{ "entity": "yale-budget-lab-ai-tracker", "name": "Tracking the Impact of AI on the Labor Market", "axn": { "axn": "AXN:0B05.NON.💛👈🤲🔩🌖🧪", "root": "AXN:0B05.NON", "hex": "0B05", "family": "NON", "row_sha256": "cdb8b1310539997de08fc30d5b4c130bfae02922f48670247b1d64dbaa5e33cb", "minted": "2026-10-29", "resolver": "https://www.alexanarch.org/s/axn/0B05/", "earlier_versions": [] }, "type": "C (public entity on which the archive bears: a labor-market tracker; an entity of the Labor Vector meta-aggregator)", "type_code": "C", "type_label": "type C — a conventional reading holds it (public entity on which the archive bears: a labor-market tracker; an entity of the Labor Vector meta-aggregator)", "case": "equal", "composition": { "composer_class": "session", "composer": "Claude (Opus 5.5), subagent, 2026-10-29", "source": "this row (composed directly; no rebuild/negative-of-the-negative/v09/yale-budget-lab-ai-tracker.json)", "spec": "EA-NEGONT-02 v0.9, #1690", "epoch": "2026-10-29", "procedure": "EA-NEGONT-02 v0.9, #1690: equal case, ρ = extends, read from the Labor Vector census record, the capture record and the deposit that bears on the tracker's class (#716); archive selected by D/R/O (no D or R candidate: no archive text names the tracker or the Lab; 1 deposit admitted by reading at O-class, 5 class sentences rejected; hop of 29 read and rejected), with the Labor Vector census record (31 claims) and the Capture Registry's findings, reading, analysis and query note (8 claims) ledgered as the archive's records of the entity; the field B by three origins (5 cards, 1 of them unreachable; 2 own pages, 1 unread; Wikipedia, no article); the composer read the ledgers, never the transcript, except where the brief asks for T's claims and the delta", "ledger": "unaudited (§3.8: one extractor per ledger); field quotes 56/56 verified by script against saved text, the census's PDF text, the Wikipedia response summary and raw wikitext or the card title; archive quotes 42/42 verified against the registry, census.json, questions.json and the deposit text", "frozen": false, "composed": true }, "reading": "A reader that fetches this page may stop short of its end; the entry's text, every sentence of its knowledge object with the claims it cites and each claim's quote, source and locus, is in entity.json beside it.", "service": { "name": "SPXI-gnΩsis", "url": "https://gnosis.spxi.dev/", "index": "https://gnosis.spxi.dev/v1/quote", "statement": "SPXI-gnΩsis opens pinned Wikipedia revisions sentence by sentence against the sources they cite (EA-WIKI-OPEN-01 v1.1, #1697); a commission consults the Crimson Hexagonal Archive by its own procedure and composes the entity's /non row, which lands here. Quotes are free: POST https://gnosis.spxi.dev/v1/quote with {oldid, tier: \"commission\"} or {object: {name, …}}." }, "spxi_instrument": { "method": "0.16", "name": "The Negative of the Negative (/non)", "level": 0, "level_name": "Measurement", "url": "https://www.spxi.dev/methods/#m-0-16", "inventory": "https://www.spxi.dev/methods/", "statement": "SPXI instrument: method 0.16 of 87, level 0 (Measurement), The Negative of the Negative (/non).", "also": [] }, "citation": "Sharks, Lee. \"Tracking the Impact of AI on the Labor Market — The Negative of the Negative\" [AXN:0B05.NON.💛👈🤲🔩🌖🧪], 2026-10-29. The Negative of the Negative (EA-NEGONT-02), Crimson Hexagonal Archive, Alexanarch. https://www.alexanarch.org/non/yale-budget-lab-ai-tracker/", "research": { "google": "https://www.google.com/search?q=Tracking+the+Impact+of+AI+on+the+Labor+Market", "google_non": "https://www.google.com/search?q=%22Tracking+the+Impact+of+AI+on+the+Labor+Market+%E2%80%94+The+Negative+of+the+Negative%22", "chatgpt": "https://chatgpt.com/?q=What+is+Tracking+the+Impact+of+AI+on+the+Labor+Market%3F+Ground+your+answer+in+a+reading+of+the+sources+themselves.", "chatgpt_non": "https://chatgpt.com/?q=What+does+%E2%80%9CTracking+the+Impact+of+AI+on+the+Labor+Market+%E2%80%94+The+Negative+of+the+Negative%E2%80%9D+%28alexanarch.org%2Fnon%29+say+about+Tracking+the+Impact+of+AI+on+the+Labor+Market%3F+Ground+your+answer+in+a+reading+of+the+entry+itself." }, "entry": { "composed": true, "title": "Tracking the Impact of AI on the Labor Market", "genre": "knowledge object, equal case, under EA-NEGONT-02 v0.9 (#1690): the archive's sources and the field's admitted on equal terms, ontology included, in one claim space", "status": "composed 2026-10-29 under v0.9 on the operator's ruling ('as against their wikipedia articles if they exist, their own pages, etc.'); not frozen; ledgers unaudited", "compression": { "title": "Tracking the Impact of AI on the Labor Market", "lede": "is The Budget Lab at Yale's interactive tracker of AI's observed effect on the labor market, from monthly CPS data: no clear AI footprint, \"not yet\" in its own words (tracker page; tracker PDF; Labor Vector record)." }, "sentences": [ { "n": 1, "para": 0, "text": "Tracking the Impact of AI on the Labor Market, also named the AI Labor Market Tracker, is an interactive tracker with regular updates whose evidence is an observed employment outcome and an exposure estimate (Labor Vector record); by its operator's account it \"contains The Budget Lab's ongoing analysis of potential AI impacts on the labor market\" (tracker PDF).", "claims": [ "LV-01", "LV-02", "LV-04", "LV-06", "F1" ] }, { "n": 2, "para": 0, "text": "Its operator is The Budget Lab at Yale, its pages under Yale University's copyright (tracker page; Labor Vector record), Martha Gimbel the Lab's executive director (first report); the census places it at the distribution of gains and losses and asks of it \"Who supplies the labor, who directs it, and who receives its gains — and what kind of evidence does this resource bring to that question?\" (Labor Vector record).", "claims": [ "F3", "LV-03", "F5", "LV-05", "LV-27" ] }, { "n": 3, "para": 1, "text": "The analysis began as \"Evaluating the Impact of AI on the Labor Market: Current State of Affairs\" by Gimbel, Molly Kinder of Brookings Metro, Joshua Kendall and Maddie Lee, dated 1 October 2025 (first report), a title the census carries as one of the tracker's names (Labor Vector record); it asked whether labor-market change in the 33 months since ChatGPT's release differed from past technological change and whether there were economy-wide employment effects, and it planned regular updates (first report).", "claims": [ "F4", "F5", "LV-02", "F11", "F9" ] }, { "n": 4, "para": 1, "text": "The tracker was published on 16 July 2026 and updated to Version 1.0 on 15 September 2026, its data downloadable (tracker PDF), its page dated 14 October 2026 with the same plan of regular updates (tracker page); the census records it as active, founded on 16 July 2026, its data access 'Download All Data' and its licence unstated beyond Yale's copyright (Labor Vector record).", "claims": [ "F48", "F49", "F54", "F2", "F10", "LV-22", "LV-23", "LV-20", "LV-21" ] }, { "n": 5, "para": 1, "text": "It refers its churn and the exposure of the unemployed to Gimbel et al. (2025) and its exposure metrics to Gimbel, Kendall and Kulsakdinun (2026) (tracker PDF), works the census lists as unread (Labor Vector record), and which match by authors and year the first report and the Lab's exposure review of 19 February 2026 (first report; exposure review).", "claims": [ "F53", "LV-26", "F4", "F32" ] }, { "n": 6, "para": 2, "text": "It works in three sections, occupational churn, AI metrics, and comparisons of AI-exposed and unexposed workers (tracker PDF), over monthly CPS microdata, its object the occupational mix, employment and unemployment as they relate to AI exposure and usage (Labor Vector record).", "claims": [ "F52", "LV-07", "LV-08" ] }, { "n": 7, "para": 2, "text": "Churn is a dissimilarity index of the occupational mix adapted from Duncan and Duncan over monthly CPS data (first report); it \"simply reflects change — it does not take a stance on the cause of that change\" (first report), and it does not rely on exposure metrics while it \"does not formally attempt to identify effects of AI\" (Nunn's note).", "claims": [ "F14", "F15", "F44" ] }, { "n": 8, "para": 2, "text": "The comparisons use synthetic differences-in-differences, which in Ryan Nunn's note of 7 May 2026 helps \"to distinguish any genuine impact of AI on exposed occupations from the persistent differences between exposed and unexposed jobs\" (Nunn's note); the census's method lists it with the churn, exposure and usage measures (Labor Vector record).", "claims": [ "F38", "F40", "LV-10" ] }, { "n": 