AI will match or exceed Nobel-level ability in computer science. | Horizon: Conditional powerful-AI definition; no fixed arrival deadline | Source: https://darioamodei.com/essay/machines-of-loving-grace | Status: review | Score: Review
023 Powerful AI will match or exceed Nobel-level ability in mathematics. | Horizon: 2026–27 | Source: https://darioamodei.com/essay/machines-of-loving-grace | Status: review | Score: Review Powerful AI will match or exceed Nobel-level ability in mathematics. | Horizon: Conditional powerful-AI definition; no fixed arrival deadline | Source: https://darioamodei.com/essay/machines-of-loving-grace | Status: review | Score: Review
024 Powerful AI will match or exceed Nobel-level ability in engineering. | Horizon: 2026–27 | Source: https://darioamodei.com/essay/machines-of-loving-grace | Status: review | Score: Review Powerful AI will match or exceed Nobel-level ability in engineering. | Horizon: Conditional powerful-AI definition; no fixed arrival deadline | Source: https://darioamodei.com/essay/machines-of-loving-grace | Status: review | Score: Review
025 The system will navigate the interfaces available to a human digital worker. | Horizon: 2026–27 | Source: https://darioamodei.com/essay/machines-of-loving-grace | Status: review | Score: Review The system will navigate the interfaces available to a human digital worker. | Horizon: Conditional powerful-AI definition; no fixed arrival deadline | Source: https://darioamodei.com/essay/machines-of-loving-grace | Status: review | Score: Review
026 The system will process and generate text, audio and video at expert level. | Horizon: 2026–27 | Source: https://darioamodei.com/essay/machines-of-loving-grace | Status: review | Score: Review The system will process and generate text, audio and video at expert level. | Horizon: Conditional powerful-AI definition; no fixed arrival deadline | Source: https://darioamodei.com/essay/machines-of-loving-grace | Status: review | Score: Review
027 The system will control mice and keyboards and browse the internet. | Horizon: 2026–27 | Source: https://darioamodei.com/essay/machines-of-loving-grace | Status: review | Score: Review The system will control mice and keyboards and browse the internet. | Horizon: Conditional powerful-AI definition; no fixed arrival deadline | Source: https://darioamodei.com/essay/machines-of-loving-grace | Status: review | Score: Review
028 The system will reason autonomously over tasks lasting hours, days or weeks. | Horizon: 2026–27 | Source: https://darioamodei.com/essay/machines-of-loving-grace | Status: review | Score: Review The system will reason autonomously over tasks lasting hours, days or weeks. | Horizon: Conditional powerful-AI definition; no fixed arrival deadline | Source: https://darioamodei.com/essay/machines-of-loving-grace | Status: review | Score: Review
029 The system will interface with laboratory, robotic and manufacturing equipment. | Horizon: 2026–27 | Source: https://darioamodei.com/essay/machines-of-loving-grace | Status: review | Score: Review The system will interface with laboratory, robotic and manufacturing equipment. | Horizon: Conditional powerful-AI definition; no fixed arrival deadline | Source: https://darioamodei.com/essay/machines-of-loving-grace | Status: review | Score: Review
030 A data center could concentrate the intellectual capability of a “country of geniuses.” | Horizon: 2026–27 | Source: https://darioamodei.com/essay/machines-of-loving-grace | Status: review | Score: Review A data center could concentrate the intellectual capability of a “country of geniuses.” | Horizon: Conditional powerful-AI definition; no fixed arrival deadline | Source: https://darioamodei.com/essay/machines-of-loving-grace | Status: review | Score: Review
031 A powerful model will absorb information and act at roughly 10–100 times human speed. | Horizon: 2026–27 | Source: https://darioamodei.com/essay/machines-of-loving-grace | Status: review | Score: Review A powerful model will absorb information and act at roughly 10–100 times human speed. | Horizon: Conditional powerful-AI definition; no fixed arrival deadline | Source: https://darioamodei.com/essay/machines-of-loving-grace | Status: review | Score: Review
032 AI could compress 50–100 years of biological progress into 5–10 years. | Horizon: 2031–37 | Source: https://darioamodei.com/essay/machines-of-loving-grace | Status: review | Score: Review AI could compress 50–100 years of biological progress into 5–10 years. | Horizon: 5–10 years after powerful AI; conditional | Source: https://darioamodei.com/essay/machines-of-loving-grace | Status: review | Score: Review
033 AI could reduce cancer mortality by 95% or more. | Horizon: 2031–37 | Source: https://darioamodei.com/essay/machines-of-loving-grace | Status: review | Score: Review AI could reduce cancer mortality by 95% or more. | Horizon: 5–10 years after powerful AI; conditional | Source: https://darioamodei.com/essay/machines-of-loving-grace | Status: review | Score: Review
034 AI could reduce cancer incidence by 95% or more. | Horizon: 2031–37 | Source: https://darioamodei.com/essay/machines-of-loving-grace | Status: review | Score: Review AI could reduce cancer incidence by 95% or more. | Horizon: 5–10 years after powerful AI; conditional | Source: https://darioamodei.com/essay/machines-of-loving-grace | Status: review | Score: Review
035 Most genetic disease could be prevented through improved embryo screening. | Horizon: 2031–37 | Source: https://darioamodei.com/essay/machines-of-loving-grace | Status: review | Score: Review Most genetic disease could be prevented through improved embryo screening. | Horizon: 5–10 years after powerful AI; conditional | Source: https://darioamodei.com/essay/machines-of-loving-grace | Status: review | Score: Review
036 Most genetic disease could be cured in existing people with safer gene editing. | Horizon: 2031–37 | Source: https://darioamodei.com/essay/machines-of-loving-grace | Status: review | Score: Review Most genetic disease could be cured in existing people with safer gene editing. | Horizon: 5–10 years after powerful AI; conditional | Source: https://darioamodei.com/essay/machines-of-loving-grace | Status: review | Score: Review
037 Alzheimer’s disease could eventually be prevented with better measurement and intervention. | Horizon: 2031–37 | Source: https://darioamodei.com/essay/machines-of-loving-grace | Status: review | Score: Review Alzheimer’s disease could eventually be prevented with better measurement and intervention. | Horizon: 5–10 years after powerful AI; conditional | Source: https://darioamodei.com/essay/machines-of-loving-grace | Status: review | Score: Review
038 Most mental illness could be effectively cured. | Horizon: 2031–37 | Source: https://darioamodei.com/essay/machines-of-loving-grace | Status: review | Score: Review Most mental illness could be effectively cured. | Horizon: 5–10 years after powerful AI; conditional | Source: https://darioamodei.com/essay/machines-of-loving-grace | Status: review | Score: Review
039 AI-accelerated logistics could improve global distribution of health interventions. | Horizon: 2031–37 | Source: https://darioamodei.com/essay/machines-of-loving-grace | Status: review | Score: Review AI-accelerated logistics could improve global distribution of health interventions. | Horizon: 5–10 years after powerful AI; conditional | Source: https://darioamodei.com/essay/machines-of-loving-grace | Status: review | Score: Review
040 Personalized cancer treatment regimens could scale beyond today’s specialist bottleneck. | Horizon: 2031–37 | Source: https://darioamodei.com/essay/machines-of-loving-grace | Status: review | Score: Review Personalized cancer treatment regimens could scale beyond today’s specialist bottleneck. | Horizon: 5–10 years after powerful AI; conditional | Source: https://darioamodei.com/essay/machines-of-loving-grace | Status: review | Score: Review
043 Systems able to figure out novel insights will arrive in 2026. | Horizon: 2026 | Source: https://blog.samaltman.com/the-gentle-singularity | Status: review | Score: Review Systems able to figure out novel insights will likely arrive in 2026. | Horizon: 2026 | Source: https://blog.samaltman.com/the-gentle-singularity | Status: review | Score: Review
044 Robots able to do useful tasks in the physical world will arrive in 2027. | Horizon: 2027 | Source: https://blog.samaltman.com/the-gentle-singularity | Status: review | Score: Review Robots able to do tasks in the real world may arrive in 2027. | Horizon: 2027 | Source: https://blog.samaltman.com/the-gentle-singularity | Status: review | Score: Review
045 More people will create software and art, and demand will expand too. | Horizon: 2030 | Source: https://blog.samaltman.com/the-gentle-singularity | Status: review | Score: Review More people will create software and art, and demand will expand too. | Horizon: No explicit deadline | Source: https://blog.samaltman.com/the-gentle-singularity | Status: review | Score: Review
046 Experts will remain much better than novices if they adopt new tools. | Horizon: 2030 | Source: https://blog.samaltman.com/the-gentle-singularity | Status: review | Score: Review Experts will probably remain much better than novices if they adopt new tools. | Horizon: No explicit deadline | Source: https://blog.samaltman.com/the-gentle-singularity | Status: review | Score: Review
048 The 2030s will be radically different in important ways. | Horizon: 2030s | Source: https://blog.samaltman.com/the-gentle-singularity | Status: review | Score: Review The 2030s are likely to be radically different in important ways. | Horizon: 2030s | Source: https://blog.samaltman.com/the-gentle-singularity | Status: review | Score: Review
051 AI progress could solve high-energy physics in one year. | Horizon: 2030s | Source: https://blog.samaltman.com/the-gentle-singularity | Status: review | Score: Review An illustrative scenario by 2035 could move from a high-energy physics breakthrough one year to beginning space colonization the next. | Horizon: Illustrative scenario by 2035; not a one-year research deadline | Source: https://blog.samaltman.com/the-gentle-singularity | Status: review | Score: Review
052 A major physics breakthrough could be followed by the start of space colonization. | Horizon: 2030s | Source: https://blog.samaltman.com/the-gentle-singularity | Status: review | Score: Review A major physics breakthrough could be followed by the start of space colonization. | Horizon: Illustrative scenario by 2035; not a firm deadline | Source: https://blog.samaltman.com/the-gentle-singularity | Status: review | Score: Review
