{"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":"ai-entry-and-worker-gains","questions":[{"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."}],"read":{"gapLabel":"Aggregate employment can hide different experiences","basis":"A shrinking junior hiring share at one company and regional reports of both reduced and increased hiring raise different questions from total job counts. Workers’ own experience and distributional outcomes remain thin in this edition; a proposal for stronger worker voice is included as a proposal.","alternatives":["Company growth and changing business functions can alter hiring composition without AI being the sole cause.","Skills learned through supervised AI work might create different entry routes; that benefit is not established here."],"assumptions":["Access to training, ownership and bargaining can shape how similar technical changes affect different people."],"revisionTriggers":["Worker accounts and hiring, pay, progression or training outcomes that test these mechanisms."],"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":"steering-beyond-automation","spanIds":["un-voice"],"role":"context"}],"positionRefs":["unger-narayanan-collaboration"],"connectionRefs":[],"gapRefs":[{"id":"entry-progression-and-distribution","reason":"One company and regional employers do not settle entry opportunities or distribution."}]}}],"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":"steering-beyond-automation","title":"Steering AI Beyond Automation","url":"https://www.normaltech.ai/p/steering-ai-beyond-automation","publishedAt":"2026-10-14","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":"5a4e1d4b2fb65d2a40b74bca91665b9dc8321e961ea8e51dea6a078d98139bff","snapshotId":"11ae3a79455a2c294b795984f741f4bb1a3df2cbe7f39d2e0867564a93f6a8a2","textHash":"f2b6cc0e1c8b6bbfe0e9efb6e94a5614b87630de3934d9902943551c31faf389","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":"un-voice","text":"Giving workers more of a voice in bargaining over AI deployment is another way to steer toward augmentation without mandating it.","locator":"Retained extracted text, character offsets [32549, 32678). Context (EM paraphrase): Retained extracted text, character offsets [32549, 32678); verify against the cited snapshot, not current HTML offsets."}],"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":"unger-narayanan-collaboration","speaker":"Gabriel Unger and Arvind Narayanan","role":"Authors of a research agenda and argument about AI development","statement":"They argue for deliberately developing collaborative AI and for workers having a stronger voice in deployment choices.","conditions":["This is a proposed direction and mechanism, not an observed estimate of its effects.","Agreement with their preferred outcome does not establish feasibility or labor-market results."],"sourceRefs":[{"sourceId":"steering-beyond-automation","spanIds":["un-voice"],"role":"supports"}],"statedAt":"2026-10-14","dateBasis":"Dated authored publication; this is not the date of every underlying observation or interview.","attribution":"direct"}],"paths":[{"id":"entry-routes-narrow","questionId":"ai-entry-and-worker-gains","outcome":"Some entry routes narrow while output grows","scope":"EM conditional scenario, not an estimated probability or a claim that this outcome has occurred.","conditions":["Implementation tasks previously used to train juniors are automated or reassigned.","Alternative training and entry routes fail to offset lost opportunities."],"sourceRefs":[{"sourceId":"anthropic-workforce-2026","spanIds":["anth-junior"],"role":"context"},{"sourceId":"nyfed-business-survey-2026","spanIds":["nyf-fewer","nyf-more"],"role":"context"}],"positionRefs":["anthropic-workforce-authors"]},{"id":"entry-opportunities-renew","questionId":"ai-entry-and-worker-gains","outcome":"New learning and entry routes share the gains","scope":"EM conditional scenario, not an estimated probability or a claim that this outcome has occurred.","conditions":["Tools and institutions help less-experienced people do valuable work.","Employers create opportunities and workers can influence deployment."],"sourceRefs":[{"sourceId":"steering-beyond-automation","spanIds":["un-voice"],"role":"context"},{"sourceId":"anthropic-workforce-2026","spanIds":["anth-junior"],"role":"challenges"}],"positionRefs":["unger-narayanan-collaboration"]}],"connections":[],"changes":[],"questionVersions":{"ai-entry-and-worker-gains":"581795fc087f7a47ad5fee65e683f359001374bf0f62f47d1fcc07fb211d984b"},"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"}]}]}