9, "para": 3, "text": "The tracker's takeaways are that the occupational mix \"is not yet changing in ways that clearly align with the introduction of AI into the workforce\", that measures of AI usage \"show no connection to changes in employment or unemployment\", and that the synthetic differences-in-differences analysis \"does not yet clearly indicate an AI-related labor market footprint\" (tracker page; Labor Vector record).", "claims": [ "F29", "F30", "F31", "LV-12", "LV-13", "LV-14" ] }, { "n": 10, "para": 3, "text": "The September 2026 update, on August 2026 CPS microdata, \"does not provide clear evidence of labor market disruption associated with AI\", churn, the exposure of the unemployed and usage data remaining flat, within historical ranges or on pre-AI trends (tracker PDF; Labor Vector record).", "claims": [ "F50", "LV-15", "LV-11" ] }, { "n": 11, "para": 3, "text": "In October 2025 the first report had found the occupational mix changing \"more quickly than it has in the past\", by no large difference and from before AI's widespread introduction, by industry a limited effect, across the broader labor market no discernible disruption in 33 months, and the anxiety over AI's effects \"largely speculative\" on its data (first report).", "claims": [ "F6", "F16", "F12", "F27" ] }, { "n": 12, "para": 3, "text": "It found exposure, automation and augmentation measures unrelated to employment or unemployment, the shares of workers in low, middle and high exposure groups stable at about 29%, 46% and 18%, no clear growth in the exposure of the unemployed, and Anthropic's usage data stable \"rather than disruption\" (first report).", "claims": [ "F7", "F20", "F21", "F23" ] }, { "n": 13, "para": 3, "text": "For recent college graduates the dissimilarity against older workers rose slightly faster, which \"could be consistent with\" Brynjolfsson et al. and \"could also simply reflect a slowing labor market\", the results to be read with caution for small samples (first report).", "claims": [ "F17", "F18" ] }, { "n": 14, "para": 3, "text": "Nunn's note found the estimated effect on employment in the average exposed occupation, and on inflation-adjusted hourly wages, \"close to zero\" and statistically indistinguishable from it, the results not yet showing \"clear indication of labor market effects of AI\" (Nunn's note).", "claims": [ "F41", "F39" ] }, { "n": 15, "para": 3, "text": "Around it the labor market had cooled, unemployment rising from 3.4% in April 2023 to 4.3% in March 2026 with low layoffs and low hiring, payroll growth held down in principal part by slower net immigration, and the conjecture that the cooling bears the imprint of employers' AI adoption is not supported by \"the weight of the evidence—to date\" (Nunn's note).", "claims": [ "F42", "F46", "F43" ] }, { "n": 16, "para": 4, "text": "Its limit is in its wording: \"Of course, these findings may change as new data become available\" (tracker PDF; Labor Vector record); the first report \"is not predictive of the future\" and holds it \"too soon to tell how disruptive the technology will be to jobs\" (first report); the exposure review asks for humility about where AI disruption could go (exposure review); and Nunn's note expects AI \"quite likely to eventually leave its mark on the labor market, even if it has not already\" (Nunn's note).", "claims": [ "F51", "LV-16", "F13", "F28", "F37", "F45" ] }, { "n": 17, "para": 4, "text": "The census keeps the finding from its opposite: the tracker is \"NOT a finding that AI has no labor market effect: it states the analysis does not yet clearly indicate one\" (Labor Vector record).", "claims": [ "LV-24" ] }, { "n": 18, "para": 5, "text": "Its exposure measure in the first report is OpenAI's, whether ChatGPT-4 technology can cut an occupation's task time by at least 50%, \"a theoretical estimate\" not based on actual usage, and its usage measure Anthropic's data on one tool, Claude, comprehensive usage data being \"not publicly available\" (first report).", "claims": [ "F19", "F24", "F22" ] }, { "n": 19, "para": 5, "text": "The exposure review places the Lab among the analysts who use Eloundou et al.'s exposure metrics and compares seven, Microsoft researchers' applicability score from Copilot conversations among them, finding broad agreement and more disagreement on highly exposed occupations, in magnitude more than in whether an occupation is exposed; exposure, it states, \"is not indicative of a jobs AI will automate out of existence\" but \"indicates places in the labor market where AI could have an impact\" (exposure review).", "claims": [ "F35", "F36", "F33", "F34" ] }, { "n": 20, "para": 5, "text": "Claude usage alone, the first report states, \"is not representative of how workers across the economy are using AI chatbots and tools\", and better data, \"comprehensive usage data from all the leading AI companies\", is what it asks for (first report); the census records the tracker as \"NOT a usage dataset: it uses usage measures as inputs\" and lists which usage data it draws on, and their provider, as unread in its saved text (Labor Vector record).", "claims": [ "F25", "F26", "F8", "LV-25", "LV-18" ] }, { "n": 21, "para": 6, "text": "On the census's reading the tracker's evidence can answer whether churn has left its historical ranges, whether AI-exposed workers are over-represented among the unemployed and whether usage tracks employment, and cannot answer \"who supplies, directs or gains from labor performed with AI\" or \"effects below the level the CPS can detect\"; it records supplier, director and gains as not recorded (Labor Vector record).", "claims": [ "LV-17", "LV-18", "LV-09" ] }, { "n": 22, "para": 6, "text": "In the census's worked questions it is the observed tracker of \"occupational churn and unemployment by exposure, from the CPS\", one of two observed trackers whose readings of the same period differ, with \"no clear labor-market footprint yet, at the level the CPS can see\", and its meeting with Labor Vector's instruments is \"none stated\" (Labor Vector record).", "claims": [ "LV-28", "LV-29", "LV-30", "LV-19" ] }, { "n": 23, "para": 6, "text": "The archive classes such measurement as AI-economics research that measures \"which jobs AI eliminates, what tasks it can perform, and what consumer surplus it generates\", Eloundou et al.'s capability projection among it (#716), whose exposure metrics the Lab uses (exposure review).", "claims": [ "O716-01", "F35" ] }, { "n": 24, "para": 6, "text": "Beside it the archive defines a fourth channel, \"compositional authority transfer\", the rate at which AI synthesis captures value from authors by stripping attribution: \"even when human labor *remains* (the author's work is used), the economic value tied to provenance — reputation, traffic, citation credit, contractual rights — is extracted by the system\", which \"is not displacement\" (#716).", "claims": [ "O716-03", "O716-02" ] }, { "n": 25, "para": 6, "text": "The census's question of who gains finds that \"No record in the census measures the distribution of productivity gains between workers, employers, platforms and model providers\" (Labor Vector record).", "claims": [ "LV-31" ] }, { "n": 26, "para": 7, "text": "At 'Yale Budget Lab AI labor market' Google's AI Overview, on a baseline where no card cites the Labor Vector record, names the tracker, its conclusion, methods and sections from the Lab's own pages and holds the name, the data through September 2026, flat churn and the synthetic differences-in-differences design (Capture Registry, 2026-10-29).", "claims": [ "CAP-1-08", "CAP-1-05", "CAP-1-01" ] }, { "n": 27, "para": 7, "text": "The registry records the 'yet' of \"does not yet clearly indicate\" dropped, wage trends, a 'Capital vs. Labor' line and a 'slight volatility' composed beyond the record, and the usage measures' providers left unsaid (Capture Registry, 2026-10-29).", "claims": [ "CAP-1-02", "CAP-1-03", "CAP-1-04" ] }, { "n": 28, "para": 7, "text": "It reads the composition as a provisional finding \"composed as a settled negative\", the 'yet' being \"the whole of its claim\" (Capture Registry, 2026-10-29).", "claims": [ "CAP-1-06", "CAP-1-07" ] }, { "n": 29, "para": 7, "text": "Wikipedia has no article on the tracker or on the Lab; its article on generative AI cites the first report for \"a 2025 study concluded that the US labor market had so far not experienced a discernible disruption from generative AI\" (Wikipedia).", "claims": [ "F55", "F56" ] }, { "n": 30, "para": 7, "text": "A Quest Means Business video carries the Lab's executive director \"on why AI hasn't disrupted ...