{ "schemaVersion": 1, "namespace": "appstore2031/storefront/v2", "editionId": "2031-2026-08-02", "candidateId": "category-002-candidate-01", "canonicalCandidateSha256": "c4a48799bb3b533229e1f29ef2cdec657323bccb2d266a1aa8a74a516b046df4", "fictionalDisclosure": true, "fiction": { "name": "ShiftWitness", "developerName": "Wholework Cooperative", "iconAsset": "/storefront/v2/icons/category-002-candidate-01.svg", "iconTheme": { "motif": "A distinct geometric mark derived from the fictional name.", "palette": "High-contrast spectral gradient.", "shapeLanguage": "Rounded app-store tile with a clear lettermark.", "accessibilityNote": "The name remains visible beside the icon; colour is not the only identifier." }, "storeDescription": "ShiftWitness is a fictional outside trial for organisations thinking about giving a supervised machine a complete job. Its testers copy the real site, hide ordinary and difficult cases inside a full shift, and count every time a person steps in. The resulting proof packet shows finished work, delays, damage, repair time, worker rescue and the exact version tested. The result expires when the machine, workplace or rescue plan materially changes.", "rating": 4.7, "ratingLabel": "imagined 2031 rating", "reviews": [ { "reviewerAlias": "NightShiftKai", "title": "Our rescue work finally counted", "body": "The supplier called the pilot autonomous. ShiftWitness showed that our team rescued it 26 times and made those hours visible in the buying decision.", "stars": 5, "stance": "benefit", "fictionalDisclosure": true }, { "reviewerAlias": "SmallPlantSam", "title": "Strong report, heavy process", "body": "The findings were clear, but preparing the site took longer than expected and the fee would be difficult for a very small operator.", "stars": 3, "stance": "critical", "fictionalDisclosure": true } ] }, "category": { "id": "category-002", "name": "Independent Proof That Work Really Finishes", "plainLanguageDefinition": "Forecast services that test bold machine and service claims in the real places where they must work. They expose hidden human rescue, broken hand-offs, delayed harm, physical damage and failed recovery, then produce evidence that buyers and affected people can challenge.", "recurringBrowsePurpose": "A buyer, safety body, assurance lab, standards body, regulator, insurer, worker body, outside researcher or affected group that needs evidence stronger than fluent output or supplier-run checks.", "completion": { "trigger": "A consequential capability or service claim lacks fresh outside evidence from a setting, time period and affected group that match the intended use.", "boundedWork": "Run independently chosen hard-case trials, observe complete work and human rescue, record the domain's exposure, uptime, energy, harm and recovery fields, repeat checks for lasting effects, publish methods, costs and limits, and support retesting when the service or setting changes.", "observableDone": "The caller receives a reproducible packet covering completion, intervention, damage, recovery, excluded settings, baseline and follow-up results, test cost and a dated retest rule. It shows when regional conditions match and names any failed claim, responsible operator and correction route." } }, "rank": { "mainChartPosition": 2, "rangeAcrossWeights": [ 1, 5 ], "dominantWorldIds": [ "W01" ], "whyAboveNext": "It ranks above Handback because buyers can use its evidence before every major deployment, while full interruption drills are likely to be less frequent and more expensive.", "whyThisPosition": "It ranks second because the need could be enormous and the service is easy to understand: independently watch the whole shift and report what truly finished. Delivery is plausible with testing teams, protected worker records and stable version identifiers. It misses first place because it extends familiar field testing, while RelayFault addresses the newer problem of responsibility moving across an entire chain of machine providers.", "couldMoveUpIf": "It could take first place if insurers, worker bodies and public buyers all require expiring full-shift proof for consequential machine systems.", "couldMoveDownIf": "It would fall if machine systems remain narrow assistants or ordinary sector certification adds rescue and recovery fields quickly and cheaply.", "strongestCounterCase": "Sector certification firms and buyer-run acceptance teams already know the workplace, so they could add full-shift, rescue and repair measures without