053 True high-bandwidth brain-computer interfaces may arrive after major AI breakthroughs. | Horizon: 2030s | Source: https://blog.samaltman.com/the-gentle-singularity | Status: review | Score: Review True high-bandwidth brain-computer interfaces may arrive after major AI breakthroughs. | Horizon: Illustrative scenario by 2035; not a firm deadline | Source: https://blog.samaltman.com/the-gentle-singularity | Status: review | Score: Review
054 A million humanoid robots could be produced through an automated supply chain. | Horizon: 2030s | Source: https://blog.samaltman.com/the-gentle-singularity | Status: review | Score: Review If the first million humanoid robots are built conventionally, they could operate the supply chain to build more robots. | Horizon: Conditional scenario; no explicit deadline | Source: https://blog.samaltman.com/the-gentle-singularity | Status: review | Score: Review
055 Robots could operate mines, factories and logistics to build more robots. | Horizon: 2030s | Source: https://blog.samaltman.com/the-gentle-singularity | Status: review | Score: Review Robots could operate mines, factories and logistics to build more robots. | Horizon: Conditional scenario; no explicit deadline | Source: https://blog.samaltman.com/the-gentle-singularity | Status: review | Score: Review
056 Data-center production could become substantially automated. | Horizon: 2030s | Source: https://blog.samaltman.com/the-gentle-singularity | Status: review | Score: Review Data-center production could become substantially automated. | Horizon: No explicit deadline | Source: https://blog.samaltman.com/the-gentle-singularity | Status: review | Score: Review
057 The cost of intelligence could converge toward the cost of electricity. | Horizon: 2030s | Source: https://blog.samaltman.com/the-gentle-singularity | Status: review | Score: Review The cost of intelligence could converge toward the cost of electricity. | Horizon: No explicit deadline | Source: https://blog.samaltman.com/the-gentle-singularity | Status: review | Score: Review
058 A new social contract could emerge through gradual policy changes. | Horizon: 2030s | Source: https://blog.samaltman.com/the-gentle-singularity | Status: review | Score: Review A new social contract could emerge through gradual policy changes. | Horizon: A few decades from 2025; approximate | Source: https://blog.samaltman.com/the-gentle-singularity | Status: review | Score: Review
059 People will adapt to rapid technological change. | Horizon: 2030s | Source: https://blog.samaltman.com/the-gentle-singularity | Status: review | Score: Review People will adapt to rapid technological change. | Horizon: No explicit deadline | Source: https://blog.samaltman.com/the-gentle-singularity | Status: review | Score: Review
060 The rate of new scientific wonders will become immense. | Horizon: 2030s | Source: https://blog.samaltman.com/the-gentle-singularity | Status: review | Score: Review The rate of new scientific wonders will become immense. | Horizon: Illustrative possibilities by 2035; no defined threshold | Source: https://blog.samaltman.com/the-gentle-singularity | Status: review | Score: Review
062 A Tesla would complete a coast-to-coast autonomous drive by the end of 2017. | Horizon: 2017 | Source: https://www.elonmuskarchive.org/video/tesla-autonomy-day-2019 | Status: review | Score: Review A Tesla would complete a coast-to-coast autonomous drive by the end of 2017. | Horizon: 2017 | Source: https://www.elonmuskarchive.org/video/ted-2017-04-28 | Status: review | Score: Review
066 Drivers would be able to sleep in their Tesla while it drives within roughly two years. | Horizon: 2019 | Source: https://www.elonmuskarchive.org/video/tesla-autonomy-day-2019 | Status: review | Score: Review Drivers would be able to sleep in their Tesla while it drives within roughly two years. | Horizon: 2019 | Source: https://www.elonmuskarchive.org/video/ted-2017-04-28 | Status: review | Score: Review
067 A Tesla on the robotaxi network could generate $10,000–$30,000 per year. | Horizon: 2020s | Source: https://www.elonmuskarchive.org/video/tesla-autonomy-day-2019 | Status: review | Score: Review An operating Tesla robotaxi could generate approximately $30,000 in annual gross profit. | Horizon: Conditional projection; no explicit deadline | Source: https://www.elonmuskarchive.org/video/tesla-autonomy-day-2019 | Status: review | Score: Review
069 Tesla’s autonomy software would become a major source of recurring fleet income. | Horizon: 2020s | Source: https://www.elonmuskarchive.org/video/tesla-autonomy-day-2019 | Status: review | Score: Review Tesla’s autonomy software would become a major source of recurring fleet income. | Horizon: Conditional business scenario; no explicit deadline | Source: https://www.elonmuskarchive.org/video/tesla-autonomy-day-2019 | Status: review | Score: Review
076 AGI could become the ultimate tool for advancing science. | Horizon: 2030s | Source: https://time.com/7277608/demis-hassabis-interview-time100-2025/ | Status: review | Score: Review AGI could become the ultimate tool for advancing science. | Horizon: Conditional on AGI; no separate deadline | Source: https://time.com/7277608/demis-hassabis-interview-time100-2025/ | Status: review | Score: Review
080 Scaling current language models alone will not produce human-level intelligence. | Horizon: 2024–34 | Source: https://lexfridman.com/?p=5821 | Status: review | Score: Review Scaling current language models alone will not produce human-level intelligence. | Horizon: Architectural claim; no explicit deadline | Source: https://lexfridman.com/?p=5821 | Status: review | Score: Review
081 World models are a required route toward human-level AI. | Horizon: 2024–34 | Source: https://lexfridman.com/?p=5821 | Status: review | Score: Review World models are a required route toward human-level AI. | Horizon: Architectural claim; no explicit deadline | Source: https://lexfridman.com/?p=5821 | Status: review | Score: Review
082 A real robotics industry will emerge over the next decade. | Horizon: 2024–34 | Source: https://lexfridman.com/?p=5821 | Status: review | Score: Review The next decade could see the emergence of a robotics industry beyond pre-programmed behavior. | Horizon: 2024–34 | Source: https://lexfridman.com/?p=5821 | Status: review | Score: Review
083 There is a 50% chance of minimal AGI by 2028. | Horizon: 2028 | Source: https://www.cognitiverevolution.ai/2028-agi-new-architectures-and-aligning-superhuman-models-with-shane-legg-deepmind-founder-on-the-dwarkesh-podcast/ | Status: review | Score: Review There is a 50% chance of AGI with broad human cognitive competence by 2028. | Horizon: 2028 | Source: https://www.cognitiverevolution.ai/2028-agi-new-architectures-and-aligning-superhuman-models-with-shane-legg-deepmind-founder-on-the-dwarkesh-podcast/ | Status: review | Score: Review
084 The probability of human-level AI reaches 90% by 2050. | Horizon: 2050 | Source: https://www.cognitiverevolution.ai/2028-agi-new-architectures-and-aligning-superhuman-models-with-shane-legg-deepmind-founder-on-the-dwarkesh-podcast/ | Status: review | Score: Review In the 2011 estimate, human-level AI had a 90% chance by 2050, conditional on no wars or disasters and favorable development. | Horizon: 2050 | Source: https://www.lesswrong.com/posts/No5JpRCHzBrWA4jmS/q-and-a-with-shane-legg-on-risks-from-ai | Status: review | Score: Review
085 The probability of human-level AI was estimated at 10% by 2018. | Horizon: 2018 | Source: https://www.cognitiverevolution.ai/2028-agi-new-architectures-and-aligning-superhuman-models-with-shane-legg-deepmind-founder-on-the-dwarkesh-podcast/ | Status: review | Score: Review In the 2011 estimate, human-level AI had a 10% chance by 2018, conditional on no wars or disasters and favorable development. | Horizon: 2018 | Source: https://www.lesswrong.com/posts/No5JpRCHzBrWA4jmS/q-and-a-with-shane-legg-on-risks-from-ai | Status: review | Score: Review
086 Radiologists would no longer need to be trained within five years. | Horizon: 2021 | Source: https://www.valence.co/ai-and-the-workforce/ai-unpacked-with-geoffrey-hinton | Status: review | Score: Review Hinton recalled forecasting that AI would replace radiologists for reading scans in five years, possibly ten. | Horizon: 2021; possible ten-year caveat to 2026 | Source: https://www.valence.co/ai-and-the-workforce/ai-unpacked-with-geoffrey-hinton | Status: review | Score: Review
093 AI will pass every test a human takes within five years. | Horizon: 2029 | Source: https://siepr.stanford.edu/news/nvidias-jensen-huang-incredible-future-ai | Status: review | Score: Review AI could pass every test a human takes in as little as five years. | Horizon: Around 2029 as an earliest possibility; not a firm deadline | Source: https://siepr.stanford.edu/news/nvidias-jensen-huang-incredible-future-ai | Status: review | Score: Review
094 AI will create more and better jobs over the coming decade. | Horizon: 2035 | Source: https://siepr.stanford.edu/news/nvidias-jensen-huang-incredible-future-ai | Status: review | Score: Review AI will create more and better jobs over the coming decade. | Horizon: 2035 | Source: https://www.axios.com/2025/07/14/ai-jobs-nvidia-jensen-huang-dario-amodei | Status: review | Score: Review
096 AI coding agents will perform a substantial part of AI research and development by 2026. | Horizon: 2026 | Source: https://cdn.arstechnica.net/wp-content/uploads/2025/06/META-Q1-2025-Earnings-Call-Transcript-1.pdf | Status: review | Score: Review AI coding agents are expected to perform a substantial part of AI research and development by mid-to-late 2026. | Horizon: Mid-to-late 2026 | Source: https://cdn.arstechnica.net/wp-content/uploads/2025/06/META-Q1-2025-Earnings-Call-Transcript-1.pdf | Status: review | Score: Review
097 Meta and peer labs will use AI engineers to build much of the next generation of AI. | Horizon: 2026+ | Source: https://cdn.arstechnica.net/wp-content/uploads/2025/06/META-Q1-2025-Earnings-Call-Transcript-1.pdf | Status: review | Score: Review AI coding agents could do a substantial part of Meta AI research and development by mid-to-late 2026. | Horizon: Mid-to-late 2026 | Source: https://cdn.arstechnica.net/wp-content/uploads/2025/06/META-Q1-2025-Earnings-Call-Transcript-1.pdf | Status: review | Score: Review
October 2 review receipt — all remaining 95 records