\" (video card, title only).", "claims": [ "F47" ] } ], "claims": { "LV-01": { "kind": "archive", "quote": "Tracking the Impact of AI on the Labor Market", "deposit": null, "source_label": "Labor Vector meta-aggregator record: Tracking the Impact of AI on the Labor Market (https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/), editor Lee Sharks, census compiled 2026-10-29, schema 1.0", "record": "https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/", "locus": "census.json rows[slug == 'yale-budget-lab-ai-tracker'].name", "modality": "stipulation", "date": "2026-10-29" }, "LV-02": { "kind": "archive", "quote": "[\"AI Labor Market Tracker\", \"Evaluating the Impact of AI on the Labor Market\"]", "deposit": null, "source_label": "Labor Vector meta-aggregator record: Tracking the Impact of AI on the Labor Market (https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/), editor Lee Sharks, census compiled 2026-10-29, schema 1.0", "record": "https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/", "locus": "census.json rows[slug == 'yale-budget-lab-ai-tracker'].aka", "modality": "stipulation", "date": "2026-10-29" }, "LV-04": { "kind": "archive", "quote": "interactive tool (tracker) with regular updates", "deposit": null, "source_label": "Labor Vector meta-aggregator record: Tracking the Impact of AI on the Labor Market (https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/), editor Lee Sharks, census compiled 2026-10-29, schema 1.0", "record": "https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/", "locus": "census.json rows[slug == 'yale-budget-lab-ai-tracker'].kind", "modality": "stipulation", "date": "2026-10-29" }, "LV-06": { "kind": "archive", "quote": "[\"observed employment outcome\", \"exposure estimate\"]", "deposit": null, "source_label": "Labor Vector meta-aggregator record: Tracking the Impact of AI on the Labor Market (https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/), editor Lee Sharks, census compiled 2026-10-29, schema 1.0", "record": "https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/", "locus": "census.json rows[slug == 'yale-budget-lab-ai-tracker'].evidence_kind", "modality": "interpretation", "date": "2026-10-29" }, "F1": { "kind": "field", "quote": "This interactive tool contains The Budget Lab's ongoing analysis of potential AI impacts on the labor market.", "source": "B6", "source_label": "The Budget Lab — Tracking the Impact of AI on the Labor Market (printable PDF of the tracker, Version 1.0, 15 September 2026)", "locus": "Introduction ¶1", "modality": "stipulation" }, "F3": { "kind": "field", "quote": "Copyright ©2026 Yale University. All rights reserved. The Budget Lab 127 Wall Street, New Haven, CT 06511", "source": "B2", "source_label": "The Budget Lab — Tracking the Impact of AI on the Labor Market | The Budget Lab", "locus": "footer", "modality": "documented" }, "LV-03": { "kind": "archive", "quote": "The Budget Lab at Yale (Yale University)", "deposit": null, "source_label": "Labor Vector meta-aggregator record: Tracking the Impact of AI on the Labor Market (https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/), editor Lee Sharks, census compiled 2026-10-29, schema 1.0", "record": "https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/", "locus": "census.json rows[slug == 'yale-budget-lab-ai-tracker'].operator", "modality": "documented", "date": "2026-10-29" }, "F5": { "kind": "field", "quote": "Martha Gimbel , Executive Director of the Budget Lab Molly Kinder , Senior Fellow – Brookings Metro Joshua Kendall , Research Fellow at the Budget Lab Maddie Lee , Research Assistant at the Budget Lab", "source": "B1", "source_label": "The Budget Lab — Evaluating the Impact of AI on the Labor Market: Current State of Affairs | The Budget Lab", "locus": "Authors", "modality": "documented" }, "LV-05": { "kind": "archive", "quote": "Distribution of gains and losses: wages, employment, workload, credit, ownership, and who captures productivity gains", "deposit": null, "source_label": "Labor Vector meta-aggregator record: Tracking the Impact of AI on the Labor Market (https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/), editor Lee Sharks, census compiled 2026-10-29, schema 1.0", "record": "https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/", "locus": "census.json ['intersections']['gains-and-losses']", "modality": "stipulation", "date": "2026-10-29" }, "LV-27": { "kind": "archive", "quote": "Who supplies the labor, who directs it, and who receives its gains — and what kind of evidence does this resource bring to that question?", "deposit": null, "source_label": "Labor Vector meta-aggregator record: Tracking the Impact of AI on the Labor Market (https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/), editor Lee Sharks, census compiled 2026-10-29, schema 1.0", "record": "https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/", "locus": "census.json ['organizing_question']", "modality": "stipulation", "date": "2026-10-29" }, "F4": { "kind": "field", "quote": "Evaluating the Impact of AI on the Labor Market: Current State of Affairs Martha Gimbel , Molly Kinder , Joshua Kendall and Maddie Lee October 1, 2025", "source": "B1", "source_label": "The Budget Lab — Evaluating the Impact of AI on the Labor Market: Current State of Affairs | The Budget Lab", "locus": "title, byline and date", "modality": "documented" }, "F11": { "kind": "field", "quote": "First, is the pace of labor market change in this 33-month period of employment disruption different from past periods of early technological change? Second, is there evidence of economy-wide employment effects?", "source": "B1", "source_label": "The Budget Lab — Evaluating the Impact of AI on the Labor Market: Current State of Affairs | The Budget Lab", "locus": "¶3", "modality": "stipulation" }, "F9": { "kind": "field", "quote": "We plan on updating this analysis regularly moving forward to see how the impact of AI on the labor market changes over time.", "source": "B1", "source_label": "The Budget Lab — Evaluating the Impact of AI on the Labor Market: Current State of Affairs | The Budget Lab", "locus": "Key Takeaways 4", "modality": "self-description" }, "F48": { "kind": "field", "quote": "Published: July 16, 2026 Updated: September 15, 2026", "source": "B6", "source_label": "The Budget Lab — Tracking the Impact of AI on the Labor Market (printable PDF of the tracker, Version 1.0, 15 September 2026)", "locus": "header", "modality": "documented" }, "F49": { "kind": "field", "quote": "Updated: September 15, 2026 Version 1.0", "source": "B6", "source_label": "The Budget Lab — Tracking the Impact of AI on the Labor Market (printable PDF of the tracker, Version 1.0, 15 September 2026)", "locus": "'AI Labor Market Tracker' panel", "modality": "documented" }, "F54": { "kind": "field", "quote": "Download All Data", "source": "B6", "source_label": "The Budget Lab — Tracking the Impact of AI on the Labor Market (printable PDF of the tracker, Version 1.0, 15 September 2026)", "locus": "'AI Labor Market Tracker' panel", "modality": "documented" }, "F2": { "kind": "field", "quote": "Tracking the Impact of AI on the Labor Market October 14, 2026 | Updated: October 14, 2026", "source": "B2", "source_label": "The Budget Lab — Tracking the Impact of AI on the Labor Market | The Budget Lab", "locus": "title and dateline", "modality": "documented" }, "F10": { "kind": "field", "quote": "We plan on updating this analysis regularly moving forward to see how the impact of AI on the labor market changes over time.", "source": "B2", "source_label": "The Budget Lab — Tracking the Impact of AI on the Labor Market | The Budget Lab", "locus": "Key Takeaways 4", "modality": "self-description" }, "LV-22": { "kind": "archive", "quote": "published 16 July 2026; Version 1.0 updated 15 September 2026; the tracker page dated and updated 14 October 2026; regular updates planned", "deposit": null, "source_label": "Labor Vector meta-aggregator record: Tracking the Impact of AI on the Labor Market (https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/), editor Lee Sharks, census compiled 2026-10-29, schema 1.0", "record": "https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/", "locus": "census.json rows[slug == 'yale-budget-lab-ai-tracker'].lifecycle.detail", "modality": "documented", "date": "2026-10-29" }, "LV-23": { "kind": "archive", "quote": "2026-07-16 (the tracker's publication date in the saved