creating a new independent app service.", "publishedChartAppearances": [ { "chart": "main", "rank": 2, "worldId": null, "geographicLensId": null, "weightSetId": null }, { "chart": "conditional", "rank": 1, "worldId": "W01", "geographicLensId": "united-states", "weightSetId": null }, { "chart": "conditional", "rank": 5, "worldId": "W04", "geographicLensId": "united-states", "weightSetId": null }, { "chart": "conditional", "rank": 3, "worldId": "W06", "geographicLensId": "united-states", "weightSetId": null }, { "chart": "conditional", "rank": 1, "worldId": "W01", "geographicLensId": "mainland-china", "weightSetId": null }, { "chart": "conditional", "rank": 5, "worldId": "W04", "geographicLensId": "mainland-china", "weightSetId": null }, { "chart": "conditional", "rank": 3, "worldId": "W06", "geographicLensId": "mainland-china", "weightSetId": null }, { "chart": "conditional", "rank": 1, "worldId": "W01", "geographicLensId": "european-union", "weightSetId": null }, { "chart": "conditional", "rank": 5, "worldId": "W04", "geographicLensId": "european-union", "weightSetId": null }, { "chart": "conditional", "rank": 3, "worldId": "W06", "geographicLensId": "european-union", "weightSetId": null }, { "chart": "conditional", "rank": 1, "worldId": "W01", "geographicLensId": "india", "weightSetId": null }, { "chart": "conditional", "rank": 5, "worldId": "W04", "geographicLensId": "india", "weightSetId": null }, { "chart": "conditional", "rank": 3, "worldId": "W06", "geographicLensId": "india", "weightSetId": null }, { "chart": "conditional", "rank": 1, "worldId": "W01", "geographicLensId": "japan-and-republic-of-korea", "weightSetId": null }, { "chart": "conditional", "rank": 5, "worldId": "W04", "geographicLensId": "japan-and-republic-of-korea", "weightSetId": null }, { "chart": "conditional", "rank": 3, "worldId": "W06", "geographicLensId": "japan-and-republic-of-korea", "weightSetId": null }, { "chart": "conditional", "rank": 1, "worldId": "W01", "geographicLensId": "gulf-technology-economies", "weightSetId": null }, { "chart": "conditional", "rank": 5, "worldId": "W04", "geographicLensId": "gulf-technology-economies", "weightSetId": null }, { "chart": "conditional", "rank": 3, "worldId": "W06", "geographicLensId": "gulf-technology-economies", "weightSetId": null }, { "chart": "conditional", "rank": 1, "worldId": "W01", "geographicLensId": "latin-america", "weightSetId": null }, { "chart": "conditional", "rank": 5, "worldId": "W04", "geographicLensId": "latin-america", "weightSetId": null }, { "chart": "conditional", "rank": 3, "worldId": "W06", "geographicLensId": "latin-america", "weightSetId": null }, { "chart": "conditional", "rank": 1, "worldId": "W01", "geographicLensId": "africa", "weightSetId": null }, { "chart": "conditional", "rank": 5, "worldId": "W04", "geographicLensId": "africa", "weightSetId": null }, { "chart": "conditional", "rank": 3, "worldId": "W06", "geographicLensId": "africa", "weightSetId": null }, { "chart": "conditional", "rank": 1, "worldId": "W01", "geographicLensId": "other-material-paths", "weightSetId": null }, { "chart": "conditional", "rank": 5, "worldId": "W04", "geographicLensId": "other-material-paths", "weightSetId": null }, { "chart": "conditional", "rank": 3, "worldId": "W06", "geographicLensId": "other-material-paths", "weightSetId": null } ] }, "salesPromise": "See whether a machine can finish the whole shift, including every rescue, delay and repair.", "whatItDoes": { "headline": "Full-Shift Completion Trial", "summary": "It watches a current machine system do a complete real-world shift instead of judging a short demo. Workers, buyers and insurers receive the same dated report, including the work humans quietly had to rescue and the situations the test did not cover.", "steps": [ "An independent operator maps the claimed job, local equipment, affected people and acceptable stopping points.", "The operator runs hidden routine and hard cases through a complete shift while recording every human rescue, delay, damage and repair.", "The operator repeats failed and repaired cases, compares them with the human baseline and issues a version-linked result with an expiry date." ], "outcome": "The caller receives a reproducible proof packet showing completed work, rescue labour, damage, repair time, exclusions, cost and the next retest date." }, "whyOnTheList": { "headline": "Supervised work needs proof of the whole job, not confidence in a demo.", "summary": "If supervised machine work becomes ordinary