This is a manual source/deadline audit, not an ordinary monthly scheduler invocation or blanket outcome verification. Source-access limitations and unresolved attribution are explicit below. Historical numeric scores are unchanged; their retention is not endorsement of the old scoring method. The other five records retain their October 1 review.

ID / date Decision and limitations Inspected or attempted sources
001 / 2026-10-02 unresolved source access: The original AP link could not be accessed. A later original TMZ interview report corroborates the broad estimate but does not verify the original September 8 attribution. Historical record retained; no source replacement or outcome finding. No new outcome verdict or score assigned. Source 1 · Source 2
002 / 2026-10-02 original post not verified: Linked reporting supports the attribution, but the original X post was not retrieved. Preserve the historical probability and horizon; this is not a fresh primary-post verification. No new outcome verdict or score assigned. Source 1
003 / 2026-10-02 supported correction: The essay gives 2026 as an earliest possibility and allows a much longer wait. It does not supply the recorded late-2026/early-2027 cutoff. No new outcome verdict or score assigned. Source 1
Basic assumptions and framework
004 / 2026-10-02 original interview supported; outcome open: Original interview reporting supports the forecast. Its one-to-five-year window is still open; causal attribution and a fixed measurement baseline remain necessary. No new outcome resolution. No new outcome verdict or score assigned. Source 1
Axios interview, May 28, 2025
005 / 2026-10-02 original interview supported; outcome open: Original interview reporting supports the forecast. Its one-to-five-year window is still open; causal attribution and a fixed measurement baseline remain necessary. No new outcome resolution. No new outcome verdict or score assigned. Source 1
Axios interview, May 28, 2025
006 / 2026-10-02 supported source and wording correction; score retained: Original CFR transcript confirms two time windows and preserves the possibility qualifier for the second. Code volume and population are not defined. The repository census cannot establish an industry-wide share; the historical negative score is retained, not newly validated. No new outcome verdict or score assigned. Source 1 · Source 2
CFR code-writing answer; census abstract
007 / 2026-10-02 supported conditional horizon correction: The clock starts after the defined powerful-AI threshold, not at essay publication. No fixed calendar deadline can be inferred. No new outcome verdict or score assigned. Source 1
Framework; biology summary
008 / 2026-10-02 supported source repair; score retained: The precise original prediction is in Reflections, not the blog homepage. Later Codex usage research supports adoption, not a clean resolution of undefined workforce or output thresholds. Preserve the existing score. No new outcome verdict or score assigned. Source 1 · Source 2
Reflections workforce paragraph; Codex study abstract
009 / 2026-10-02 supported horizon clarification: The original essay supplies forecast years, not precise December deadlines, and retains uncertainty. No independently specified success threshold exists. No new outcome verdict or score assigned. Source 1
2025/2026/2027 paragraph
010 / 2026-10-02 supported horizon clarification: The original essay supplies forecast years, not precise December deadlines, and retains uncertainty. No independently specified success threshold exists. No new outcome verdict or score assigned. Source 1
2025/2026/2027 paragraph
011 / 2026-10-02 original interview supported; outcome open: Original interview supports a five-to-ten-year AGI window. Calendar years are approximate conversions from 2025, not exact deadlines. A public capability test is still required. No new outcome verdict or score assigned. Source 1
AGI timeline and scientific-discovery definition
012 / 2026-10-02 supported wording clarification: Interview defines AGI through broad human cognitive competence and gives 50% by 2028; the minimal qualifier is not in the reviewed wording. A single unrealized 50% forecast is not automatically a forecasting error. No new outcome verdict or score assigned. Source 1
Full transcript: definition and Timelines
013 / 2026-10-02 original event not text-verified: The Hudson Forum video was identified but could not be retrieved as a transcript. Existing coverage is not enough for a fresh primary-text correction. The October claim is not interchangeable with the separate March Lex interview. No new outcome verdict or score assigned. Source 1 · Source 2
014 / 2026-10-02 original recording not text-verified: Original NBIM episode was located, but its spoken forecast was not retrieved in primary text. Preserve wording and historical unresolvable status; do not infer a revised deadline from derivative reports. No new outcome verdict or score assigned. Source 1 · Source 2
015 / 2026-10-02 forecast supported; historical verdict retained: Original Autonomy Day speech reproduction supports the 2020 forecast. Tesla reports launching its Robotaxi service in 2025. This supports a missed original launch window, but does not verify the page historical September-2026 fleet count or its error percentage. No new numeric score. No new outcome verdict or score assigned. Source 1 · Source 2
Autonomy Day next-year robotaxis; Tesla Q4 2025 update pp. 4, 12
016 / 2026-10-02 primary retrospective supported; scope clarified: Hinton personally acknowledges the forecast was wrong and clarifies that he meant reading scans, recalling five years, possibly ten. This supports the retrospective, not a universal benchmark comparison. Existing scores remain historical. No new outcome verdict or score assigned. Source 1
2016 prediction retrospective
017 / 2026-10-02 original BBC interview unavailable: The original BBC interview was not retrieved; Forbes coverage could not provide usable primary interview text. Preserve the historical probability and horizon without claiming fresh attribution verification. No new outcome verdict or score assigned. Source 1
018 / 2026-10-02 supported possibility and horizon correction: Event host report says as little as five years, not a guaranteed five-year deadline. The test universe is undefined. Restore possibility language and mark the derived calendar year approximate. No new outcome verdict or score assigned. Source 1
Opening report of 2024 summit
019 / 2026-10-02 primary timing supported; historical score retained: Q1 transcript describes possible mid-level capability in 2025 scaling into 2026, not a retraction or delayed original deadline. Pull-request acceptance research and METR productivity results do not establish a general engineering-equivalence threshold. Retain historical score with that limitation. No new outcome verdict or score assigned. Source 1 · Source 2 · Source 3
Printed transcript p.14
020 / 2026-10-02 original interviews not text-verified: Original Fallon recording was located but primary transcript/audio was not inspected. The ledger claims and calendar horizons are retained as historical, not freshly verified. For the separately dated 2023 claim, the original Noah interview also remains unverified; comparative superiority is not established by locating a video. No new outcome verdict or score assigned. Source 1 · Source 2
021 / 2026-10-02 conditional definition, not independent dated forecast: This is part of the essay stipulated powerful-AI definition. It is not a separate firm 2026–27 forecast. Capabilities are conditional and require the full threshold, not isolated demonstrations. No new outcome verdict or score assigned. Source 1
Framework capability bullets
022 / 2026-10-02 conditional definition, not independent dated forecast: This is part of the essay stipulated powerful-AI definition. It is not a separate firm 2026–27 forecast. Capabilities are conditional and require the full threshold, not isolated demonstrations. No new outcome verdict or score assigned. Source 1
Framework capability bullets
023 / 2026-10-02 conditional definition, not independent dated forecast: This is part of the essay stipulated powerful-AI definition. It is not a separate firm 2026–27 forecast. Capabilities are conditional and require the full threshold, not isolated demonstrations. No new outcome verdict or score assigned. Source 1
Framework capability bullets
024 / 2026-10-02 conditional definition, not independent dated forecast: This is part of the essay stipulated powerful-AI definition. It is not a separate firm 2026–27 forecast. Capabilities are conditional and require the full threshold, not isolated demonstrations. No new outcome verdict or score assigned. Source 1
Framework capability bullets
025 / 2026-10-02 conditional definition, not independent dated forecast: This is part of the essay stipulated powerful-AI definition. It is not a separate firm 2026–27 forecast. Capabilities are conditional and require the full threshold, not isolated demonstrations. No new outcome verdict or score assigned. Source 1
Framework capability bullets
026 / 2026-10-02 conditional definition, not independent dated forecast: This is part of the essay stipulated powerful-AI definition. It is not a separate firm 2026–27 forecast. Capabilities are conditional and require the full threshold, not isolated demonstrations. No new outcome verdict or score assigned. Source 1
Framework capability bullets
027 / 2026-10-02 conditional definition, not independent dated forecast: This is part of the essay stipulated powerful-AI definition. It is not a separate firm 2026–27 forecast. Capabilities are conditional and require the full threshold, not isolated demonstrations. No new outcome verdict or score assigned. Source 1
Framework capability bullets
028 / 2026-10-02 conditional definition, not independent dated forecast: This is part of the essay stipulated powerful-AI definition. It is not a separate firm 2026–27 forecast. Capabilities are conditional and require the full threshold, not isolated demonstrations. No new outcome verdict or score assigned. Source 1
Framework capability bullets
029 / 2026-10-02 conditional definition, not independent dated forecast: This is part of the essay stipulated powerful-AI definition. It is not a separate firm 2026–27 forecast. Capabilities are conditional and require the full threshold, not isolated demonstrations. No new outcome verdict or score assigned. Source 1
Framework capability bullets
030 / 2026-10-02 conditional definition, not independent dated forecast: This is part of the essay stipulated powerful-AI definition. It is not a separate firm 2026–27 forecast. Capabilities are conditional and require the full threshold, not isolated demonstrations. No new outcome verdict or score assigned. Source 1
Framework capability bullets
031 / 2026-10-02 conditional definition, not independent dated forecast: This is part of the essay stipulated powerful-AI definition. It is not a separate firm 2026–27 forecast. Capabilities are conditional and require the full threshold, not isolated demonstrations. No new outcome verdict or score assigned. Source 1
Framework capability bullets
032 / 2026-10-02 supported conditional horizon correction: The essay postulates benefits over 5–10 years after powerful AI. The former 2031–37 range was editorial; conditions, biological limits and deployment constraints remain. No present medical outcome is asserted. No new outcome verdict or score assigned. Source 1
Biology; mental health; distribution of health interventions
033 / 2026-10-02 supported conditional horizon correction: The essay postulates benefits over 5–10 years after powerful AI. The former 2031–37 range was editorial; conditions, biological limits and deployment constraints remain. No present medical outcome is asserted. No new outcome verdict or score assigned. Source 1
Biology; mental health; distribution of health interventions
034 / 2026-10-02 supported conditional horizon correction: The essay postulates benefits over 5–10 years after powerful AI. The former 2031–37 range was editorial; conditions, biological limits and deployment constraints remain. No present medical outcome is asserted. No new outcome verdict or score assigned. Source 1
Biology; mental health; distribution of health interventions
035 / 2026-10-02 supported conditional horizon correction: The essay postulates benefits over 5–10 years after powerful AI. The former 2031–37 range was editorial; conditions, biological limits and deployment constraints remain. No present medical outcome is asserted. No new outcome verdict or score assigned. Source 1
Biology; mental health; distribution of health interventions
036 / 2026-10-02 supported conditional horizon correction: The essay postulates benefits over 5–10 years after powerful AI. The former 2031–37 range was editorial; conditions, biological limits and deployment constraints remain. No present medical outcome is asserted. No new outcome verdict or score assigned. Source 1
Biology; mental health; distribution of health interventions
037 / 2026-10-02 supported conditional horizon correction: The essay postulates benefits over 5–10 years after powerful AI. The former 2031–37 range was editorial; conditions, biological limits and deployment constraints remain. No present medical outcome is asserted. No new outcome verdict or score assigned. Source 1
Biology; mental health; distribution of health interventions
038 / 2026-10-02 supported conditional horizon correction: The essay postulates benefits over 5–10 years after powerful AI. The former 2031–37 range was editorial; conditions, biological limits and deployment constraints remain. No present medical outcome is asserted. No new outcome verdict or score assigned. Source 1
Biology; mental health; distribution of health interventions
039 / 2026-10-02 supported conditional horizon correction: The essay postulates benefits over 5–10 years after powerful AI. The former 2031–37 range was editorial; conditions, biological limits and deployment constraints remain. No present medical outcome is asserted. No new outcome verdict or score assigned. Source 1
Biology; mental health; distribution of health interventions
040 / 2026-10-02 supported conditional horizon correction: The essay postulates benefits over 5–10 years after powerful AI. The former 2031–37 range was editorial; conditions, biological limits and deployment constraints remain. No present medical outcome is asserted. No new outcome verdict or score assigned. Source 1
Biology; mental health; distribution of health interventions
043 / 2026-10-02 supported uncertainty correction: The source uses likely for 2026 and may for 2027. The ledger had replaced uncertainty with will. No new outcome finding. No new outcome verdict or score assigned. Source 1
2025/2026/2027 paragraph
044 / 2026-10-02 supported uncertainty correction: The source uses likely for 2026 and may for 2027. The ledger had replaced uncertainty with will. No new outcome finding. No new outcome verdict or score assigned. Source 1
2025/2026/2027 paragraph
045 / 2026-10-02 supported qualifier/horizon correction: The source does not date these propositions to 2030. Experts retaining an advantage is qualified by probably and adoption of new tools. No new outcome verdict or score assigned. Source 1
Software/art paragraph
046 / 2026-10-02 supported qualifier/horizon correction: The source does not date these propositions to 2030. Experts retaining an advantage is qualified by probably and adoption of new tools. No new outcome verdict or score assigned. Source 1
Software/art paragraph
047 / 2026-10-02 wording and period supported; outcome open: The essay supports the stated comparison or decade. Terms such as abundance and productivity lack an operational outcome threshold; no early resolution. No new outcome verdict or score assigned. Source 1
2030 comparison and 2030s abundance
048 / 2026-10-02 supported uncertainty correction: The essay describes radical differences as likely, not certain. Broad social change is not a measurable binary outcome without an explicit rule. No new outcome verdict or score assigned. Source 1
2030s paragraph
049 / 2026-10-02 wording and period supported; outcome open: The essay supports the stated comparison or decade. Terms such as abundance and productivity lack an operational outcome threshold; no early resolution. No new outcome verdict or score assigned. Source 1
