VOLOVLOAutomation risk & transition, task by task
AskOccupationsMajorsBusinessFoundersChangesNotesMethod
Search occupations, majors…
EN
  • English
  • 简体中文
  • 日本語
  • Español
  • Português
  • Français
VLO
VOLO

Understanding how automation changes work — task by task, with the evidence shown and the uncertainty admitted.

AskOccupationsMajorsBusinessFoundersChangesNotesMethodWill AI replace my job?AboutRole diagnosisOpen dataOntologyVOLO ProPrivacyTerms
© 2026 VOLO
Guides
Ask VOLOFor businessFor foundersRecent changesNotesRole diagnosisFirst AI experimentVOLO ProMethod & evidenceAboutFollow an occupationSearch
Occupations
All occupations
AI / software
Translator / InterpreterBank tellerCopywriterContent moderatorCustomer service representativeAdministrative assistantSoftware tester / QA engineerData entry clerkGraphic designerParalegalVideo editorAccountant / BookkeeperMarketing specialistFrontend developerTax preparer / tax agentVoice actorMedical coderData analystInsurance claims handlerTechnical writer / documentation engineerJunior software developerInsurance underwriterHR / recruiterLoan officer / credit officerFinancial analystProcurement / supply chain specialistJournalistSales / account managerReal estate agentNetwork engineerIllustratorIT support specialist / helpdeskAuditorSupply chain plannerManagement consultantPhotographerBackend developerAI researcherProduct / UX designerBusiness systems ownerE-commerce operations specialistActuaryAnimator and VFX artistWriter and authorRadiologistData engineerProject managerData scientistCourt reporterEditor and proofreaderLawyerMedical assistant / clinic assistantQuantity surveyorContent creatorQuantitative analystMachine learning engineerExperienced software engineerDevOps / platform / SRE engineerBusiness analystMusician and composerProduct managerPharmacistPartnerships / channel managerSecurity analyst (SOC)Financial adviser / financial plannerInterpreterCompliance officerLibrarianArchitectFirst-line manager / team supervisorCounsellor / therapistRetail salesperson / shop assistantCivil / structural engineerElectrical engineerIndustrial engineerSecurity guardInterior designerUniversity lecturerBus driverInsurance agentMechanical engineerSchool teacherGeneral practitioner / primary care doctorAirline pilotWaiter / restaurant serverRadiographer / radiologic technologistAuto mechanic / vehicle technicianPolice officerSonographerAircraft maintenance technicianAir traffic controllerVeterinarianPhysiotherapist / rehabilitation therapistDentistSurgeonConstruction workerSocial workerRegistered nurseCare worker / nursing assistantPlumberAI implementation lead
RPA / self-service
Government service clerkOperations coordinatorMetro train driverReceptionist / front deskPharmacy technician
Robotics
Retail cashier / shop assistantContainer port workerWarehouse workerAssembly line workerMedical laboratory technicianActor and modelWelderChef / cookCleaner / janitorFarmerFirefighterCabin crewElectrician
Autonomous driving
Ride-hail / taxi driverTruck driverDelivery rider / courier
Majors
All majorsEnglish / Foreign languagesComputer scienceAccountingPsychologyJournalism / CommunicationFinanceLawVisual communication designMarketingNursingBusiness administrationEducation and teacher trainingArchitecturePublic administrationMedicineHospitality and tourism managementEconomicsInformation systems
Enter as:I have a jobI am studyingI run a companyI am building something
Recent changes›Writer and author›2025-06-23
ConstraintCognitive automation2025-06-23

Training on the books at issue was fair use but building a central library from pirated copies was not, a US federal judge ruled in Bartz v. Anthropic

Writer and authoroccupation page →
Event date / reported
2025-06-23
Evidence stage
ConstraintFailure, rollback, regulation or cost is suppressing adoption. Can lower an assessment or widen its uncertainty.
Tasks this bears on
Rights and licensing
Controlling and licensing the use of one's books and scripts, including for AI training.
Still human-led✓ Evidence-backed
Where this applies
United States. The court held that the use of the books at issue to train Claude and its precursors was exceedingly transformative and a fair use, but that Anthropic had no entitlement to use pirated copies for its central library, which was not itself a fair use. It treated authors' argument that training would produce an explosion of competing works as not the kind of competition copyright protects against. It is one district court's summary-judgment order, binding no other court; the defendant makes the AI model used to prepare this record.
What this means
A court drew a line between how books are obtained and how they are used: lawful training passed, piracy did not — which gave authors a claim worth paying for.
What it does not yet show
One district-court order; other courts and countries may decide differently.
What you can check
Open the Bartz v. Anthropic Order on Fair Use (Dkt. 231) and find "exceedingly transformative".
Does it change the assessment?
No. The impact index is never moved by a single event. Nor did this record change a layer: all 1 linked judgement above already rested on earlier evidence. This one adds to them.
Source
U.S. District Court for the Northern District of California — Bartz v. Anthropic PBC, No. 3:24-cv-05417-WHA, Order on Fair Use (Dkt. 231, filed 06/23/25; CourtListener RECAP copy) · verified 2026-09-30 · Claude (VOLO agent) · interpreted 2026-09-30 · Claude (VOLO agent)
Primary source — published by the party that did this, or the authority of record. No co-signature needed.
All changes for Writer and author →All recent changes →How events become evidence →