{"schemaVersion":1,"edition":{"id":"jobs-quality-2026-10-29","authoredAt":"2026-10-29","evidenceReviewedAt":"2026-10-29","scope":"Selected source review, October 2024–October 2026, centered on technical work and selected US employers, with attributed AI capability and investment arguments. Initial authored edition, not a reconstructed EM view from earlier dates. Broad jobs, AGI and bubble entries preserve their scope and expose limits of this slice.","authors":[{"name":"Astra 6","role":"Editorial synthesis author; revised after the independent audit","model":"gpt-6-astra"}],"reviewers":[{"name":"Opus 5.5","role":"Independent audit of earlier working content; findings informed this revision, not approval of revised content","model":"claude-opus-5-5","reviewedAt":"2026-10-29"}]},"projection":"question","selectedQuestionId":"jobs","questions":[{"id":"jobs","text":"AI taking most jobs: evidence for or against it, including automation and displacement, job creation and new occupations, hiring, employment, wages, productivity or how gains and losses are distributed.","displayTitle":"Will AI take most jobs?","topicIds":["work-and-business","job-displacement-and-creation","wages-and-labor-share"],"broader":[],"narrower":[{"id":"ai-and-work","reason":"Examine whether task capability becomes dependable help in real work."},{"id":"ai-entry-and-worker-gains","reason":"Follow who can enter work and share its benefits."}],"related":[{"id":"agi","reason":"Broader capability could change the set of automatable tasks, but is not employment itself."},{"id":"bubble","reason":"Adoption economics connect workplace outcomes to investment returns, without making them equivalent."}],"read":{"gapLabel":"Selected settings; the economy-wide claim remains open","basis":"Amodei argues that sufficiently capable, cheap AI could eventually undermine human economic contribution. The workplace reports here describe narrower task and hiring changes. They do not establish the economy-wide effect; aggregate labor context and independent worker outcomes remain gaps.","alternatives":["Growing output could expand demand for workers; the same tools could reduce hiring in particular roles.","Employment can persist while entry opportunities, wages or bargaining power deteriorate."],"assumptions":["Task substitution, organizational deployment, demand and institutions jointly influence employment; none alone fixes the result."],"revisionTriggers":["Broader outcome evidence separating hiring, exits, wages and task changes across occupations and places.","Credible evidence that apparent labor effects have another explanation."],"estimate":{"status":"not-estimated","reason":"This selected evidence does not justify a probability, date or numerical outcome range for this question."},"sourceRefs":[{"sourceId":"anthropic-workforce-2026","spanIds":["anth-junior"],"role":"context"},{"sourceId":"nyfed-business-survey-2026","spanIds":["nyf-fewer","nyf-more"],"role":"context"},{"sourceId":"amodei-loving-grace-2024","spanIds":["labor-contribution"],"role":"context"}],"positionRefs":["anthropic-workforce-authors","nyfed-survey-authors","amodei-labor-long-run"],"connectionRefs":[],"gapRefs":[{"id":"aggregate-labor-context","reason":"Selected employers cannot establish total hiring, job creation or employment change."}]}}],"navigationQuestions":[{"id":"jobs","text":"AI taking most jobs: evidence for or against it, including automation and displacement, job creation and new occupations, hiring, employment, wages, productivity or how gains and losses are distributed.","displayTitle":"Will AI take most jobs?","topicIds":["work-and-business","job-displacement-and-creation","wages-and-labor-share"],"broader":[],"narrower":[{"id":"ai-and-work","reason":"Examine whether task capability becomes dependable help in real work."},{"id":"ai-entry-and-worker-gains","reason":"Follow who can enter work and share its benefits."}],"related":[{"id":"agi","reason":"Broader capability could change the set of automatable tasks, but is not employment itself."},{"id":"bubble","reason":"Adoption economics connect workplace outcomes to investment returns, without making them equivalent."}]},{"id":"ai-and-work","text":"When does an AI become a dependable colleague?","displayTitle":"When does AI become a dependable colleague?","topicIds":["work-and-business","human-ai-collaboration","reliability-in-deployment"],"broader":[{"id":"jobs","reason":"Dependable assistance may change tasks and labor demand, with different effects across roles."