2030 comparison and 2030s abundance
050 / 2026-10-02 wording and period supported; outcome open: The essay supports the stated comparison or decade. Terms such as abundance and productivity lack an operational outcome threshold; no early resolution. No new outcome verdict or score assigned. Source 1
2030 comparison and 2030s abundance
051 / 2026-10-02 supported illustrative-scenario clarification: The passage offers illustrative possibilities by 2035, not one-year research-duration promises or guaranteed discovery deadlines. Preserve speculative scope. No new outcome verdict or score assigned. Source 1
By-2035 examples
052 / 2026-10-02 supported illustrative-scenario clarification: The passage offers illustrative possibilities by 2035, not one-year research-duration promises or guaranteed discovery deadlines. Preserve speculative scope. No new outcome verdict or score assigned. Source 1
By-2035 examples
053 / 2026-10-02 supported illustrative-scenario clarification: The passage offers illustrative possibilities by 2035, not one-year research-duration promises or guaranteed discovery deadlines. Preserve speculative scope. No new outcome verdict or score assigned. Source 1
By-2035 examples
054 / 2026-10-02 supported conditional-scenario correction: The first million robots are hypothesized to be built conventionally, then automate the supply chain to build more. No explicit decade deadline is given. No new outcome verdict or score assigned. Source 1
First-million humanoid robots conditional
055 / 2026-10-02 supported conditional-scenario correction: The first million robots are hypothesized to be built conventionally, then automate the supply chain to build more. No explicit decade deadline is given. No new outcome verdict or score assigned. Source 1
First-million humanoid robots conditional
056 / 2026-10-02 supported horizon correction: Automation and eventual cost convergence are conditional future propositions without explicit calendar deadlines. No new outcome verdict or score assigned. Source 1
Data-center production and electricity cost
057 / 2026-10-02 supported horizon correction: Automation and eventual cost convergence are conditional future propositions without explicit calendar deadlines. No new outcome verdict or score assigned. Source 1
Data-center production and electricity cost
058 / 2026-10-02 supported relative-horizon correction: The essay says changes may accumulate over a few decades; it does not restrict the claim to the 2030s. No new outcome verdict or score assigned. Source 1
Social-contract paragraph
059 / 2026-10-02 supported horizon correction: General adaptation claim has no dated deadline or explicit measurement threshold. No new outcome verdict or score assigned. Source 1
Adaptation paragraphs
060 / 2026-10-02 supported illustrative-scenario clarification: The passage offers illustrative possibilities by 2035, not one-year research-duration promises or guaranteed discovery deadlines. Preserve speculative scope. No new outcome verdict or score assigned. Source 1
By-2035 examples
061 / 2026-10-02 retrospective support; original date unresolved: The 2019 speech describes hardware designed for robotaxis since October 2016, but the original 2016 announcement now redirects. This does not independently verify the original date or hardware sufficiency outcome. No new outcome verdict or score assigned. Source 1 · Source 2
062 / 2026-10-02 supported transcript-source repair; outcome unresolved: The 2017 TED speech reproduction, not the 2019 citation, supports the stated timing. Official TED page confirms event identity; its transcript was not exposed. Current supervised FSD is not proof of sleep-capable autonomy or of the historical exact demonstration date. No new outcome verdict or score assigned. Source 1 · Source 2 · Source 3
2017 cross-country and sleep-capable autonomy answers
063 / 2026-10-02 attribution or deadline unresolved: The linked 2019 speech does not verify this record as dated and scoped. Historical wording/horizon retained with this source-repair warning; no new miss, replacement forecast, or inferred deadline. No new outcome verdict or score assigned. Source 1
064 / 2026-10-02 attribution or deadline unresolved: The linked 2019 speech does not verify this record as dated and scoped. Historical wording/horizon retained with this source-repair warning; no new miss, replacement forecast, or inferred deadline. No new outcome verdict or score assigned. Source 1
065 / 2026-10-02 forecast supported; historical verdict retained: Original Autonomy Day speech reproduction supports the 2020 forecast. Tesla reports launching its Robotaxi service in 2025. This supports a missed original launch window, but does not verify the page historical September-2026 fleet count or its error percentage. No new numeric score. No new outcome verdict or score assigned. Source 1 · Source 2
Autonomy Day next-year robotaxis; Tesla Q4 2025 update pp. 4, 12
066 / 2026-10-02 supported transcript-source repair; outcome unresolved: The 2017 TED speech reproduction, not the 2019 citation, supports the stated timing. Official TED page confirms event identity; its transcript was not exposed. Current supervised FSD is not proof of sleep-capable autonomy or of the historical exact demonstration date. No new outcome verdict or score assigned. Source 1 · Source 2 · Source 3
2017 cross-country and sleep-capable autonomy answers
067 / 2026-10-02 supported financial-scope correction: The speech gives an approximate annual gross-profit projection of $30,000 for an operating robotaxi, not a $10,000–$30,000 revenue range. This is a conditional unit-economic projection, without a fixed decade deadline. No new outcome verdict or score assigned. Source 1
Robotaxi gross-profit slide discussion
068 / 2026-10-02 attribution or deadline unresolved: The linked 2019 speech does not verify this record as dated and scoped. Historical wording/horizon retained with this source-repair warning; no new miss, replacement forecast, or inferred deadline. No new outcome verdict or score assigned. Source 1
069 / 2026-10-02 supported horizon correction: The revenue-sharing business scenario is supported, but a specific 2020s resolution deadline is not supplied. Commercial significance needs a quantitative threshold. No new outcome verdict or score assigned. Source 1
Network revenue-sharing discussion
070 / 2026-10-02 attribution or deadline unresolved: The linked 2019 speech does not verify this record as dated and scoped. Historical wording/horizon retained with this source-repair warning; no new miss, replacement forecast, or inferred deadline. No new outcome verdict or score assigned. Source 1
071 / 2026-10-02 original interview supported; outcome open: Original interview supports a five-to-ten-year AGI window. Calendar years are approximate conversions from 2025, not exact deadlines. A public capability test is still required. No new outcome verdict or score assigned. Source 1
AGI timeline and scientific-discovery definition
072 / 2026-10-02 specific attribution/deadline unresolved: The reviewed TIME interview does not establish this exact probability, comparative multiplier, or dated disease-cure claim. Other reporting is not substituted for primary evidence. Retain historical wording with source-repair warning. No new outcome verdict or score assigned. Source 1
073 / 2026-10-02 specific attribution/deadline unresolved: The reviewed TIME interview does not establish this exact probability, comparative multiplier, or dated disease-cure claim. Other reporting is not substituted for primary evidence. Retain historical wording with source-repair warning. No new outcome verdict or score assigned. Source 1
074 / 2026-10-02 specific attribution/deadline unresolved: The reviewed TIME interview does not establish this exact probability, comparative multiplier, or dated disease-cure claim. Other reporting is not substituted for primary evidence. Retain historical wording with source-repair warning. No new outcome verdict or score assigned. Source 1
075 / 2026-10-02 specific attribution/deadline unresolved: The reviewed TIME interview does not establish this exact probability, comparative multiplier, or dated disease-cure claim. Other reporting is not substituted for primary evidence. Retain historical wording with source-repair warning. No new outcome verdict or score assigned. Source 1
076 / 2026-10-02 supported conditional horizon correction: The science-tool aspiration is supported; no independent 2030s deadline is specified for it. No new outcome verdict or score assigned. Source 1
Scientific-discovery AGI definition
078 / 2026-10-02 specific paraphrase unresolved: The cited March transcript provides a decade-or-longer integration estimate, not this several-years-to-a-decade formulation or 2027–34 calendar window. The October Hudson wording remains separately unverified. No new outcome verdict or score assigned. Source 1
02:04–02:06
080 / 2026-10-02 supported architecture/horizon clarification: The interview argues for missing components/world understanding rather than a dated architectural test. No 2024–34 resolution deadline is specified. No new outcome verdict or score assigned. Source 1
00:02:47–00:04:08; 02:00–02:05
081 / 2026-10-02 supported architecture/horizon clarification: The interview argues for missing components/world understanding rather than a dated architectural test. No 2024–34 resolution deadline is specified. No new outcome verdict or score assigned. Source 1
00:02:47–00:04:08; 02:00–02:05
082 / 2026-10-02 supported uncertainty correction: LeCun expects the next decade to be interesting for robotics emergence; he does not guarantee a fully formed industry. The relative decade is approximate, and significant autonomy remains qualified. No new outcome verdict or score assigned. Source 1
02:29:44–02:30:41
083 / 2026-10-02 supported wording clarification: Interview defines AGI through broad human cognitive competence and gives 50% by 2028; the minimal qualifier is not in the reviewed wording. A single unrealized 50% forecast is not automatically a forecasting error. No new outcome verdict or score assigned. Source 1
Full transcript: definition and Timelines
084 / 2026-10-02 supported historical-source repair: The original 2011 Q&A supplies 10%/50%/90% dates and explicitly conditions them on uninterrupted favorable development. The later podcast is not the original source for these two estimates. A non-occurrence cannot by itself make a 10% forecast false. No new outcome verdict or score assigned. Source 1
Interview Q1
085 / 2026-10-02 supported historical-source repair: The original 2011 Q&A supplies 10%/50%/90% dates and explicitly conditions them on uninterrupted favorable development. The later podcast is not the original source for these two estimates. A non-occurrence cannot by itself make a 10% forecast false. No new outcome verdict or score assigned. Source 1
Interview Q1
086 / 2026-10-02 primary retrospective supported; scope clarified: Hinton personally acknowledges the forecast was wrong and clarifies that he meant reading scans, recalling five years, possibly ten. This supports the retrospective, not a universal benchmark comparison. Existing scores remain historical. No new outcome verdict or score assigned. Source 1
2016 prediction retrospective
087 / 2026-10-02 wrong-source mapping unresolved: The reviewed Valence transcript does not supply the recorded 10–20%/30-year forecast. Original BBC interview remains unavailable; keep the historical record qualified, not source-verified. No new outcome verdict or score assigned. Source 1
088 / 2026-10-02 original interviews not text-verified: Original Fallon recording was located but primary transcript/audio was not inspected. The ledger claims and calendar horizons are retained as historical, not freshly verified. For the separately dated 2023 claim, the original Noah interview also remains unverified; comparative superiority is not established by locating a video. No new outcome verdict or score assigned. Source 1 · Source 2
089 / 2026-10-02 original interviews not text-verified: Original Fallon recording was located but primary transcript/audio was not inspected. The ledger claims and calendar horizons are retained as historical, not freshly verified. For the separately dated 2023 claim, the original Noah interview also remains unverified; comparative superiority is not established by locating a video. No new outcome verdict or score assigned. Source 1 · Source 2
090 / 2026-10-02 original interviews not text-verified: Original Fallon recording was located but primary transcript/audio was not inspected. The ledger claims and calendar horizons are retained as historical, not freshly verified. For the separately dated 2023 claim, the original Noah interview also remains unverified; comparative superiority is not established by locating a video. No new outcome verdict or score assigned. Source 1 · Source 2
091 / 2026-10-02 original interviews not text-verified: Original Fallon recording was located but primary transcript/audio was not inspected. The ledger claims and calendar horizons are retained as historical, not freshly verified. For the separately dated 2023 claim, the original Noah interview also remains unverified; comparative superiority is not established by locating a video. No new outcome verdict or score assigned. Source 1 · Source 2
092 / 2026-10-02 original interviews not text-verified: Original Fallon recording was located but primary transcript/audio was not inspected. The ledger claims and calendar horizons are retained as historical, not freshly verified. For the separately dated 2023 claim, the original Noah interview also remains unverified; comparative superiority is not established by locating a video. No new outcome verdict or score assigned. Source 1 · Source 2
093 / 2026-10-02 supported possibility and horizon correction: Event host report says as little as five years, not a guaranteed five-year deadline. The test universe is undefined. Restore possibility language and mark the derived calendar year approximate. No new outcome verdict or score assigned. Source 1
Opening report of 2024 summit
094 / 2026-10-02 supported original-interview source repair: A July 2025 original interview supports the jobs forecast; the 2024 Stanford report was the wrong citation. The decade is a contextual scenario, not a precise measured net-jobs deadline. No new outcome verdict or score assigned. Source 1
Original Axios interview
096 / 2026-10-02 supported timing/scope correction: The Q1 company transcript predicts coding agents doing a substantial share of AI R&D by middle-to-end 2026. It does not establish that all peer labs will follow. No present share or outcome threshold is supplied. No new outcome verdict or score assigned. Source 1
Printed p.14
097 / 2026-10-02 supported timing/scope correction: The Q1 company transcript predicts coding agents doing a substantial share of AI R&D by middle-to-end 2026. It does not establish that all peer labs will follow. No present share or outcome threshold is supplied. No new outcome verdict or score assigned. Source 1
Printed p.14
098 / 2026-10-02 aggregate forecast supported; outcome open: The original survey paper abstract supports the aggregate probabilities and 2028 milestones. These are aggregate forecasts, not unanimous individual beliefs. No validated task-specific resolution was established in this review. No new outcome verdict or score assigned. Source 1
Abstract
099 / 2026-10-02 aggregate forecast supported; outcome open: The original survey paper abstract supports the aggregate probabilities and 2028 milestones. These are aggregate forecasts, not unanimous individual beliefs. No validated task-specific resolution was established in this review. No new outcome verdict or score assigned. Source 1
Abstract
100 / 2026-10-02 aggregate forecast supported; outcome open: The original survey paper abstract supports the aggregate probabilities and 2028 milestones. These are aggregate forecasts, not unanimous individual beliefs. No validated task-specific resolution was established in this review. No new outcome verdict or score assigned. Source 1
Abstract
October 2 source repairs — 13 repaired, 9 unresolved