by 2031, a fluent demonstration will say very little about a complete day involving local equipment, unusual cases and people under pressure. ShiftWitness turns full-job completion into an observable buying decision. It could be used repeatedly because software, staff, tools and local conditions change, making yesterday's proof unsafe to reuse without checking.", "why2031Not2026": "Acceptance tests exist now, but they are often short, shaped by suppliers and weakly linked to later releases. This service forecasts a world where machines carry enough of an entire job that version-linked proof, paid rescue accounting and automatic expiry become normal requirements in buying, insurance and worker agreements.", "worldShifts": [ { "shift": "In W01, machine use is common across bounded work, so the dangerous gap is between a fluent step and a reliably finished job in one real setting.", "causalChain": [ "Widespread supervised use makes full-job claims ordinary purchasing inputs.", "Local equipment, rare cases and human rescue make supplier demonstrations poor guides to actual completion.", "A site-matched outside trial turns those hidden differences into a dated accept, limit or stop decision." ], "basis": "measured-trend", "evidenceIds": [ "src-metr-long-tasks-2025", "src-international-ai-safety-report-2026" ], "worldIds": [ "W01" ], "evidenceLimit": "The sources support present conditions and directional pressures. This 2031 world, product, name and rank are reasoned forecast artefacts." } ], "whyRepeatedUse": "Versions, equipment, staffing and local conditions change, so proof must expire and be run again after a material change." }, "futureDistance": { "cutoffBaseline": "In 2026, organisations can run acceptance tests, but evidence is usually short, supplier-shaped and weakly linked to later versions and full-shift rescue.", "structuralDifference2031": "The service treats a machine-mediated shift as a changing operational object whose proof expires when the release, site or rescue system changes.", "essential2031Conditions": [ "Supervised machine systems routinely span enough of a full job that version-linked completion and rescue evidence becomes a normal buying requirement." ], "notJustBetterAI": "Its core value comes from independent whole-job observation, worker rescue accounting and expiring site evidence, not a more capable model.", "failureCondition": "If supervised systems remain narrow tools that do not carry material responsibility across complete jobs, ordinary acceptance testing is enough and this candidate fails." }, "howItCouldBeBuilt": { "overview": "A testing operator combines a site model, concealed case library, tamper-evident event record and paid human-rescue log into one bounded trial service.", "components": [ { "name": "Shift case pack", "plainLanguageRole": "Defines ordinary work, difficult cases and the human baseline without revealing every test to the supplier." }, { "name": "Rescue and repair recorder", "plainLanguageRole": "Records who intervened, what damage occurred and how long recovery took." } ], "dependencies": [ { "kind": "institutional", "name": "Lawful version-linked test access", "plainLanguageRole": "Lets the outside operator test the same release and controls that the buyer will use.", "causalRequirement": "Procurement and assurance agreements can require test access and a stable release identifier.", "necessity": "essential", "basis": "design-inference", "evidenceIds": [], "worldIds": [ "W01" ], "ifMissing": "The service must label the result unverified and cannot issue a completion claim." } ], "hardestPart": "Keeping tests independent, affordable and representative while still protecting people and legitimate security details.", "whatCouldBeSimpler": "A witnessed buyer-run acceptance test." }, "harmsAndFailure": { "whoBenefits": [ "Exposes incomplete work and unpaid rescue before broad deployment", "Gives buyers a comparable account of repair and limits" ], "warnings": [ "Workers whose intervention is recorded", "Small suppliers and buyers facing test costs", "People represented poorly by the case pack" ], "waysItCouldFail": [ "Surveillance of workers", "False confidence outside the tested site", "Disclosure of personal or security-sensitive information" ], "abuseRisks": [ "A buyer uses a narrow pass as permission for every setting", "A supplier rehearses leaked hard cases", "Managers punish workers who report rescue" ], "safeguards": [ "Minimise and separate worker identity data", "Publish