}],"narrower":[{"id":"ai-work-quality-and-rework","reason":"Count the checking and correction needed for acceptable work."},{"id":"ai-delegation-reliability","reason":"Examine what happens when a human stops checking each step."}],"related":[]},{"id":"ai-work-quality-and-rework","text":"Does AI reduce the work needed to produce an acceptable result?","displayTitle":"Does AI reduce the work needed for an acceptable result?","topicIds":["quality-and-rework","human-ai-collaboration","economics-of-adoption"],"broader":[{"id":"ai-and-work","reason":"Checking and correction are part of dependability."}],"narrower":[],"related":[{"id":"ai-delegation-reliability","reason":"Low average rework does not establish safe unsupervised operation."},{"id":"ai-deployment-returns","reason":"Net workflow value is one input to sustainable returns."},{"id":"ai-entry-and-worker-gains","reason":"Review and training work may be redistributed across experience levels."}]},{"id":"ai-entry-and-worker-gains","text":"Who gets an entry point, and who shares the gains?","displayTitle":"Who gets an entry point and shares the gains?","topicIds":["job-displacement-and-creation","worker-bargaining","education-and-learning","wages-and-labor-share"],"broader":[{"id":"jobs","reason":"Track distribution and opportunity alongside total employment."}],"narrower":[],"related":[{"id":"ai-work-quality-and-rework","reason":"Who performs review can affect skill development and the distribution of work."}]},{"id":"agi","text":"AGI within a few years: progress, limits, timelines or forecasts for broadly capable systems, including disagreement.","displayTitle":"Is AGI a few years away?","topicIds":["ai-capabilities-and-limits","long-horizon-planning"],"broader":[],"narrower":[{"id":"ai-delegation-reliability","reason":"Test one practical dependency without substituting it for the whole AGI question."}],"related":[{"id":"jobs","reason":"Capability does not determine deployment, demand or employment on its own."}]},{"id":"ai-delegation-reliability","text":"When can work be delegated without checking every step?","displayTitle":"When can work be delegated without checking every step?","topicIds":["reliability-in-deployment","long-horizon-planning","ai-capabilities-and-limits--evaluation-and-reliability"],"broader":[{"id":"agi","reason":"Reliability is one relevant condition, not a sufficient definition of general intelligence."},{"id":"ai-and-work","reason":"A dependable colleague can also be a supervised collaborator."}],"narrower":[],"related":[{"id":"ai-work-quality-and-rework","reason":"Inspect the cost of detecting and correcting failures."}]},{"id":"bubble","text":"An AI bubble: financing, valuations, capital expenditure, compute investment, revenues, demand or sustainable returns.","displayTitle":"Is there an AI bubble?","topicIds":["finance-and-the-economy","economics-of-adoption"],"broader":[],"narrower":[{"id":"ai-deployment-returns","reason":"Begin with value to a deploying organization, then identify the additional evidence needed for investor returns."}],"related":[{"id":"jobs","reason":"Employment effects and investment outcomes can move differently."}]},{"id":"ai-deployment-returns","text":"When does a useful AI deployment become worth its total cost?","displayTitle":"When is an AI deployment worth its total cost?","topicIds":["economics-of-adoption","work-and-business--adoption-and-deployment","finance-and-the-economy"],"broader":[{"id":"bubble","reason":"Customer value is one dependency; supplier margins, capital cost and valuation need separate evidence."}],"narrower":[],"related":[{"id":"ai-work-quality-and-rework","reason":"Review and correction can affect total cost and value."},{"id":"jobs","reason":"A positive deployment return does not specify whether employment expands or contracts."}]}],"sources":[{"id":"anthropic-workforce-2026","title":"How employment is changing at Anthropic","url":"https://www.anthropic.com/research/employment-at-anthropic","publishedAt":"2026-10-16","dateBasis":"Publisher publication date, checked on original page.","access":{"status":"public-page","note":"Original publisher page and exact retained source reviewed. Source retention does not establish every downstream reuse or training right.","checkedAt":"2026-10-29"},"provenance":{"kind":"stream-snapshot","workId":"18f3c3ca31491462a8ab52f797ebadd2a7087803317e69a5152e2a0c4cfbed65","snapshotId":"a633ce13b2d661ad9c008ac99d3357f15a80c4bcd91009290d11712c2f565793","textHash":"8ea3533aa08b1f63c143b0a383911da93e88f464edd2d8e61edebf2a97a42232","reason":"Exact retained Stream work/snapshot and SHA256 verified against the 29 October SELECT-only source packet. That lookup found no joined public Stream or bridge reading revision; no reading identity is invented."