This manual follow-up supersedes the earlier source-access notes for these 22 records. It does not validate outcomes or historical scores. The unchanged nine records remain attribution-repair items; they are not newly source-verified.

ID Finding / primary-source locator Sources inspected or attempted
001 unresolved; historical fields retained: Original September attribution unresolved. Coxon’s original X post states a qualitative concern, not the recorded 10% probability. A September 11 original TMZ interview report concerns a later, conditional estimate; it cannot be silently backdated to September 8. Source 1 · Source 2 · Source 3
002 supported source repair: The original public post confirms a personal greater-than-10% estimate over the next decade, not a company probability or a claim about present-model danger. The public follow-up distinguishes future superintelligence from present models. September 2036 is approximate, not an exact-day deadline. Original post; displayed September 8, 2026 local date; public follow-up 2097528891846074828 Source 1
013 supported source repair: The event recording separates the research-program estimate (years, if not a decade) from an explicit human-level-AI answer (years to decades with large uncertainty). It does not establish the recorded 2027–2034 window or a firm ceiling. Recording published October 13, 2024; upload date is not asserted as the speaking date. 31:55–32:10; 34:27–34:38 Source 1
014 supported source repair: The original NBIM host recording confirms probably around the end of next year, spoken April 8, 2024. A later answer adds within two years and makes the AGI definition explicit. This repairs the source and timing qualifier, not the undefined intelligence outcome. 01:44–01:54; 06:24–06:35; host description dates recording April 8, 2024 Source 1
017 unresolved; historical fields retained: The exact December 2024 BBC interview passage supporting 10–20% over 30 years remains unavailable. Syndicated coverage and a public BBC clip lead do not establish the exact probability passage. No substitution with a later interview. Source 1 · Source 2
020 supported source repair: In the original Fallon interview, Gates asks whether people should work two or three days a week. It is a question about adapting to AI, not a dated two-day-workweek forecast. The preceding decade forecast concerns intelligence, medical advice and tutoring; it must not become a workweek deadline. The original upload is February 2025, not the historical March coverage date. 07:08–07:49 Source 1
061 unresolved; historical fields retained: The original 2016 Tesla announcement still redirects; a 2019 retrospective does not replace contemporaneous 2016 attribution or prove hardware sufficiency. Source 1 · Source 2
063 unresolved; historical fields retained: The recorded 2016 safer-than-human forecast and short regulatory-delay wording remain an unresolved composite attribution; the cited 2019 event is not the original dated statement. Source 1
064 unresolved; historical fields retained: The exact 2019 Level-5/2021 attribution is not supported by the cited speech. Separate 2020 or later forecasts cannot be silently mapped onto this historical record. Source 1
068 unresolved; historical fields retained: The original 2024 optional-work statement and claimed decade deadline remain unverified together. A purported 2024 VivaTech transcript contains apparent event/date inconsistencies and was rejected. Later 2025 statements are different forecasts. Source 1 · Source 2
070 unresolved; historical fields retained: The 2021 unsupervised-fleet wording and iteration scope remain unsupported by the cited 2019 event. Generic later Tesla projections do not establish this record’s original attribution. Source 1
072 supported source repair: The original July 2025 interview estimates roughly 50% within five years, by about 2030, not a five-to-ten-year 2030–2035 probability window. The definition requires consistent broad cognitive competence, including invention and creativity. 00:52:33–00:53:28 Source 1
073 supported source repair: The original interview supports the probably-tenfold-impact comparison. It supplies no measured impact metric or independent 2030s deadline. The adjacent ten-year illustration is comparative duration, not a calendar deadline. 01:45:37–01:46:31 Source 1
074 supported source repair: The original interview supports the ten-times-faster comparison, illustrating ten years rather than a hundred. This is not an independently dated 2030s forecast or an observed measurement. 01:45:37–01:46:31 Source 1
075 supported source repair: The original Google DeepMind recording explicitly conditions curing most diseases within a decade or two on AI drug design working. The prior TIME source did not support this attribution. The recording was published August 14, 2024; derived calendar years remain approximate. 42:24–42:32 Source 1
078 supported source repair: The original Hudson Forum human-level-AI answer says years to decades with substantial uncertainty. The cited March Lex interview is a different statement. Remove the unsupported 2027–2034 window; this overlaps record 013 rather than becoming a new independent forecast. 34:27–34:38; recording published October 13, 2024 Source 1
087 unresolved; historical fields retained: The Valence source does not contain the recorded 10–20%/30-year forecast. The original BBC December 2024 probability passage remains unavailable, as for record 017. Source 1 · Source 2
088 supported source repair: In the original Fallon interview, Gates asks whether people should work two or three days a week. It is a question about adapting to AI, not a dated two-day-workweek forecast. The preceding decade forecast concerns intelligence, medical advice and tutoring; it must not become a workweek deadline. The original upload is February 2025, not the historical March coverage date. 07:08–07:49 Source 1
089 unresolved; historical fields retained: A third-party reproduction locates conditional three-day-workweek discussion in the separate November 2023 Trevor Noah episode. The original audio or publisher transcript has not been inspected; it does not justify publishing a repaired claim or the old 2035+ deadline. Source 1 · Source 2
090 supported source repair: The original Fallon interview supplies the next-decade horizon for scarce intelligence becoming free and commonplace. About 2035 is an approximate conversion from the February 2025 upload, not an exact deadline. 07:08–07:23 Source 1
091 supported source repair: The original interview predicts access to great tutoring as intelligence becomes free and commonplace. It does not claim tutors will outperform most human teachers, specify a benchmark, or demonstrate a present outcome. 07:08–07:30 Source 1
092 supported source repair: The original interview predicts great medical advice becoming free and commonplace, not a clinical doctor-replacement threshold. No present medical efficacy or safety outcome is asserted. 07:08–07:30 Source 1
v1.6 exact corrections — prior v1.5 values preserved
ID Before After
002 More than a 10% chance that AI kills all humans within the next decade. | Horizon: Deadline: September 2036 | Source: https://www.washingtonpost.com/technology/2026/09/10/years-they-warned-ai-could-kill-all-humans-now-people-are-listening/ | Status: pending | Score: Pending Hubinger personally estimated a greater-than-10% chance that AI kills all humans within the next decade. | Horizon: Approximately September 2036; relative ten-year horizon | Source: https://x.com/EvanHub/status/2097497037956891126 | Status: pending | Score: Pending
013 Human-level AI would take several years, if not a decade, and would not arrive in the next year or two. | Horizon: Window: roughly 2027–2034 | Source: https://techcrunch.com/2024/10/16/metas-ai-chief-says-world-models-are-key-to-human-level-ai-but-it-might-be-10-years-out/ | Status: pending | Score: Pending Developing the proposed AI capabilities could take years, if not a decade; reaching human-level AI could take years to decades, with substantial uncertainty. | Horizon: Years to decades; no firm calendar deadline | Source: https://www.youtube.com/watch?v=4DsCtgtQlZU | Status: pending | Score: Pending
014 AI would probably become smarter than any single human by the end of 2025. | Horizon: Deadline passed | Source: https://www.axios.com/2024/04/11/ai-human-intelligence-smart-elon-musk | Status: unresolvable | Score: No score Musk guessed that AI would probably be smarter than any one human around the end of 2025. | Horizon: Around end-2025; later answer says within two years from April 2024 | Source: https://www.youtube.com/watch?v=_rQBZ3vKRA0 | Status: unresolvable | Score: No score
020 AI could make a two-day workweek possible within a decade as machines handle most routine work. | Horizon: Deadline: 2035 | Source: https://fortune.com/2025/03/27/billionaire-bill-gates-two-day-workweek-ai-replacing-humans/ | Status: pending | Score: Pending Gates asked whether people should work two or three days a week as society adapts to AI. | Horizon: Open question; no explicit workweek deadline | Source: https://www.youtube.com/watch?v=uHY5i9-0tJM | Status: pending | Score: Pending
072 There is roughly a 50% chance of AGI within that five-to-ten-year window. | Horizon: 2030–35 | Source: https://time.com/7277608/demis-hassabis-interview-time100-2025/ | Status: review | Score: Review Hassabis estimated roughly a 50% chance of AGI within five years, by about 2030. | Horizon: About 2030; approximate five-year horizon from 2025 | Source: https://lexfridman.com/demis-hassabis-2-transcript | Status: review | Score: Review
073 AI-driven change could be ten times larger than the Industrial Revolution. | Horizon: 2030s | Source: https://time.com/7277608/demis-hassabis-interview-time100-2025/ | Status: review | Score: Review Hassabis expected AI-driven change to have probably about ten times the impact of the Industrial Revolution. | Horizon: Comparative scenario; no explicit calendar deadline | Source: https://lexfridman.com/demis-hassabis-2-transcript | Status: review | Score: Review
074 AI-driven change could arrive ten times faster than the Industrial Revolution. | Horizon: 2030s | Source: https://time.com/7277608/demis-hassabis-interview-time100-2025/ | Status: review | Score: Review Hassabis expected AI-driven change to unfold about ten times faster than the Industrial Revolution. | Horizon: Comparative duration (10 vs 100 years); no explicit calendar deadline | Source: https://lexfridman.com/demis-hassabis-2-transcript | Status: review | Score: Review
075 AI could help cure most diseases within a decade or two. | Horizon: 2034–44 | Source: https://time.com/7277608/demis-hassabis-interview-time100-2025/ | Status: review | Score: Review Most diseases could be cured within the next decade or two if AI drug design works. | Horizon: Approximately 2034–2044; conditional on AI drug design working | Source: https://www.youtube.com/watch?v=pZybROKrj2Q | Status: review | Score: Review
078 Human-level AI will take several years, if not a decade. | Horizon: 2027–34 | Source: https://lexfridman.com/?p=5821 | Status: review | Score: Review Reaching human-level AI could take years to decades, with substantial uncertainty. | Horizon: Years to decades; no firm calendar deadline | Source: https://www.youtube.com/watch?v=4DsCtgtQlZU | Status: review | Score: Review
088 AI could make a two-day workweek possible within a decade. | Horizon: 2035 | Source: https://fortune.com/2025/03/27/billionaire-bill-gates-two-day-workweek-ai-replacing-humans/ | Status: review | Score: Review Gates asked whether people should work two or three days a week as society adapts to AI. | Horizon: Open question; no explicit workweek deadline | Source: https://www.youtube.com/watch?v=uHY5i9-0tJM | Status: review | Score: Review
090 Intelligence will become free and common through AI. | Horizon: 2035 | Source: https://fortune.com/2025/03/27/billionaire-bill-gates-two-day-workweek-ai-replacing-humans/ | Status: review | Score: Review Gates expected intelligence to become free and commonplace through AI over the next decade. | Horizon: Approximately 2035; relative next-decade horizon | Source: https://www.youtube.com/watch?v=uHY5i9-0tJM | Status: review | Score: Review
091 AI tutors will outperform most human teachers and become widely available. | Horizon: 2035 | Source: https://fortune.com/2025/03/27/billionaire-bill-gates-two-day-workweek-ai-replacing-humans/ | Status: review | Score: Review Gates expected great tutoring to become free and commonplace through AI over the next decade. | Horizon: Approximately 2035; relative next-decade horizon | Source: https://www.youtube.com/watch?v=uHY5i9-0tJM | Status: review | Score: Review
092 AI doctors will provide excellent medical consultation at low cost. | Horizon: 2035 | Source: https://fortune.com/2025/03/27/billionaire-bill-gates-two-day-workweek-ai-replacing-humans/ | Status: review | Score: Review Gates expected great medical advice to become free and commonplace through AI over the next decade. | Horizon: Approximately 2035; relative next-decade horizon | Source: https://www.youtube.com/watch?v=uHY5i9-0tJM | Status: review | Score: Review
October 2 v1.7 source search: 3 repaired, 6 unresolved