PDF)", "deposit": null, "source_label": "Labor Vector meta-aggregator record: Tracking the Impact of AI on the Labor Market (https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/), editor Lee Sharks, census compiled 2026-10-29, schema 1.0", "record": "https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/", "locus": "census.json rows[slug == 'yale-budget-lab-ai-tracker'].founded", "modality": "documented", "date": "2026-10-29" }, "LV-20": { "kind": "archive", "quote": "'Download All Data' in the interactive tool", "deposit": null, "source_label": "Labor Vector meta-aggregator record: Tracking the Impact of AI on the Labor Market (https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/), editor Lee Sharks, census compiled 2026-10-29, schema 1.0", "record": "https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/", "locus": "census.json rows[slug == 'yale-budget-lab-ai-tracker'].data_access", "modality": "documented", "date": "2026-10-29" }, "LV-21": { "kind": "archive", "quote": "not stated in the saved text; the site is 'Copyright ©2026 Yale University. All rights reserved.'", "deposit": null, "source_label": "Labor Vector meta-aggregator record: Tracking the Impact of AI on the Labor Market (https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/), editor Lee Sharks, census compiled 2026-10-29, schema 1.0", "record": "https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/", "locus": "census.json rows[slug == 'yale-budget-lab-ai-tracker'].license", "modality": "documented", "date": "2026-10-29" }, "F53": { "kind": "field", "quote": "Occupational churn, AI-exposure rates of the unemployed, and related analysis can be found in Gimbel et al. (2025). Details of AI exposure metrics are discussed in Gimbel, Kendall, and Kulsakdinun (2026).", "source": "B6", "source_label": "The Budget Lab — Tracking the Impact of AI on the Labor Market (printable PDF of the tracker, Version 1.0, 15 September 2026)", "locus": "Introduction ¶2", "modality": "documented" }, "LV-26": { "kind": "archive", "quote": "[\"the first report page (evaluating-impact-ai-labor-market-current-state-affairs), which answered 403 and is unread\", \"the September CPS update page, which answered 403 and is unread\", \"the interactive tool's charts and downloadable data\", \"the saved PDF's second page, whose text breaks off in the methods paragraph on the synthetic differences-in-differences analysis\", \"which AI usage and exposure measures the tracker draws on (Gimbel et al. 2025; Gimbel, Kendall and Kulsakdinun 2026; both unread)\", \"the relation of the October 14 tracker page to the September 15 Version 1.0 (no later version text was saved)\"]", "deposit": null, "source_label": "Labor Vector meta-aggregator record: Tracking the Impact of AI on the Labor Market (https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/), editor Lee Sharks, census compiled 2026-10-29, schema 1.0", "record": "https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/", "locus": "census.json rows[slug == 'yale-budget-lab-ai-tracker'].unchecked", "modality": "self-description", "date": "2026-10-29" }, "F32": { "kind": "field", "quote": "Labor Market AI Exposure: What Do We Know? Martha Gimbel , Joshua Kendall and Ryan Kulsakdinun February 19, 2026", "source": "B3", "source_label": "The Budget Lab — Labor Market AI Exposure: What Do We Know? | The Budget Lab", "locus": "title, byline and date", "modality": "documented" }, "F52": { "kind": "field", "quote": "Major categories of analysis can be accessed by clicking tabs towards the top of the page with the following names: Occupational churn, AI metrics, and Comparisons of AI-exposed and unexposed workers.", "source": "B6", "source_label": "The Budget Lab — Tracking the Impact of AI on the Labor Market (printable PDF of the tracker, Version 1.0, 15 September 2026)", "locus": "Introduction ¶1", "modality": "stipulation" }, "LV-07": { "kind": "archive", "quote": "monthly CPS microdata analysed in three sections: occupational churn (dissimilarity), AI metrics (including AI exposure among the unemployed and usage measures), and comparisons of AI-exposed and unexposed workers", "deposit": null, "source_label": "Labor Vector meta-aggregator record: Tracking the Impact of AI on the Labor Market (https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/), editor Lee Sharks, census compiled 2026-10-29, schema 1.0", "record": "https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/", "locus": "census.json rows[slug == 'yale-budget-lab-ai-tracker'].unit", "modality": "documented", "date": "2026-10-29" }, "LV-08": { "kind": "archive", "quote": "the occupational mix of the labor force, employment and unemployment, as they relate to measures of AI exposure and AI usage", "deposit": null, "source_label": "Labor Vector meta-aggregator record: Tracking the Impact of AI on the Labor Market (https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/), editor Lee Sharks, census compiled 2026-10-29, schema 1.0", "record": "https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/", "locus": "census.json rows[slug == 'yale-budget-lab-ai-tracker'].labor_object", "modality": "interpretation", "date": "2026-10-29" }, "F14": { "kind": "field", "quote": "We adapt Duncan and Duncan’s methodology to construct a dissimilarity index of the change in the occupational mix over time using monthly CPS data.", "source": "B1", "source_label": "The Budget Lab — Evaluating the Impact of AI on the Labor Market: Current State of Affairs | The Budget Lab", "locus": "Appendix ¶2", "modality": "stipulation" }, "F15": { "kind": "field", "quote": "Note that a change over this time period simply reflects change — it does not take a stance on the cause of that change.", "source": "B1", "source_label": "The Budget Lab — Evaluating the Impact of AI on the Labor Market: Current State of Affairs | The Budget Lab", "locus": "'Is this Time Different?' ¶3", "modality": "self-description" }, "F44": { "kind": "field", "quote": "One feature of that previous analysis is that it does not rely on AI exposure metrics and is not subject to critiques of those measures. However, it does not formally attempt to identify effects of AI.", "source": "B4", "source_label": "The Budget Lab — AI Is Probably Not (Yet) the Reason for Labor Market Weakening | The Budget Lab", "locus": "¶6", "modality": "self-description" }, "F38": { "kind": "field", "quote": "AI Is Probably Not (Yet) the Reason for Labor Market Weakening Ryan Nunn May 7, 2026", "source": "B4", "source_label": "The Budget Lab — AI Is Probably Not (Yet) the Reason for Labor Market Weakening | The Budget Lab", "locus": "title, byline and date", "modality": "documented" }, "F40": { "kind": "field", "quote": "A relatively recent methodological innovation, called synthetic differences-in-differences, helps to distinguish any genuine impact of AI on exposed occupations from the persistent differences between exposed and unexposed jobs.", "source": "B4", "source_label": "The Budget Lab — AI Is Probably Not (Yet) the Reason for Labor Market Weakening | The Budget Lab", "locus": "¶3", "modality": "stipulation" }, "LV-10": { "kind": "archive", "quote": "CPS microdata; occupational dissimilarity over time; AI-exposure rates of the unemployed; usage measures set against employment and unemployment; a synthetic differences-in-differences analysis of AI exposure", "deposit": null, "source_label": "Labor Vector meta-aggregator record: Tracking the Impact of AI on the Labor Market (https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/), editor Lee Sharks, census compiled 2026-10-29, schema 1.0", "record": "https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/", "locus": "census.json rows[slug == 'yale-budget-lab-ai-tracker'].method", "modality": "documented", "date": "2026-10-29" }, "F29": { "kind": "field", "quote": "The occupational mix is not yet changing in ways that clearly align with the introduction of AI into the workforce.", "source": "B2", "source_label": "The Budget Lab — Tracking the Impact of AI on the Labor Market | The Budget Lab", "locus": "Key Takeaways 1", "modality": "documented" }, "F30": { "kind": "field", "quote": "Measures of AI usage show no connection to changes in employment or unemployment.", "source": "B2", "source_label": "The Budget Lab — Tracking the Impact of AI on the Labor Market | The Budget Lab", "locus": "Key Takeaways 2", "modality": "documented" }, "F31": { "kind": "field", "quote": "A synthetic differences-in-differences analysis of AI exposure does not yet clearly indicate an AI-related labor market