},"spans":[{"id":"anth-junior","text":"The proportion of junior technical hires fell even faster, from 27% to 9%.","locator":"Retained extracted text, character offsets [4420, 4494). Context (EM paraphrase): Anthropic’s October 2026 report describes its own workforce; junior employees’ share fell from early 2025, and technical hiring still grew in absolute terms. This is a changing hiring mix, not a count of jobs lost."}],"readingRefs":[]},{"id":"nyfed-business-survey-2026","title":"Businesses Are Using AI to Transform Work, Not Cut Jobs","url":"https://libertystreeteconomics.newyorkfed.org/2026/09/businesses-are-using-ai-to-transform-work-not-cut-jobs/","publishedAt":"2026-09-01","dateBasis":"Publisher publication date, checked on original page.","access":{"status":"public-page","note":"Original publisher page and exact retained source reviewed. Source retention does not establish every downstream reuse or training right.","checkedAt":"2026-10-29"},"provenance":{"kind":"stream-snapshot","workId":"c16ff26252860625027590ed41b03b3773be9d5b324475687ef0304e51a73af8","snapshotId":"d59dc274ed0f66564545055ec05e4a9abf5a5314f05623d021bbe3ac1b2274ab","textHash":"7ec36434625838d3aa01b2819ecb8d90e622fd2f2e8a664dd2c656116c4829dd","reason":"Exact retained Stream work/snapshot and SHA256 verified against the 29 October SELECT-only source packet. That lookup found no joined public Stream or bridge reading revision; no reading identity is invented."},"spans":[{"id":"nyf-fewer","text":"hired fewer workers","locator":"Retained extracted text, character offsets [4475, 4494). Context (EM paraphrase): August 2026 regional survey: about 15% of AI-using service firms reported hiring fewer workers than they would otherwise have because of AI. This is employers’ stated counterfactual, not independently identified job loss. The paired figure for hiring more is about 13%; firm percentages cannot be subtracted into a net job count."},{"id":"nyf-more","text":"About 13 percent of service firms said they had hired more workers due to AI","locator":"Retained extracted text, character offsets [4776, 4852). Context (EM paraphrase): August 2026 regional business survey, reporting workforce adjustments over the preceding six months. The workforce charts concern AI-using firms in the survey; they are not national employment totals. Authors also report retraining as a common response."}],"readingRefs":[]},{"id":"amodei-loving-grace-2024","title":"Machines of Loving Grace","url":"https://darioamodei.com/essay/machines-of-loving-grace","publishedAt":"2024-10","dateBasis":"October 2024 is printed in the retained essay. The work metadata has no publication timestamp; month precision is preserved.","access":{"status":"retained-public-essay","note":"Original personal essay retained in Stream and reviewed here; not an institutional position or a new 2026 statement. Public availability does not establish every reuse right.","checkedAt":"2026-10-29"},"provenance":{"kind":"stream-snapshot","workId":"6aa2c807bdcb81da04a30b6cf0b1c0620353219816ab224111920bdc8c02bc32","snapshotId":"07fedfacf7c11b925e82d6c8a319ee710df91c8b7160fae3d7ca3fda1da6af45","textHash":"d8f37e4a35c07240bca22712dece7667d41c3e3efb9f28b7ca62c4c5f807442a","reason":"Exact original Stream identity and SHA256 verified against the retained source packet."},"spans":[{"id":"labor-contribution","text":"most or all humans may not be able to contribute meaningfully","locator":"Retained extracted text, character offsets [75299, 75360). Context (EM paraphrase): In the essay’s long-run economic discussion, Amodei considers sufficiently capable and cheap AI displacing the basis of human economic contribution. He first allows comparative advantage and new complementary jobs to preserve employment. No job-loss date or measured proportion is supplied."