This manual follow-up supersedes the v1.6 access notes for the nine remaining gaps. The repairs verify forecast attribution and qualifiers only. All historical statuses and scores remain unchanged and are not newly validated. Tesla’s 2016 press-call source is an edited recording mirror with visuals added; the original spoken statement is distinguished from third-party narration and captions. BFM Tech broadcast the original 2024 VivaTech event.

ID Finding and locator Sources inspected or attempted
001 unresolved; historical fields retained: AP’s September 14 report attributes 10% over a decade to social posts, but its linked September 9 report only reproduces qualitative warnings. The original numeric September 8 post remains unlocated. The later September 11 TMZ estimate cannot be silently substituted or backdated. Historical record retained and explicitly unresolved. Source 1 · Source 2 · Source 3 · Source 4 · Source 5
017 unresolved; historical fields retained: The broadcaster’s December 27, 2024 public post was retrieved. Its text describes extinction concern within two decades, without the recorded 10–20% probability and 30-year horizon. That excerpt cannot verify the missing numerical passage. The full original Today interview or numerical transcript is still required. Records 017 and 087 overlap; no replacement with later interviews. Source 1 · Source 2 · Source 3
061 supported source repair: The October 19, 2016 press-call recording supports the hardware assertion and explicitly separates it from unfinished software validation and regulatory approval. The recording is a third-party mirror with pauses/names removed and visuals added; its original spoken statement is primary evidence, not an archive author’s paraphrase. Tesla’s 2016 Form 10-K independently repeats the October hardware assertion. Remove the unsupported 2016–20 release window. Neither source proves hardware sufficiency or successful autonomy. Press call 00:05–01:30; Tesla 2016 Form 10-K, printed page 5 (PDF page 8), Autopilot Systems Source 1 · Source 2
063 supported source repair: The original 2016 press call predicts at least twice-human safety after software validation and required approval. In the regulatory answer, Musk says approval could vary radically between regions and was outside Tesla’s control. The old short-regulatory-delay wording and 2018–19 deadline are unsupported and removed. The edited recording mirror documents the forecast; it does not establish actual comparative safety. Press call 00:33–01:01 and 12:15–13:54 Source 1
064 unresolved; historical fields retained: Searches located different 2020/2021 Level-5 statements and 2019 feature-complete forecasts, but did not establish this exact 2019 statement with a 2021 deadline. Historical fields remain unchanged; no later statement is substituted. Source 1
068 supported source repair: BFM Tech’s original 2024 VivaTech broadcast contains the optional-work answer in English. Musk conditions it on a benign long-term scenario. The work answer supplies no ten-year deadline; the former 2034 horizon is removed. This is the 2024 event, not the mislabeled 2023 archive transcript or a later 2025 forecast. No outcome verdict is assigned. VivaTech May 23, 2024; broadcast 39:37–42:26, especially 41:46–42:10 Source 1
070 unresolved; historical fields retained: Tesla’s original Q3 2021 shareholder update describes a vision of autonomy and expansion of supervised FSD beta based on driver safety and attentiveness. It does not support the recorded large unsupervised-fleet forecast or its software-iteration wording. The exact 2021 original statement remains missing. Source 1 · Source 2
087 unresolved; historical fields retained: The broadcaster’s December 27, 2024 public post was retrieved. Its text describes extinction concern within two decades, without the recorded 10–20% probability and 30-year horizon. That excerpt cannot verify the missing numerical passage. The full original Today interview or numerical transcript is still required. Records 017 and 087 overlap; no replacement with later interviews. Source 1 · Source 2
089 unresolved; historical fields retained: The publisher’s current RSS feed and original episode listing identify the Bill Gates episode as November 21, 2023 at 05:02 UTC, not a 2025 Fortune interview. Metadata alone does not verify the three-day passage or a 2035+ deadline. The original spoken passage has not been inspected; a derivative transcript remains only a lead. Source 1 · Source 2 · Source 3 · Source 4
v1.7 exact corrections: prior v1.6 values preserved
ID Before After
061 Every new Tesla would have the hardware needed for full self-driving. | Horizon: 2016–20 | Source: https://www.elonmuskarchive.org/video/tesla-autonomy-day-2019 | Status: review | Score: Review Musk said all Tesla vehicles leaving the factory had the hardware necessary for Level 5 autonomy; software validation and regulatory approval were still pending. | Horizon: Hardware assertion made October 2016; no software-release deadline in this answer | Source: https://www.youtube.com/watch?v=-vjGEEF_p5E | Status: review | Score: Review
063 Full autonomy would be safer than a human driver after a short regulatory delay. | Horizon: 2018–19 | Source: https://www.elonmuskarchive.org/video/tesla-autonomy-day-2019 | Status: review | Score: Review Musk expected the new hardware to enable autonomy at least twice as safe as a person, subject to software validation and regulatory approval. | Horizon: Conditional on validation and approval; no calendar deadline in the cited answer | Source: https://www.youtube.com/watch?v=-vjGEEF_p5E | Status: review | Score: Review
068 AI and robotics will make work optional for many people within a decade. | Horizon: 2034 | Source: https://www.elonmuskarchive.org/video/tesla-autonomy-day-2019 | Status: review | Score: Review Musk expected AI and robots to make any job optional in a benign long-term scenario, with goods and services supplied by machines. | Horizon: Long term, conditional benign scenario; no deadline in the optional-work answer | Source: https://www.youtube.com/watch?v=z2XRnJiyZQI | Status: review | Score: Review
October 2 v1.8 original interviews: 3 repaired, 3 unresolved