exclusions and a non-transfer warning", "Rotate cases and protect reporters from retaliation" ], "whenItMustStop": "Pause the trial on unsafe physical behaviour, uncontained data exposure or pressure to hide an intervention." }, "rankExplanation": { "whyThisRank": "It ranks second because the need could be enormous and the service is easy to understand: independently watch the whole shift and report what truly finished. Delivery is plausible with testing teams, protected worker records and stable version identifiers. It misses first place because it extends familiar field testing, while RelayFault addresses the newer problem of responsibility moving across an entire chain of machine providers.", "sourceWhyAboveNext": "It ranks above Handback because buyers can use its evidence before every major deployment, while full interruption drills are likely to be less frequent and more expensive.", "plainEnglishWhyAboveNext": "It ranks above Handback because buyers can use its evidence before every major deployment, while full interruption drills are likely to be less frequent and more expensive.", "couldMoveUpIf": "It could take first place if insurers, worker bodies and public buyers all require expiring full-shift proof for consequential machine systems.", "couldMoveDownIf": "It would fall if machine systems remain narrow assistants or ordinary sector certification adds rescue and recovery fields quickly and cheaply.", "basis": "design-inference", "evidenceIds": [ "src-metr-long-tasks-2025", "src-international-ai-safety-report-2026", "SC-R01", "SC-R02", "SC-R05", "SC-R06", "SC-R03", "SC-R04", "SC-R21", "SC-R22", "SC-R18", "SC-R19", "src-asean-ai-governance-guide-2024", "src-un-sids-digital-foundations" ], "worldIds": [ "W01" ], "evidenceLimit": "The score and rank are authored judgements over sealed concepts, not measurements of future adoption." }, "grounding": { "scores": { "futureDistance": 5, "needScale": 5, "globalBreadth": 4, "marketplaceClarity": 5, "deliveryReadiness2031": 5, "trustAndSafety": 4, "total": 95 }, "evidenceAnchors": [ { "statement": "The bound evidence reports limited dependable machine-task horizons and uneven transfer, which supports testing complete work rather than assuming that a strong demonstration generalises.", "basis": "measured-trend", "evidenceIds": [ "src-metr-long-tasks-2025", "src-international-ai-safety-report-2026" ], "worldIds": [ "W01" ] } ], "regionalVariation": [ { "geographyId": "united-states", "fit": "conditional", "explanation": "Fit depends on state rules, worker protection and access to human fallback; the bound regional evidence is adjacent rather than a validation of this service.", "evidenceIds": [ "SC-R01", "SC-R02" ] }, { "geographyId": "mainland-china", "fit": "conditional", "explanation": "Identity linkage and outcome transparency shape lawful testing, but independent correction and comparable completion evidence remain unresolved.", "evidenceIds": [ "SC-R05", "SC-R06" ] }, { "geographyId": "european-union", "fit": "conditional", "explanation": "Rights, portability and human alternatives support careful proof, while enforcement and cross-border transfer still need local design.", "evidenceIds": [ "SC-R03", "SC-R04" ] }, { "geographyId": "india", "fit": "unknown", "explanation": "The packet does not establish region-specific evidence that this form of full-shift trial predicts completion and recovery.", "evidenceIds": [] }, { "geographyId": "japan-and-republic-of-korea", "fit": "unknown", "explanation": "The packet does not establish local transfer, worker-governance or recovery evidence for this service.", "evidenceIds": [] }, { "geographyId": "gulf-technology-economies", "fit": "unknown", "explanation": "The packet does not establish how migrant-worker protections and independent access would operate across these economies.", "evidenceIds": [] }, { "geographyId": "latin-america", "fit": "conditional", "explanation": "Country-specific safety and community rights matter, but the listed material does not validate the proposed trial.", "evidenceIds": [ "SC-R21", "SC-R22" ] }, { "geographyId": "africa", "fit": "conditional", "explanation": "National capability, cost and repair access will shape fit; the evidence is adjacent and not a completion-trial result.", "evidenceIds": [ "SC-R18", "SC-R19" ] }, { "geographyId": "other-material-paths", "fit": "conditional", "explanation": "Local norms, connectivity, safe exit and human fallback require separate test packs rather than a copied global