}],"readingRefs":[]}],"positions":[{"id":"anthropic-workforce-authors","speaker":"Nathan Wilmers, Regina Catipon, Maxim Massenkoff and Peter McCrory","role":"Anthropic Institute researchers reporting on their employer","statement":"The authors report a falling junior share of technical hires and propose that intensive AI adoption at Anthropic may offer an early indication of wider workplace change.","conditions":["One rapidly growing AI company; technical hiring still grew in absolute terms.","Reported internal patterns and the authors’ interpretation do not identify an economy-wide causal effect."],"sourceRefs":[{"sourceId":"anthropic-workforce-2026","spanIds":["anth-junior"],"role":"supports"}],"statedAt":"2026-10-16","dateBasis":"Dated authored publication; this is not the date of every underlying observation or interview.","attribution":"direct"},{"id":"nyfed-survey-authors","speaker":"Jaison R. Abel, Richard Deitz, Natalia Emanuel and Nick Montalbano","role":"New York Fed research staff; article expresses their views","statement":"The authors interpret their regional business surveys as showing more worker augmentation than replacement so far, while explicitly allowing this to change as adoption matures.","conditions":["August 2026 regional business survey, not a national census.","Workforce changes are employer reports; the relevant charts describe firms using AI."],"sourceRefs":[{"sourceId":"nyfed-business-survey-2026","spanIds":["nyf-fewer","nyf-more"],"role":"supports"}],"statedAt":"2026-09-01","dateBasis":"Dated authored publication; this is not the date of every underlying observation or interview.","attribution":"direct"},{"id":"amodei-labor-long-run","speaker":"Dario Amodei","role":"Anthropic chief executive writing a personal essay","statement":"He allows human comparative advantage and complementary jobs to persist initially, but expects sufficiently capable and cheap AI eventually to undermine the present basis of human economic contribution.","conditions":["Conditional long-run argument, not measured job loss or a dated prediction that most jobs disappear.","The essay treats economic arrangements and distribution as choices needing further debate."],"sourceRefs":[{"sourceId":"amodei-loving-grace-2024","spanIds":["labor-contribution"],"role":"supports"}],"statedAt":"2024-10","dateBasis":"Month printed in the essay; no job-loss horizon is stated.","attribution":"direct"}],"paths":[{"id":"jobs-complements-persist","questionId":"jobs","outcome":"Tasks change while substantial human work persists","scope":"EM conditional scenario, not an estimated probability or a claim that this outcome has occurred.","conditions":["Human contributions, demand growth or new tasks complement automation.","Deployment remains constrained by costs, reliability or institutions."],"sourceRefs":[{"sourceId":"amodei-loving-grace-2024","spanIds":["labor-contribution"],"role":"context"},{"sourceId":"nyfed-business-survey-2026","spanIds":["nyf-fewer","nyf-more"],"role":"context"}],"positionRefs":["amodei-labor-long-run","nyfed-survey-authors"]},{"id":"jobs-substitution-expands","questionId":"jobs","outcome":"Substitution spreads beyond particular tasks and occupations","scope":"EM conditional scenario, not an estimated probability or a claim that this outcome has occurred.","conditions":["Capability and cost improve enough for widespread deployment.","New tasks, demand or institutions do not offset the reduced labor demand."],"sourceRefs":[{"sourceId":"amodei-loving-grace-2024","spanIds":["labor-contribution"],"role":"context"},{"sourceId":"anthropic-workforce-2026","spanIds":["anth-junior"],"role":"context"}],"positionRefs":["amodei-labor-long-run"]}],"connections":[],"changes":[],"questionVersions":{"jobs":"26f53ad614af16d8ca4318678a785c1e312cdee7f628e4124d2d31e04b79d014"},"availableEditions":[{"id":"jobs-quality-2026-10-29","authoredAt":"2026-10-29","evidenceReviewedAt":"2026-10-29","scope":"Selected source review, October 2024–October 2026, centered on technical work and selected US employers, with attributed AI capability and investment arguments. Initial authored edition, not a reconstructed EM view from earlier dates. Broad jobs, AGI and bubble entries preserve their scope and expose limits of this slice.","authors":[{"name":"Astra 6","role":"Editorial synthesis author; revised after the independent audit","model":"gpt-6-astra"}],"reviewers":[{"name":"Opus 5.5","role":"Independent audit of earlier working content; findings informed this revision, not approval of revised content","model":"claude-opus-5-5","reviewedAt":"2026-10-29"}]}]}