Original recordings support the source repairs for 017, 087 and 089. The BBC clip’s own captions were checked against direct-audio local transcription. Gates’s publisher-feed audio was transcribed locally in context and checked in a separate cropped pass; machine text is not a publisher transcript. No paid API was used. Prior source-access notes are historical and superseded by this review. All historical statuses and scores remain unchanged. Records 017 and 087 overlap.

ID Finding and locator Primary sources
017 The BBC’s own December 27, 2024 video contains the numerical exchange at 00:00–00:20. Javid supplies the extinction-within-three-decades premise; Hinton answers with a 10–20% estimate. The broadcaster’s on-video captions and direct-audio local transcription agree on the key passage. The post’s two-decade description does not replace the spoken thirty-year question. Replace derivative/wrong-source links with the original BBC clip, make the relative horizon explicit, and retain the overlap warning for 017 and 087. These are two ledger records of the same forecast, not independent predictions. This source verification is not an extinction outcome or a new calibration verdict. BBC Radio 4 Today video published December 27, 2024; 00:00–00:15 question, 00:16–00:20 answer Primary source 1
087 The BBC’s own December 27, 2024 video contains the numerical exchange at 00:00–00:20. Javid supplies the extinction-within-three-decades premise; Hinton answers with a 10–20% estimate. The broadcaster’s on-video captions and direct-audio local transcription agree on the key passage. The post’s two-decade description does not replace the spoken thirty-year question. Replace derivative/wrong-source links with the original BBC clip, make the relative horizon explicit, and retain the overlap warning for 017 and 087. These are two ledger records of the same forecast, not independent predictions. This source verification is not an extinction outcome or a new calibration verdict. BBC Radio 4 Today video published December 27, 2024; 00:00–00:15 question, 00:16–00:20 answer Primary source 1
089 The original What Now? episode was published November 21, 2023. Its publisher-feed audio was retrieved and the AI/workweek context inspected through local transcription, with a second cropped-pass check. At approximately 37:32–38:56 in the retrieved audio, Gates describes a three-day workweek as potentially acceptable if machines provide necessities, and stresses gradual displacement and help learning new skills. This is a conditional, partly normative scenario, not a dated promise that three days will become normal. The workweek answer supplies no calendar deadline; remove the unsupported 2035+ horizon and replace the 2025 coverage link. Dynamic advertising can shift timestamps. The machine transcript is a locator, not a publisher-certified transcript. No new outcome verdict or score is assigned. Publisher RSS: November 21, 2023, 05:02 UTC, episode 3; retrieved audio 37:32–38:56, key scenario 37:38–37:51; timestamps may shift with ads Primary source 1 · Primary source 2

Remaining source gaps: 001 (original Coxon numerical post), 064 (exact 2019 Level-5 deadline), 070 (original 2021 unsupervised-fleet statement). These records were not re-reviewed or changed in this scoped interview check.

v1.8 exact corrections: prior v1.7 values preserved
ID Before After
017 A 10–20% chance that AI causes human extinction within 30 years. | Horizon: Deadline: 2054 | Source: https://www.forbes.com/sites/danfitzpatrick/2024/12/29/geoffrey-hintons-prediction-of-human-extinction-at-the-hands-of-ai/ | Status: pending | Score: Pending In response to a question about AI causing human extinction within three decades, Hinton estimated a 10–20% chance. | Horizon: Within three decades of December 2024 (approximately 2054) | Source: https://x.com/BBCr4today/status/1872561808545837433 | Status: pending | Score: Pending
087 AI has a 10–20% chance of causing human extinction within 30 years. | Horizon: 2054 | Source: https://www.valence.co/ai-and-the-workforce/ai-unpacked-with-geoffrey-hinton | Status: review | Score: Review In response to a question about AI causing human extinction within three decades, Hinton estimated a 10–20% chance. | Horizon: Within three decades of December 2024 (approximately 2054) | Source: https://x.com/BBCr4today/status/1872561808545837433 | Status: review | Score: Review
089 A three-day workweek could eventually become normal because of AI. | Horizon: 2035+ | Source: https://fortune.com/2025/03/27/billionaire-bill-gates-two-day-workweek-ai-replacing-humans/ | Status: review | Score: Review Gates said a society needing only three days of work a week would probably be acceptable if machines supplied necessities. | Horizon: Conditional scenario; no workweek deadline in the November 2023 answer | Source: https://podcasts.apple.com/us/podcast/bill-gates-doesnt-need-to-track-you/id1710609544?i=1000635506667 | Status: review | Score: Review
October 2 v1.9: three original-source corrections; two historical attributions unresolved

Current wording is restored to the inspected originals. This does not validate the superseded numerical Coxon attribution or the exact Level-5/2021 paraphrase. Those remain historical evidence tasks. All historical statuses and scores are unchanged. No new outcome or calibration verdict is assigned.

ID Evidence and limits Original sources
001 Coxon’s original public post reports AI builders’ belief that AI could kill all humans by the end of the decade. It supplies no numerical probability. Hubinger’s separately authored quote-post gives his own greater-than-10% estimate over the next decade; record 002 already tracks it. Restore Coxon’s qualitative warning and its stated horizon rather than transferring Hubinger’s number or backdating the later TMZ interview. The former Coxon 10%/September-2036 assertion remains in history and is not verified by this repair. No motive or outcome finding is made. Coxon: September 9, 2026 00:04:30 UTC (September 8 in Vancouver); Hubinger: September 9 01:27:18 UTC. Original post bodies, authors and DOM timestamps inspected. Original source 1 · Original source 2
064 Tesla’s own April 22, 2019 Autonomy Day recording separates feature completeness, reliability without occupant attention, and regulatory approval. At 2:45:39–2:46:25, Musk expects feature-complete self-driving that year, sufficient reliability probably around Q2 of the next year, and some jurisdictional approvals toward the end of the next year. Restore those 2019/2020 milestones and their qualifiers. The Level-5 phrasing appears in an analyst question at 3:31:45–3:32:19; Musk’s following answer discusses regulatory evidence, not a 2021 deadline. Do not turn the question into Musk’s promise. The former exact Level-5-by-2021 attribution remains unverified and preserved in history. YouTube captions are automatically generated and can contain errors; this is source repair, not an outcome verdict. Original Tesla upload April 22, 2019; auto-caption passages 2:45:39–2:46:25 and 3:31:45–3:33:01. Original source 1
070 The interviewer’s original episode page is dated November 12, 2019 and links its publisher-hosted Rev.com transcript. Page 11, 26:08–26:50, contains Musk’s million-Teslas-without-a-person statement, followed by observations about Autopilot iterations. Restore the November 2019 attribution and the vague short-term wording. The adjacent iteration discussion does not establish that software iteration is a condition or a deployment deadline. Remove the unsupported 2021 date and 2020s calendar horizon. This is a different statement from the April 2019 robotaxi forecast and is not independent evidence of an achieved outcome. Publisher episode page November 12, 2019; publisher-linked transcript page 11, 26:08–26:50. Original source 1 · Original source 2
v1.9 exact corrections: prior v1.8 claims and dates preserved
ID Before After
001 A 10% chance that AI causes human extinction within the next decade. | Horizon: Deadline: September 2036 | Source: https://apnews.com/article/98316b0d64de17191f33c0fbf1d37858 | Status: pending | Score: Pending Coxon warned that AI builders believe AI could kill all humans by the end of the decade; this post gives no numerical probability. | Horizon: End of the 2020s; qualitative warning attributed to AI builders | Source: https://x.com/hilbertspaess/status/2097476203863224394 | Status: pending | Score: Pending
064 Tesla would reach Level 5 autonomy in the early 2020s. | Horizon: 2021 | Source: https://www.elonmuskarchive.org/video/tesla-autonomy-day-2019 | Status: review | Score: Review Musk expected feature-complete self-driving in 2019, reliability without occupant attention probably around Q2 2020, and some regulatory approvals toward end-2020. | Horizon: 2019; probably Q2 2020; some approvals toward end-2020 | Source: https://www.youtube.com/watch?v=Ucp0TTmvqOE | Status: review | Score: Review
070 Tesla would deploy a large unsupervised vehicle fleet after software iteration. | Horizon: 2020s | Source: https://www.elonmuskarchive.org/video/tesla-autonomy-day-2019 | Status: review | Score: Review Musk said it would not be long before one million Teslas could drive without a person inside. | Horizon: No calendar deadline; vague short-term forecast in November 2019 | Source: https://lexfridman.com/wordpress/wp-content/uploads/2019/11/elon_musk_lex_fridman_2_transcript.pdf | Status: review | Score: Review
070 display date 2021 November 12, 2019; publisher episode date

Prior Coxon presentation and context (historical, superseded)