result.", "evidenceIds": [ "src-asean-ai-governance-guide-2024", "src-un-sids-digital-foundations" ] } ], "scenarioFit": [ { "worldId": "W01", "fit": "strong", "reason": "Routine supervised machine work makes independent, version-linked proof of complete jobs a recurring decision input." } ], "resolutionCriteria": [ "At least two independent operators reproduce the same pass or fail classification on matched cases.", "Every report includes rescue, damage, recovery, exclusions, cost and an exact retest date.", "A material version or site change reliably expires the old result before reuse." ] }, "evidenceLimitations": "Observed and published evidence grounds the world pressures and present constraints. The category, product, developer, reviews, rating and exact rank are fictional forecasts and may be wrong.", "datedCollisionAudit": { "cutoff": "2026-08-02", "auditedAt": "2026-08-03T23:59:59.000Z", "verdict": "future-dependent-no-collision-found", "publicReason": "no-material-collision-found. This is a search-engine snapshot, not a trademark search, company-register search, domain search, app-store clearance or legal opinion. Search indexing and regional coverage are incomplete, and a no-material-collision-found verdict means only that this bounded search did not surface a material exact-name use. It does not establish availability or clearance.", "closestMatches": [] }, "evidenceReferences": [ { "kind": "source", "id": "src-metr-long-tasks-2025", "title": "Measuring AI Ability to Complete Long Tasks", "publisher": "Model Evaluation and Threat Research", "url": "https://metr.org/blog/2025-03-19-measuring-ai-ability-to-complete-long-tasks/", "publishedAt": "2025-03-19", "accessedAt": "2026-08-02", "limitations": "The task set is weighted toward software and research work. A historical doubling trend does not guarantee continuation or transfer to 30-day, multi-stakeholder assignments.", "evidenceClass": "measured-trend", "geographies": [ "global" ] }, { "kind": "source", "id": "src-international-ai-safety-report-2026", "title": "International AI Safety Report 2026", "publisher": "International AI Safety Report", "url": "https://internationalaisafetyreport.org/publication/international-ai-safety-report-2026", "publishedAt": "2026-02-03", "accessedAt": "2026-08-02", "limitations": "The report synthesises evidence available through December 2025, so later capability claims require separate checks. Trend continuation and risk scenarios are not forecasts, and benchmark progress may not transfer to messy real work.", "evidenceClass": "measured-trend", "geographies": [ "global" ] }, { "kind": "source", "id": "SC-R01", "title": "Our Epidemic of Loneliness and Isolation", "publisher": "United States Department of Health and Human Services, Office of the Surgeon General", "url": "https://www.hhs.gov/sites/default/files/surgeon-general-social-connection-advisory.pdf", "publishedAt": "2023-05-02", "accessedAt": "2026-08-02", "limitations": "Many reported health relationships are observational associations; United States evidence is not globally representative.", "evidenceClass": "measured-trend", "geographies": [ "United States" ] }, { "kind": "source", "id": "SC-R02", "title": "Families and living arrangements: 2022 data", "publisher": "United States Census Bureau", "url": "https://www.census.gov/newsroom/press-releases/2024/families-living-arrangements.html", "publishedAt": "2024-05-30", "accessedAt": "2026-08-02", "limitations": "Household composition is not a measure of loneliness, relationship quality or voluntary solitude.", "evidenceClass": "measured-trend", "geographies": [ "United States" ] }, { "kind": "source", "id": "SC-R05", "title": "Communique on Major Data of the 1% National Population Sample Survey in 2025", "publisher": "National Bureau of Statistics of China", "url": "https://www.stats.gov.cn/english/PressRelease/202605/t20260522_1963789.html", "publishedAt": "2026-05-22", "accessedAt": "2026-08-02", "limitations": "Demographic, household and migration indicators do not directly measure loneliness, belonging or relationship quality.", "evidenceClass": "measured-trend", "geographies": [ "China" ] }, { "kind": "source", "id": "SC-R06", "title": "China targets wider mutual-aid eldercare coverage by 2030", "publisher": "State Council of the People's Republic of China", "url": "https://english.www.gov.cn/news/202604/29/content_WS69f1abd1c6d00ca5f9a0ab18.html", "publishedAt": "2026-04-29", "accessedAt": "2026-08-02", "limitations": "A