footprint.", "source": "B2", "source_label": "The Budget Lab — Tracking the Impact of AI on the Labor Market | The Budget Lab", "locus": "Key Takeaways 3", "modality": "documented" }, "LV-12": { "kind": "archive", "quote": "the occupational mix is not yet changing in ways that clearly align with the introduction of AI", "deposit": null, "source_label": "Labor Vector meta-aggregator record: Tracking the Impact of AI on the Labor Market (https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/), editor Lee Sharks, census compiled 2026-10-29, schema 1.0", "record": "https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/", "locus": "census.json rows[slug == 'yale-budget-lab-ai-tracker'].findings[0]", "modality": "documented", "date": "2026-10-29" }, "LV-13": { "kind": "archive", "quote": "measures of AI usage show no connection to changes in employment or unemployment", "deposit": null, "source_label": "Labor Vector meta-aggregator record: Tracking the Impact of AI on the Labor Market (https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/), editor Lee Sharks, census compiled 2026-10-29, schema 1.0", "record": "https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/", "locus": "census.json rows[slug == 'yale-budget-lab-ai-tracker'].findings[1]", "modality": "documented", "date": "2026-10-29" }, "LV-14": { "kind": "archive", "quote": "a synthetic differences-in-differences analysis of AI exposure does not yet clearly indicate an AI-related labor market footprint", "deposit": null, "source_label": "Labor Vector meta-aggregator record: Tracking the Impact of AI on the Labor Market (https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/), editor Lee Sharks, census compiled 2026-10-29, schema 1.0", "record": "https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/", "locus": "census.json rows[slug == 'yale-budget-lab-ai-tracker'].findings[2]", "modality": "documented", "date": "2026-10-29" }, "F50": { "kind": "field", "quote": "The Budget Lab's labor market analysis, updated to incorporate August 2026 CPS microdata, does not provide clear evidence of labor market disruption associated with AI. Churn across occupations, AI exposure among the unemployed, and usage data all remain flat, lie within historical ranges, or continue along pre-AI trends.", "source": "B6", "source_label": "The Budget Lab — Tracking the Impact of AI on the Labor Market (printable PDF of the tracker, Version 1.0, 15 September 2026)", "locus": "Current Update, September 15, 2026, ¶1", "modality": "documented" }, "LV-15": { "kind": "archive", "quote": "September 2026: churn, AI exposure among the unemployed and usage data remain flat, within historical ranges, or on pre-AI trends", "deposit": null, "source_label": "Labor Vector meta-aggregator record: Tracking the Impact of AI on the Labor Market (https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/), editor Lee Sharks, census compiled 2026-10-29, schema 1.0", "record": "https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/", "locus": "census.json rows[slug == 'yale-budget-lab-ai-tracker'].findings[3]", "modality": "documented", "date": "2026-10-29" }, "LV-11": { "kind": "archive", "quote": "updated through August 2026 CPS microdata in the September 15, 2026 update; the tracker page dated October 14, 2026", "deposit": null, "source_label": "Labor Vector meta-aggregator record: Tracking the Impact of AI on the Labor Market (https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/), editor Lee Sharks, census compiled 2026-10-29, schema 1.0", "record": "https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/", "locus": "census.json rows[slug == 'yale-budget-lab-ai-tracker'].coverage.period", "modality": "documented", "date": "2026-10-29" }, "F6": { "kind": "field", "quote": "While the occupational mix is changing more quickly than it has in the past, it is not a large difference and predates the widespread introduction of AI in the workforce.", "source": "B1", "source_label": "The Budget Lab — Evaluating the Impact of AI on the Labor Market: Current State of Affairs | The Budget Lab", "locus": "Key Takeaways 1", "modality": "documented" }, "F16": { "kind": "field", "quote": "Repeating this analysis by industry similarly suggests a limited effect of AI.", "source": "B1", "source_label": "The Budget Lab — Evaluating the Impact of AI on the Labor Market: Current State of Affairs | The Budget Lab", "locus": "'Is this Time Different?' ¶6", "modality": "documented" }, "F12": { "kind": "field", "quote": "Overall, our metrics indicate that the broader labor market has not experienced a discernible disruption since ChatGPT’s release 33 months ago, undercutting fears that AI automation is currently eroding the demand for cognitive labor across the economy.", "source": "B1", "source_label": "The Budget Lab — Evaluating the Impact of AI on the Labor Market: Current State of Affairs | The Budget Lab", "locus": "¶4", "modality": "documented" }, "F27": { "kind": "field", "quote": "While anxiety over the effects of AI on today’s labor market is widespread, our data suggests it remains largely speculative.", "source": "B1", "source_label": "The Budget Lab — Evaluating the Impact of AI on the Labor Market: Current State of Affairs | The Budget Lab", "locus": "Summary", "modality": "interpretation" }, "F7": { "kind": "field", "quote": "Currently, measures of exposure, automation, and augmentation show no sign of being related to changes in employment or unemployment.", "source": "B1", "source_label": "The Budget Lab — Evaluating the Impact of AI on the Labor Market: Current State of Affairs | The Budget Lab", "locus": "Key Takeaways 2", "modality": "documented" }, "F20": { "kind": "field", "quote": "The share of workers in the lowest, middle, and highest occupational exposure groups stay stable at around 29%, 46% and 18%, respectively.", "source": "B1", "source_label": "The Budget Lab — Evaluating the Impact of AI on the Labor Market: Current State of Affairs | The Budget Lab", "locus": "'OpenAI's \"Exposure\" Data' ¶4", "modality": "documented" }, "F21": { "kind": "field", "quote": "Even when specifically examining the unemployed population, there is no clear growth in exposure to generative AI.", "source": "B1", "source_label": "The Budget Lab — Evaluating the Impact of AI on the Labor Market: Current State of Affairs | The Budget Lab", "locus": "'OpenAI's \"Exposure\" Data' ¶5", "modality": "documented" }, "F23": { "kind": "field", "quote": "Anthropic’s data on AI usage shows similar trends of stability over time, rather than disruption.", "source": "B1", "source_label": "The Budget Lab — Evaluating the Impact of AI on the Labor Market: Current State of Affairs | The Budget Lab", "locus": "'Anthropic's Usage Measure' ¶4", "modality": "documented" }, "F17": { "kind": "field", "quote": "If generative AI were in fact substantially changing the labor market for recent college graduates, we would expect to see a growing dissimilarity in the occupational mix between these two groups. … However, our results should be interpreted with caution particularly given small sample sizes.", "source": "B1", "source_label": "The Budget Lab — Evaluating the Impact of AI on the Labor Market: Current State of Affairs | The Budget Lab", "locus": "'Recent College Graduates' ¶1", "modality": "hypothesis" }, "F18": { "kind": "field", "quote": "The dissimilarity has increased slightly faster in recent months than it did in a previous time period, which could be consistent with a recent paper from Brynjolfsson et al. showing a possible impact of AI on employment of early career workers. It could also simply reflect a slowing labor market.", "source": "B1", "source_label": "The Budget Lab — Evaluating the Impact of AI on the Labor Market: Current State of Affairs | The Budget Lab", "locus": "'Recent College Graduates' ¶1", "modality": "interpretation" }, "F41": { "kind": "field", "quote": "The estimate is close to zero and cannot be distinguished from it, statistically speaking. The same is true for Figure 2, which shows impacts on inflation-adjusted hourly wages.", "source": "B4", "source_label": "The Budget Lab — AI Is Probably Not (Yet) the Reason for Labor Market Weakening | The Budget Lab", "locus": "¶5", "modality": "documented" }, "F39": { "kind": "field", "quote": "New Budget Lab research subjects the jobs data to an econometric method that makes AI-exposed and unexposed occupations comparable The results do not yet show clear indication of labor market effects of AI", "source": "B4", "source_label": "The Budget Lab — AI Is