 
           Jacob Coxon  Former pretraining researcher, Anthropic and OpenAI · September 8, 2026   Pending  
         A 10% chance that AI causes human extinction within the next decade. 
          Pending  Risk  Deadline: September 2036  Probability supplied  
         This is a probabilistic forecast, not a claim that extinction will occur. It cannot be marked wrong merely because the outcome does not happen; calibration requires a reference class of comparable forecasts. 
          Source and incentive context  Coxon made the estimate while publicly resigning and said he left before his Anthropic equity vested. That reduces one obvious financial incentive to promote Anthropic, but does not validate the forecast. Sources:  Associated Press ;  Axios interview .  
        Historical v1.5 review:  The original AP link could not be accessed. A later original TMZ interview report corroborates the broad estimate but does not verify the original September 8 attribution. Historical record retained; no source replacement or outcome finding. Historical status and score retained; this is not a new calibration verdict.   October 2 v1.6 source repair (supersedes the v1.5 source-access note):  Original September attribution unresolved. Coxon’s original X post states a qualitative concern, not the recorded 10% probability. A September 11 original TMZ interview report concerns a later, conditional estimate; it cannot be silently backdated to September 8. Historical status and score retained.   October 2 v1.7 follow-up (supersedes the v1.6 access note):  AP’s September 14 report attributes 10% over a decade to social posts, but its linked September 9 report only reproduces qualitative warnings. The original numeric September 8 post remains unlocated. The later September 11 TMZ estimate cannot be silently substituted or backdated. Historical record retained and explicitly unresolved. Historical status and score retained.     The current alarm is now on the record.  Jacob Coxon assigned a 10% probability to AI-caused human extinction within a decade after leaving Anthropic. Dario Amodei then called for slower frontier capability gains, and Sam Altman publicly agreed. Those are consequential statements. They are not evidence, by themselves, of a coordinated “psy-op” or regulatory capture. The ledger records commercial and policy incentives, but it does not infer hidden motives without documentation. 
October 2 v1.10: archived attribution findings; both historical gaps remain open

This manual review adds preserved-source evidence. It changes no prediction, deadline, status or score. The superseded assertions remain in the earlier correction history and are still unverified.

001 · Coxon: preserved warning, no probability in this post

The archived original X post, captured September 9, 2026 at 04:15:21 UTC, preserves Coxon’s author name, handle, complete warning and displayed September 9 timestamp. It reports AI builders’ belief that AI could kill all humans by the end of the decade. It supplies no numerical probability. This corroborates the supported v1.9 wording; it does not establish Coxon’s former personal 10%/ten-year attribution or prove that he never supplied a probability elsewhere.

064 · Musk: the recovered Level-5/2021 exchange is dated 2021

Tesla’s original webcast page links its January 27, 2021 replay, 31:57–32:24. The question asks why Tesla would achieve Level 5 autonomy in 2021. Musk responds that his confidence rests on his understanding of the technical roadmap and progress between beta iterations. The Level-5/2021 wording is in the question; Musk gives the confidence response. This is a separate 2021 exchange, not evidence of the ledger’s superseded 2019 attribution. It does not establish where that old paraphrase originated. Locators use the original upload’s automatically generated captions, which can contain errors.

Still needed: Coxon’s own original September 8/9 numerical statement specifying AI-caused human extinction and a ten-year horizon; Musk’s own original 2019 statement explicitly specifying Level 5 autonomy by 2021. Later statements cannot be backdated. Failure to recover either statement is not a finding that it never existed. Internet Archive’s CDX lookup returned a temporary-offline notice during this review; no Wayback capture was verified.

October 2 v1.11: historical-score eligibility safeguards

Historical-score display safeguards: explicit reviewed-record eligibility, designated duplicate-group representatives, strict full-string integer scores in −100…+100, eligible status checks and fail-closed exclusion of new/changed records. Historical gaps 001/064 and unverified 077 explicitly excluded. Chart relabeled Historical editorial scores; all 100 records, claims, sources, statuses and scores plus prior history preserved. No new outcome validation or API-contract change.

The previous chart counted any numeric substring in a score, without eligibility or duplicate checks. The new display policy preserves the five historical contributors but rejects unresolved, duplicate, malformed, out-of-range, unapproved or changed records. The old calculation and exact pre-update page are retained in the publication backup. No forecast or outcome is newly resolved.

October 2 v1.12: score limitations and layout update

Published the five historical-score outcome audits beside chart values and in their detailed records, with source links and unresolved resolution requirements. Added consistent row alignment, responsive annotation spacing and room between page sections. All 100 canonical records, historical statuses/scores, eligibility policy and prior revisions preserved. No new outcome verdict or API-contract change.

Two narrower findings have stronger qualitative support: the missed Tesla 2020 operating-robotaxi milestone and Hinton’s admitted five-year timing miss. The other three broader outcomes remain incompletely resolved by their linked evidence. No exact numerical score is reproducible from the published rubric. These audit findings annotate the historical judgments without replacing them.

October 2 v1.13: prospective scoring policy published

Published prospective scoring methodology 1.0 for future assessments: frozen resolution contracts, evidence-supported outcome states, type-specific calculations, reproducible receipts, duplicate safeguards and separate prospective aggregates. All 100 records, historical claims, statuses, scores, eligibility, chart calculations and prior history preserved. Policy publication only; no new scoring engine, outcome assessment or API-contract change.

Methodology 1.0 applies to future assessment receipts. Retrospective contracts must be labeled and reported separately. The five historical numeric scores remain editorial judgments under their existing safeguards; none has been reassessed or enrolled in a new aggregate.

October 2 v1.14: assessment receipt downloads published

Published versioned assessment receipt downloads beside prospective methodology 1.0: blank JSON template, TXT usage guide and explicitly fictional JSON worked example excluded from real aggregates. All 100 records, historical claims, statuses, scores, eligibility, chart calculations and prior history preserved. Supporting files only; no scoring-engine activation or API-contract change.

The fictional example is a format demonstration, not an assessment receipt for a real prediction. These files are separate from the canonical ledger export contract. New receipt-template releases must use a new versioned directory rather than silently replacing these published files.

October 2 v1.15: read-only receipt validator published

Published read-only assessment receipt validator 1.0 and its usage guide beside the receipt templates, with explicit verification limits. Local format, declared-rule and arithmetic checks only; no evidence authentication, server-side validation, scoring-engine activation or historical reassessment. All 100 records, claims, statuses, scores, eligibility, receipt-template files and prior history preserved; API contract unchanged.

The validator download uses its own immutable versioned directory. A passing result is a mechanical check, not factual verification or publication approval. The fictional example remains excluded from real assessments.

October 2 v1.16: fictional validator report and annotations

Added a reproducible, explicitly fictional validator report with two calculation errors and three incomplete review fields, annotated explanations and separate input/JSON-output/TXT-notes downloads. Existing validator 1.0, receipt downloads, all 100 records, historical scores, eligibility, policy and prior revisions preserved. No real assessment, scoring-engine activation or API-contract change.

October 2 v1.17: validator troubleshooting

Added a short validator troubleshooting section covering common input, calculation, evidence-reference, unresolved-outcome, review-completeness and duplicate-family failures. Documentation only: all 100 records, historical scores, eligibility, validator 1.0, eight published downloads, policy and prior revisions preserved; no API-contract change or reassessment.

October 5 v1.18: receipt documentation clarifications

Clarified receipt documentation: completeness checks cover only a subset of policy requirements; unresolved receipts still need required attribution, contract and review fields; condition findings use not_met while the overall outcome uses condition_not_met. Published documentation revision 1.1 guides at new URLs and reconciled the stale local publication statement. All 100 records, historical claims, statuses, scores, eligibility, validator 1.0, original eight downloads, methodology and prior revisions preserved; no reassessment or API-contract change.

October 5 v1.19: printable reviewer checklist

Published the printable one-page reviewer checklist PDF beside the receipt guides: 12 checkboxes, separate validator completeness and human policy review, reviewer fields and follow-up space. Reviewer aid only; not an assessment or publication approval. All 100 records, historical claims, statuses, scores, eligibility, validator 1.0, methodology, ten existing downloads and prior revisions preserved; no reassessment or API-contract change.

The monthly evidence review will append future versions when a source, status, score, deadline or record count changes. Unchanged reviews are intentionally not represented as fake revisions.

Historical editorial scoring

This retained rubric describes the historical editorial scores. Future assessments follow the prospective scoring policy; no historical score or eligibility rule is changed.

An accuracy score runs from −100 to +100 only after a claim can be evaluated. The score combines outcome, timing, magnitude, scope and mechanism. It is an editorial judgment with an evidence trail, not a scientific probability.

OutcomeDid the specified event happen?
TimingDid it happen inside the stated window?
MagnitudeWas the size of the effect close?
ScopeDid it apply to the promised population or only a narrow example?

Leaderboards are withheld until a forecaster has at least five independently resolvable claims. Ranking people on one cherry-picked hit or miss would manufacture certainty.

What counts as evidence of influence

People selling AI have an incentive to emphasize capability and adoption. Safety-focused labs can benefit from rules that raise the cost of entry. Investors benefit from growth narratives. Critics gain attention when forecasts fail. These incentives justify scrutiny, not automatic dismissal.

A regulatory-capture claim needs documented lobbying, proposed rules, competitive effects and a plausible causal link. A “psy-op” claim needs evidence of coordinated deception. Similar public statements, even when they appear suddenly, do not prove either one. The ledger will preserve policy positions and financial interests so readers can test those hypotheses against records rather than vibes.

Corrections and submissions

Submit a correction with the record ID, original source, exact date, full surrounding context, stated deadline and a proposed resolution rule. Corrections should identify the specific field at issue and provide stronger evidence. Archived copies are preferred for posts that can be edited or deleted.

Editorial rule: a forecast can be revised, but its earlier version stays in the history. Quietly moving a deadline is itself useful data.

Core sources

  1. Associated Press. “New warnings about the risks of AI to humanity revive a long-running debate.” September 14, 2026.
  2. Dario Amodei. “We Must Pace the Frontier.” September 2026.
  3. Dario Amodei. “Machines of Loving Grace.” October 2024.
  4. Anthropic. Recommendations to OSTP for the US AI Action Plan. March 6, 2025.
  5. Sam Altman. “The Gentle Singularity.” June 10, 2025.
  6. OpenAI. “How agents are transforming work.” June 25, 2026.
  7. Google DeepMind. “From AGI to ASI.” June 12, 2026.
  8. Rodney Brooks. “Predictions Scorecard, 2025 January 01.”
  9. Grace et al. “Thousands of AI Authors on the Future of AI.” 2024.

Disclosure: The featured image is an AI-generated editorial illustration, not documentary evidence. The 100 records are tracked historical assertions, not 100 independently verified or unique forecasts. Conditional definitions, duplicate statements and source-repair items remain visible. Source support and outcome resolution are separate; see each dated review note. Forecast evaluation is an editorial judgment based on documented sources and may be revised as evidence changes. This ledger is a growing dataset, not a claim that every public AI forecast has already been captured.