target is not proof of implementation, equitable access, service quality or social-connection outcomes.", "evidenceClass": "policy-intent", "geographies": [ "China" ] }, { "kind": "source", "id": "SC-R03", "title": "EU Loneliness Survey", "publisher": "European Commission Joint Research Centre", "url": "https://joint-research-centre.ec.europa.eu/projects-and-activities/survey-methods-and-analysis-centre/loneliness/eu-loneliness-survey_en", "publishedAt": "undated-at-access", "accessedAt": "2026-08-02", "limitations": "Online 2022 survey; response and sampling differences limit exact comparisons between countries.", "evidenceClass": "measured-trend", "geographies": [ "European Union member states surveyed in 2022" ] }, { "kind": "source", "id": "SC-R04", "title": "Household composition statistics", "publisher": "Eurostat", "url": "https://ec.europa.eu/eurostat/statistics-explained/SEPDF/cache/29071.pdf", "publishedAt": "undated-at-access", "accessedAt": "2026-08-02", "limitations": "Household form does not measure loneliness or belonging; member-state patterns vary.", "evidenceClass": "measured-trend", "geographies": [ "European Union" ] }, { "kind": "source", "id": "SC-R21", "title": "The care society: acting today for a better future", "publisher": "United Nations Economic Commission for Latin America and the Caribbean", "url": "https://www.cepal.org/en/articles/2024-care-society-acting-today-better-future", "publishedAt": "2024-10-29", "accessedAt": "2026-08-02", "limitations": "Regional aggregates conceal country and subnational variation; care pressure is not a direct loneliness measure.", "evidenceClass": "policy-intent", "geographies": [ "Latin America and the Caribbean" ] }, { "kind": "source", "id": "SC-R22", "title": "Mental health", "publisher": "Pan American Health Organization", "url": "https://www.paho.org/en/topics/mental-health", "publishedAt": "2026-08-02", "accessedAt": "2026-08-02", "limitations": "Regional treatment-gap and spending summaries are not current service-capacity estimates for each country.", "evidenceClass": "measured-trend", "geographies": [ "Latin America and the Caribbean; Americas where stated" ] }, { "kind": "source", "id": "SC-R18", "title": "Urgent action needed to accelerate mental health progress in African region", "publisher": "World Health Organization Regional Office for Africa", "url": "https://www.afro.who.int/news/urgent-action-needed-accelerate-mental-health-progress-african-region", "publishedAt": "2024-10-10", "accessedAt": "2026-08-02", "limitations": "Regional averages hide large country differences; service inputs do not prove access, quality or outcomes.", "evidenceClass": "measured-trend", "geographies": [ "WHO African Region" ] }, { "kind": "source", "id": "SC-R19", "title": "Ageing in Africa", "publisher": "United Nations Department of Economic and Social Affairs", "url": "https://www.un.org/development/desa/en/news/population/ageing-in-africa.html", "publishedAt": "2016-05-04", "accessedAt": "2026-08-02", "limitations": "Older source and projection; Africa is highly heterogeneous and remains younger than other world regions.", "evidenceClass": "modelled-projection", "geographies": [ "Africa" ] }, { "kind": "source", "id": "src-asean-ai-governance-guide-2024", "title": "ASEAN Guide on AI Governance and Ethics", "publisher": "Association of Southeast Asian Nations", "url": "https://asean.org/wp-content/uploads/2024/02/ASEAN-Guide-on-AI-Governance-and-Ethics_beautified_201223_v2.pdf", "publishedAt": "2024-02-02", "accessedAt": "2026-08-02", "limitations": "The guide is voluntary and focuses on responsible adoption rather than frontier capability. ASEAN member states differ greatly in infrastructure, regulation, income, and implementation capacity.", "evidenceClass": "policy-intent", "geographies": [ "other" ] }, { "kind": "source", "id": "src-un-sids-digital-foundations", "title": "Small Island Developing States", "publisher": "United Nations Department of Economic and Social Affairs", "url": "https://sdgs.un.org/topics/small-island-developing-states", "publishedAt": "undated-at-access", "accessedAt": "2026-08-02", "limitations": "The official topic page did not expose a single reliable publication date; it was accessed on 2026-08-02. It establishes structural constraints and agreed priorities, not a specific AI adoption path.", "evidenceClass": "policy-intent", "geographies": [ "other" ] } ], "rankingIndexPath": "rankings/category-002/index.json", "sourceReceipts": [] }