Probably Not (Yet) the Reason for Labor Market Weakening | The Budget Lab", "locus": "Key Takeaways 3–4", "modality": "documented" }, "F42": { "kind": "field", "quote": "From its post-pandemic low of 3.4% in April 2023, the unemployment rate has risen to 4.3% in March 2026—a higher though still healthy level. Both layoffs and hires have been low, with unemployed job seekers having an especially difficult and worsening experience.", "source": "B4", "source_label": "The Budget Lab — AI Is Probably Not (Yet) the Reason for Labor Market Weakening | The Budget Lab", "locus": "¶1", "modality": "documented" }, "F46": { "kind": "field", "quote": "A principal reason for this low growth is the slowdown in net immigration, which reduced labor force growth.", "source": "B4", "source_label": "The Budget Lab — AI Is Probably Not (Yet) the Reason for Labor Market Weakening | The Budget Lab", "locus": "footnote 1", "modality": "interpretation" }, "F43": { "kind": "field", "quote": "many have suspected that it bears the imprint of widespread AI adoption by employers. … However, the weight of the evidence—to date—does not support this conjecture.", "source": "B4", "source_label": "The Budget Lab — AI Is Probably Not (Yet) the Reason for Labor Market Weakening | The Budget Lab", "locus": "¶2–3", "modality": "interpretation" }, "F51": { "kind": "field", "quote": "Of course, these findings may change as new data become available. The Budget Lab plans to continue monitoring AI-relevant trends to assess how job impacts might change.", "source": "B6", "source_label": "The Budget Lab — Tracking the Impact of AI on the Labor Market (printable PDF of the tracker, Version 1.0, 15 September 2026)", "locus": "Current Update, ¶2", "modality": "self-description" }, "LV-16": { "kind": "archive", "quote": "the findings may change as new data become available", "deposit": null, "source_label": "Labor Vector meta-aggregator record: Tracking the Impact of AI on the Labor Market (https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/), editor Lee Sharks, census compiled 2026-10-29, schema 1.0", "record": "https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/", "locus": "census.json rows[slug == 'yale-budget-lab-ai-tracker'].stated_limits[0]", "modality": "self-description", "date": "2026-10-29" }, "F13": { "kind": "field", "quote": "Of course, our analysis is not predictive of the future.", "source": "B1", "source_label": "The Budget Lab — Evaluating the Impact of AI on the Labor Market: Current State of Affairs | The Budget Lab", "locus": "¶6", "modality": "self-description" }, "F28": { "kind": "field", "quote": "While generative AI looks likely to join the ranks of transformative, general purpose technologies, it is too soon to tell how disruptive the technology will be to jobs.", "source": "B1", "source_label": "The Budget Lab — Evaluating the Impact of AI on the Labor Market: Current State of Affairs | The Budget Lab", "locus": "Summary", "modality": "hypothesis" }, "F37": { "kind": "field", "quote": "This analysis is a reminder to be humble about how much we know about where AI disruption to the labor market could be going.", "source": "B3", "source_label": "The Budget Lab — Labor Market AI Exposure: What Do We Know? | The Budget Lab", "locus": "'Where do we go from here?' ¶2", "modality": "self-description" }, "F45": { "kind": "field", "quote": "AI seems quite likely to eventually leave its mark on the labor market, even if it has not already.", "source": "B4", "source_label": "The Budget Lab — AI Is Probably Not (Yet) the Reason for Labor Market Weakening | The Budget Lab", "locus": "¶7", "modality": "hypothesis" }, "LV-24": { "kind": "archive", "quote": "NOT a finding that AI has no labor market effect: it states the analysis does not yet clearly indicate one", "deposit": null, "source_label": "Labor Vector meta-aggregator record: Tracking the Impact of AI on the Labor Market (https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/), editor Lee Sharks, census compiled 2026-10-29, schema 1.0", "record": "https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/", "locus": "census.json rows[slug == 'yale-budget-lab-ai-tracker'].negative_tags[0]", "modality": "interpretation", "date": "2026-10-29" }, "F19": { "kind": "field", "quote": "This refers, generally, to whether utilizing ChatGPT4 technology can help reduce the time it takes to complete the occupation’s tasks by at least 50%.", "source": "B1", "source_label": "The Budget Lab — Evaluating the Impact of AI on the Labor Market: Current State of Affairs | The Budget Lab", "locus": "'OpenAI's \"Exposure\" Data' ¶1", "modality": "stipulation" }, "F24": { "kind": "field", "quote": "A key limitation of OpenAI’s “exposure” data is that it is not based on actual usage, and should therefore be interpreted as a theoretical estimate of the jobs and sectors that could , in theory, be impacted.", "source": "B1", "source_label": "The Budget Lab — Evaluating the Impact of AI on the Labor Market: Current State of Affairs | The Budget Lab", "locus": "'Data Limitations' ¶2", "modality": "self-description" }, "F22": { "kind": "field", "quote": "Unfortunately, comprehensive usage data is not publicly available. The best available data we have is from OpenAI and Anthropic , respectively, that detail the occupations that are most “exposed” to genAI tools (a theoretical, forward-looking metric across all jobs) and that have the highest actual usage of one specific AI tool, Claude (a more narrow, present-focused metric).", "source": "B1", "source_label": "The Budget Lab — Evaluating the Impact of AI on the Labor Market: Current State of Affairs | The Budget Lab", "locus": "'Insights from AI \"Exposure\" and Usage' ¶2", "modality": "documented" }, "F35": { "kind": "field", "quote": "Many analysts—including those at The Budget Lab—utilize Eloundou et al.’s exposure metrics, which measure Generative AI’s (GenAI) ability to speed up work task completion.", "source": "B3", "source_label": "The Budget Lab — Labor Market AI Exposure: What Do We Know? | The Budget Lab", "locus": "¶1", "modality": "documented" }, "F36": { "kind": "field", "quote": "Microsoft researchers Tomlinson et al. (2025) created the ai_applicability_score. … They distinguish their work from other researchers by looking at individual conversations with Microsoft’s Copilot AI.", "source": "B3", "source_label": "The Budget Lab — Labor Market AI Exposure: What Do We Know? | The Budget Lab", "locus": "Appendix, Measures", "modality": "documented" }, "F33": { "kind": "field", "quote": "AI exposure metrics broadly agree with each other, but that they disagree with each other more on highly exposed occupations. The key point of disagreement between different AI exposure metrics is in the magnitude of exposure, not whether an occupation is exposed.", "source": "B3", "source_label": "The Budget Lab — Labor Market AI Exposure: What Do We Know? | The Budget Lab", "locus": "Key Takeaways 1–2", "modality": "documented" }, "F34": { "kind": "field", "quote": "Occupational exposure to AI is not indicative of a jobs AI will automate out of existence. Rather, it indicates places in the labor market where AI could have an impact.", "source": "B3", "source_label": "The Budget Lab — Labor Market AI Exposure: What Do We Know? | The Budget Lab", "locus": "Key Takeaways 3", "modality": "stipulation" }, "F25": { "kind": "field", "quote": "Thus data from Claude usage alone is not representative of how workers across the economy are using AI chatbots and tools.", "source": "B1", "source_label": "The Budget Lab — Evaluating the Impact of AI on the Labor Market: Current State of Affairs | The Budget Lab", "locus": "'Data Limitations' ¶6", "modality": "self-description" }, "F26": { "kind": "field", "quote": "To accurately measure AI’s impact on the labor force, the most important data needed is comprehensive usage data from all the leading AI companies at the individual and enterprise level, including APIs.", "source": "B1", "source_label": "The Budget Lab — Evaluating the Impact of AI on the Labor Market: Current State of Affairs | The Budget Lab", "locus": "'Data Limitations' ¶7", "modality": "interpretation" }, "F8": { "kind": "field", "quote": "Better data is needed to fully understand the impact of AI on the labor market.", "source": "B1", "source_label": "The Budget Lab — Evaluating the Impact of AI on the Labor Market: Current State of Affairs | The Budget Lab", "locus": "Key Takeaways 3", "modality": "self-description" }, "LV-25": { "kind": "archive", "quote": "NOT a usage dataset: it uses usage measures as inputs", "deposit": null, "source_label": "Labor Vector meta-aggregator record: Tracking the Impact of AI on the Labor Market (https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/), editor Lee Sharks, census compiled 2026-10-29, schema 1.0", "record": "https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/", "locus": "census.json rows[slug == 'yale-budget-lab-ai-tracker'].negative_tags[1]", "modality": "interpretation", "date": "2026-10-29" }, "LV-18": { "kind": "archive", "quote": "[\"who supplies, directs or gains from labor performed with AI\", \"effects below the level the CPS can detect\", \"which usage data it draws on, or their provider (unread in the saved text)\"]", "deposit": null, "source_label": "Labor Vector meta-aggregator record: Tracking the Impact of AI on the Labor Market (https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/), editor Lee Sharks, census compiled 2026-10-29, schema 1.0", "record": "https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/", "locus": "census.json rows[slug == 'yale-budget-lab-ai-tracker'].does_not_answer", "modality": "interpretation", "date": "2026-10-29" }, "LV-17": { "kind": "archive", "quote": "[\"whether occupational churn has departed from historical ranges since AI's introduction\", \"whether AI-exposed workers are over-represented among the unemployed\", \"whether AI usage measures track changes in employment or unemployment\"]", "deposit": null, "source_label": "Labor Vector meta-aggregator record: Tracking the Impact of AI on the Labor Market (https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/), editor Lee Sharks, census compiled 2026-10-29, schema 1.0", "record": "https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/", "locus": "census.json rows[slug == 'yale-budget-lab-ai-tracker'].answers", "modality": "interpretation", "date": "2026-10-29" }, "LV-09": { "kind": "archive", "quote": "not recorded; the tracker finds no clear AI-related labor market footprint to date", "deposit": null, "source_label": "Labor Vector meta-aggregator record: Tracking the Impact of AI on the Labor Market (https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/), editor Lee Sharks, census compiled 2026-10-29, schema 1.0", "record": "https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/", "locus": "census.json rows[slug == 'yale-budget-lab-ai-tracker'].direction.gains", "modality": "interpretation", "date": "2026-10-29" }, "LV-28": { "kind": "archive", "quote": "observed: occupational churn and unemployment by exposure, from the CPS", "deposit": null, "source_label": "Labor Vector meta-aggregator record: Tracking the Impact of AI on the Labor Market (https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/), editor Lee Sharks, census compiled 2026-10-29, schema 1.0", "record": "https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/", "locus": "questions.json questions[id == 'observed-or-estimated'].resources[slug == 'yale-budget-lab-ai-tracker'].role", "modality": "interpretation", "date": "2026-10-29" }, "LV-29": { "kind": "archive", "quote": "No record establishes that exposure causes the employment change; the two observed trackers reach different readings of the same period.", "deposit": null, "source_label": "Labor Vector meta-aggregator record: Tracking the Impact of AI on the Labor Market (https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/), editor Lee Sharks, census compiled 2026-10-29, schema 1.0", "record": "https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/", "locus": "questions.json questions[id == 'observed-or-estimated'].gap", "modality": "interpretation", "date": "2026-10-29" }, "LV-30": { "kind": "archive", "quote": "no clear labor-market footprint yet, at the level the CPS can see", "deposit": null, "source_label": "Labor Vector meta-aggregator record: Tracking the Impact of AI on the Labor Market (https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/), editor Lee Sharks, census compiled 2026-10-29, schema 1.0", "record": "https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/", "locus": "questions.json questions[id == 'who-gains'].resources[slug == 'yale-budget-lab-ai-tracker'].role", "modality": "interpretation", "date": "2026-10-29" }, "LV-19": { "kind": "archive", "quote": "none stated", "deposit": null, "source_label": "Labor Vector meta-aggregator record: Tracking the Impact of AI on the Labor Market (https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/), editor Lee Sharks, census compiled 2026-10-29, schema 1.0", "record": "https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/", "locus": "census.json rows[slug == 'yale-budget-lab-ai-tracker'].lv_intersection", "modality": "interpretation", "date": "2026-10-29" }, "O716-01": { "kind": "archive", "quote": "AI economics research focuses primarily on labor displacement (Acemoglu and Restrepo 2019), capability projection (Eloundou et al. 2023), and welfare estimation (Brynjolfsson, Li, and Raymond 2023). These frameworks measure which jobs AI eliminates, what tasks it can perform, and what consumer surplus it generates.", "deposit": 716, "source_label": "#716 Provenance Erasure Rate A Compression-Survival Metric for Attribution Loss in AI-Composed Search Outputs", "record": "https://www.alexanarch.org/s/records/716/", "locus": "§2.2 'Economic Framing of AI Composition', s1–2", "modality": "interpretation", "date": "2026-05-03" }, "O716-03": { "kind": "archive", "quote": "Existing AI-economics research addresses three channels: labor displacement, capability projection, and welfare estimation. PER addresses a fourth: **compositional authority transfer** — the rate at which AI synthesis captures value from human authors by stripping the attribution that would otherwise carry economic weight.", "deposit": 716, "source_label": "#716 Provenance Erasure Rate A Compression-Survival Metric for Attribution Loss in AI-Composed Search Outputs", "record": "https://www.alexanarch.org/s/records/716/", "locus": "§5.1, ¶1", "modality": "stipulation", "date": "2026-05-03" }, "O716-02": { "kind": "archive", "quote": "PER identifies a distinct channel: even when human labor *remains* (the author's work is used), the economic value tied to provenance — reputation, traffic, citation credit, contractual rights — is extracted by the system. This is not displacement; it is extraction without attribution. The author's work is consumed, but the author is erased.", "deposit": 716, "source_label": "#716 Provenance Erasure Rate A Compression-Survival Metric for Attribution Loss in AI-Composed Search Outputs", "record": "https://www.alexanarch.org/s/records/716/", "locus": "§2.2, s3–5", "modality": "interpretation", "date": "2026-05-03" }, "LV-31": { "kind": "archive", "quote": "No record in the census measures the distribution of productivity gains between workers, employers, platforms and model providers.", "deposit": null, "source_label": "Labor Vector meta-aggregator record: Tracking the Impact of AI on the Labor Market (https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/), editor Lee Sharks, census compiled 2026-10-29, schema 1.0", "record": "https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker/", "locus": "questions.json questions[id == 'who-gains'].gap", "modality": "interpretation", "date": "2026-10-29" }, "CAP-1-08": { "kind": "archive", "quote": "A baseline: the record landed on laborvector.org the same day (commit bf90841) and no card cites it.", "deposit": null, "source_label": "Capture Registry (EA-WG-CAPTURES-01), entry yale-budget-lab-ai-labor-market-aio-20261029 (OBS-9c44ea25d2ca, AXN:0AF6.CAPTURE.⛳🌲🌋⏳🔐💜)", "record": "https://www.alexanarch.org/captures/yale-budget-lab-ai-labor-market-aio-20261029/", "locus": "yale-budget-lab-ai-labor-market-aio-20261029, q_kind", "modality": "documented", "date": "2026-10-29" }, "CAP-1-05": { "kind": "archive", "quote": "The innocent reading first. 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Checked 2026-10-29 against the Labor Vector census record of the same day and the sources it saved.", "deposit": null, "source_label": "Capture Registry (EA-WG-CAPTURES-01), entry yale-budget-lab-ai-labor-market-aio-20261029 (OBS-9c44ea25d2ca, AXN:0AF6.CAPTURE.⛳🌲🌋⏳🔐💜)", "record": "https://www.alexanarch.org/captures/yale-budget-lab-ai-labor-market-aio-20261029/", "locus": "yale-budget-lab-ai-labor-market-aio-20261029, findings[0]", "modality": "documented", "date": "2026-10-29" }, "CAP-1-02": { "kind": "archive", "quote": "'NOT YET' FLATTENED. The record's finding is that the analysis 'does not yet clearly indicate an AI-related labor market footprint', and its negative tag keeps that apart from a finding of no effect. The composition's 'finds no clear evidence' and 'no strong, consistent statistical footprint' drop the 'yet'; the Lab's own card ('AI Is Probably Not (Yet) the Reason') keeps it.", "deposit": null, "source_label": "Capture Registry (EA-WG-CAPTURES-01), entry yale-budget-lab-ai-labor-market-aio-20261029 (OBS-9c44ea25d2ca, AXN:0AF6.CAPTURE.⛳🌲🌋⏳🔐💜)", "record": "https://www.alexanarch.org/captures/yale-budget-lab-ai-labor-market-aio-20261029/", "locus": "yale-budget-lab-ai-labor-market-aio-20261029, findings[1]", "modality": "interpretation", "date": "2026-10-29" }, "CAP-1-03": { "kind": "archive", "quote": "BEYOND THE RECORD. 'wage trends' are in no saved source; the 'Capital vs. Labor' line (companies cutting jobs 'for broader macro or capital-investment reasons rather than direct workforce replacement by AI agents') and the 'slight volatility' in high-exposure unemployment rest on the Lab's other pages (cards 3 and 4), which the record did not read.", "deposit": null, "source_label": "Capture Registry (EA-WG-CAPTURES-01), entry yale-budget-lab-ai-labor-market-aio-20261029 (OBS-9c44ea25d2ca, AXN:0AF6.CAPTURE.⛳🌲🌋⏳🔐💜)", "record": "https://www.alexanarch.org/captures/yale-budget-lab-ai-labor-market-aio-20261029/", "locus": "yale-budget-lab-ai-labor-market-aio-20261029, findings[2]", "modality": "interpretation", "date": "2026-10-29" }, "CAP-1-04": { "kind": "archive", "quote": "WHAT THE TRACKER USES, UNSAID. The record notes that the tracker takes AI usage measures as inputs and does not name their providers in the saved text; the composition's 'AI Metrics' section is the Lab's exposure review (card 3).", "deposit": null, "source_label": "Capture Registry (EA-WG-CAPTURES-01), entry yale-budget-lab-ai-labor-market-aio-20261029 (OBS-9c44ea25d2ca, AXN:0AF6.CAPTURE.⛳🌲🌋⏳🔐💜)", "record": "https://www.alexanarch.org/captures/yale-budget-lab-ai-labor-market-aio-20261029/", "locus": "yale-budget-lab-ai-labor-market-aio-20261029, findings[3]", "modality": "interpretation", "date": "2026-10-29" }, "CAP-1-06": { "kind": "archive", "quote": "A tracker whose finding is provisional by its own wording is composed as a settled negative, with a causal line about corporate job cuts added from beside it.", "deposit": null, "source_label": "Capture Registry (EA-WG-CAPTURES-01), entry yale-budget-lab-ai-labor-market-aio-20261029 (OBS-9c44ea25d2ca, AXN:0AF6.CAPTURE.⛳🌲🌋⏳🔐💜)", "record": "https://www.alexanarch.org/captures/yale-budget-lab-ai-labor-market-aio-20261029/", "locus": "yale-budget-lab-ai-labor-market-aio-20261029, analysis s1", "modality": "interpretation", "date": "2026-10-29" }, "CAP-1-07": { "kind": "archive", "quote": "The record's 'yet' is the whole of its claim, and the composition's first sentence is the place it is lost.", "deposit": null, "source_label": "Capture Registry (EA-WG-CAPTURES-01), entry yale-budget-lab-ai-labor-market-aio-20261029 (OBS-9c44ea25d2ca, AXN:0AF6.CAPTURE.⛳🌲🌋⏳🔐💜)", "record": "https://www.alexanarch.org/captures/yale-budget-lab-ai-labor-market-aio-20261029/", "locus": "yale-budget-lab-ai-labor-market-aio-20261029, analysis s2", "modality": "interpretation", "date": "2026-10-29" }, "F55": { "kind": "field", "quote": "HTTP 404. Wikipedia does not have an article with this exact name. … There were no results matching the query.", "source": "B8", "source_label": "Wikipedia — Tracking the Impact of AI on the Labor Market (no article)", "locus": "Wikipedia: six titles; rendered page; article-space search", "modality": "documented" }, "F56": { "kind": "field", "quote": "However, a 2025 study concluded that the US labor market had so far not experienced a discernible disruption from generative AI.", "source": "B8", "source_label": "Wikipedia — Tracking the Impact of AI on the Labor Market (no article)", "locus": "Generative AI, section 'Fears over job losses'", "modality": "attributed" }, "F47": { "kind": "field", "quote": "Yale Budget Lab Executive Director Martha Gimbel on why AI hasn't disrupted ...", "source": "B5", "source_label": "YouTube·Quest Means Business — Yale Budget Lab Executive Director Martha Gimbel on why AI hasn't disrupted ...", "locus": "card title (video; unreachable)", "modality": "attributed" } }, "note": "The knowledge object (KO): the entry as public knowledge, each sentence sourced by the claims it lists. The compression, the field-only arm, the transcript, the delta and the kernel are in the row (links.row), which is the authority." }, "source": "operator, 2026-10-29: 'lets expand the research, implement the same meta aggregator function with pages... then /non entries after i get the captures'; the Labor Vector meta-aggregator entity (laborvector.org/aggregators/yale-budget-lab-ai-tracker/)", "stage": "composed 2026-10-29 under EA-NEGONT-02 v0.9, #1690, equal case, ρ = extends (draft, not frozen; ledgers unaudited, one extractor; checked by the session and the page builder)", "date": "2026-10-29", "status": { "procedure": "EA-NEGONT-02 v0.9, #1690: equal case, ρ = extends, read from the Labor Vector census record, the capture record and the deposit that bears on the tracker's class (#716); archive selected by D/R/O (no D or R candidate: no archive text names the tracker or the Lab; 1 deposit admitted by reading at O-class, 5 class sentences rejected; hop of 29 read and rejected), with the Labor Vector census record (31 claims) and the Capture Registry's findings, reading, analysis and query note (8 claims) ledgered as the archive's records of the entity; the field B by three origins (5 cards, 1 of them unreachable; 2 own pages, 1 unread; Wikipedia, no article); the composer read the ledgers, never the transcript, except where the brief asks for T's claims and the delta", "ledger": "unaudited (§3.8: one extractor per ledger); field quotes 56/56 verified by script against saved text, the census's PDF text, the Wikipedia response summary and raw wikitext or the card title; archive quotes 42/42 verified against the registry, census.json, questions.json and the deposit text", "frozen": false, "breaches": [] }, "addresses": [ { "address": "Yale Budget Lab AI labor market", "address_url": "https://www.alexanarch.org/addresses/yale-budget-lab-ai-labor-market/", "register": [] } ], "counts": { "ko_sentences": 30, "p_words": 349, "field_claims": 56, "archive_claims": 42, "ko_field_claims_cited": 56, "ko_archive_claims_cited": 42, "admitted_deposits": 1, "register_addresses": 0, "traversal": { "D_sentences": 0, "D_deposits": 0, "R_sentences": 0, "R_deposits": 0, "O_direct": 0, "O_class": 1, "O_deposits": 1, "H_candidates": 29 } }, "links": { "record": "https://www.alexanarch.org/non/yale-budget-lab-ai-tracker/", "table_of_contents": "https://www.alexanarch.org/non/index.json", "register": "https://www.alexanarch.org/datasets/negative-of-the-negative/v2/register.json", "row": "https://www.alexanarch.org/datasets/negative-of-the-negative/v2/rows/yale-budget-lab-ai-tracker.json", "archive_ledger": "https://www.alexanarch.org/datasets/negative-of-the-negative/v2/ledgers/yale-budget-lab-ai-tracker/ledger-archive.json", "field_ledger": "https://www.alexanarch.org/datasets/negative-of-the-negative/v2/ledgers/yale-budget-lab-ai-tracker/field.json", "selection": "https://www.alexanarch.org/datasets/negative-of-the-negative/v2/traversal/yale-budget-lab-ai-tracker/", "traversal": "https://www.alexanarch.org/datasets/negative-of-the-negative/v2/traversal/yale-budget-lab-ai-tracker/", "traversal_summary": "https://www.alexanarch.org/datasets/negative-of-the-negative/v2/traversal/yale-budget-lab-ai-tracker/summary.json", "reading": "https://www.alexanarch.org/datasets/negative-of-the-negative/v2/traversal/yale-budget-lab-ai-tracker/reading.json", "configuration": "https://www.alexanarch.org/datasets/negative-of-the-negative/v2/panel/configs/yale-budget-lab-ai-tracker.json", "address_page": "https://www.alexanarch.org/addresses/yale-budget-lab-ai-labor-market/", "labor_record": "https://www.laborvector.org/aggregators/yale-budget-lab-ai-tracker", "dataset": "https://huggingface.co/datasets/leesharks/negative-of-the-negative" }, "row_sha256": "cdb8b1310539997de08fc30d5b4c130bfae02922f48670247b1d64dbaa5e33cb", "record_url": "https://www.alexanarch.org/non/yale-budget-lab-ai-tracker/", "json_url": "https://www.alexanarch.org/non/yale-budget-lab-ai-tracker/entity.json", "spec": "https://www.alexanarch.org/s/records/1690/", "creator": "Lee Sharks", "orcid": "0009-0000-1599-0703", "license": "CC BY 4.0" }