{ "version": "V5-roadmap", "generated_at": "2026-03-21T16:09:31.003Z", "current_live_version": "V5", "prerequisite_release": "V4.3", "status": "promoted_live", "summary": "V5 is now the live structural release. The retained V4.3 baseline, sidecars, and promotion-comparison artifacts remain published for auditability while the next work shifts to V5.x calibration.", "v43_handoff": { "experimental_status": "promoted", "experimental_summary": "The V4.3 shadow model was first promoted into the live structural release and is now retained as the immediate pre-V5 baseline. The shadow artifacts remain published for auditability against the earlier V4.2 baseline.", "headline_promotion_ready": true, "task_native_count": 485, "band_flip_count": 111, "impact_flip_count": 47, "validation_result": "2/3" }, "release_thesis": "V5 should be the first release that upgrades the science beyond exposure alone: augmentation heterogeneity, empirical mobility, richer uncertainty, and a clearer realized-risk forecast.", "formula_family": { "effective_coverage": "Σ_t w_it · exposure_t · success_t", "automation_pressure": "Σ_t w_it · exposure_t · success_t · autonomy_t · (1 - bottleneck_t)", "augmentation_upside": "Σ_t w_it · exposure_t · success_t · (1 - autonomy_t) · bottleneck_t", "realized_risk_proxy": "structural_risk_i · adoption_t · capability_t · κ_short" }, "sidecar_status": { "augmentation_heterogeneity": { "status": "pilot_sidecar", "artifact": "v5-augmentation-heterogeneity.json" }, "empirical_mobility": { "status": "enriched_sidecar", "artifact": "v5-empirical-mobility.json" }, "posterior_uncertainty": { "status": "pilot_sidecar", "artifact": "v5-posterior-uncertainty.json" }, "realized_risk_forecast": { "status": "pilot_sidecar", "artifact": "v5-realized-risk.json" } }, "experimental_model_status": { "status": "promoted_live", "model_artifact": "v5-experimental-model.json", "validation_artifact": "v5-experimental-validation.json", "structural_validation_result": "2/2", "realized_validation_result": "3/4", "comparison_baseline_version": "V4.3", "transition_band_flip_count": 135, "impact_flip_count": 242 }, "workstreams": [ { "key": "augmentation_heterogeneity", "label": "Augmentation heterogeneity", "goal": "Replace one universal augmentation rule with workflow-sensitive priors informed by empirical productivity studies.", "research": [ { "key": "brynjolfsson_li_raymond_2023", "title": "Generative AI at Work", "url": "https://www.nber.org/papers/w31161", "year": 2023 }, { "key": "dellacqua_etal_2025", "title": "Navigating the Jagged Technological Frontier", "url": "https://www.nber.org/papers/w33641", "year": 2025 }, { "key": "dillon_etal_2025", "title": "AI, Productivity, and Work Quality", "url": "https://www.nber.org/papers/w33795", "year": 2025 } ], "deliverables": [ "Role/archetype-level augmentation priors", "Updated task-to-augmentation mapping", "Validation note on which occupations move most" ] }, { "key": "empirical_mobility", "label": "Empirical mobility transitions", "goal": "Move transition support from broad heuristic rankings toward observed occupational pathways and wage/training tradeoffs.", "research": [ { "key": "imf_occupational_mobility_2024", "title": "Exposure to Artificial Intelligence and Occupational Mobility: A Cross-country Analysis", "url": "https://www.imf.org/en/publications/wp/issues/2024/06/07/exposure-to-artificial-intelligence-and-occupational-mobility-a-cross-country-analysis-549989", "year": 2024 } ], "deliverables": [ "Occupation-to-occupation transition prior", "Observed wage delta and training duration fields", "Transition ranking override when empirical evidence exists" ] }, { "key": "posterior_uncertainty", "label": "Posterior uncertainty", "goal": "Upgrade bootstrap intervals into a latent measurement model across the exposure sources and propagate uncertainty through the final score.", "research": [ { "key": "coyle_poquiz_2025", "title": "Making AI Count: The Next Measurement Frontier", "url": "https://www.nber.org/papers/w34330", "year": 2025 }, { "key": "anthropic_economic_index_2026", "title": "Anthropic Economic Index: New building blocks for understanding AI use", "url": "https://www.anthropic.com/economic-futures/", "year": 2026 } ], "deliverables": [ "Latent exposure posterior", "80/95% intervals on exposure and net risk", "Separation of statistical uncertainty from provenance confidence" ] }, { "key": "realized_risk_forecast", "label": "Realized-risk forecast", "goal": "Calibrate short-run realized effects separately from structural overlap using adoption and capability evidence.", "research": [ { "key": "bick_blandin_deming_2025", "title": "The Rapid Adoption of Generative AI", "url": "https://www.nber.org/papers/w32966", "year": 2025 }, { "key": "humlum_vestergaard_2025", "title": "Large Language Models, Small Labor Market Effects", "url": "https://www.nber.org/papers/w33777", "year": 2025 }, { "key": "metr_time_horizons_2026", "title": "Task-Completion Time Horizons of Frontier AI Models", "url": "https://metr.org/time-horizons/", "year": 2026 }, { "key": "anthropic_labor_market_impacts_2026", "title": "Labor market impacts of AI: A new measure and early evidence", "url": "https://www.anthropic.com/research/labor-market-impacts", "year": 2026 } ], "deliverables": [ "Adoption and capability scalars grounded in literature", "Realized-risk proxy distinct from structural and near-term risk", "Validation family for short-run labour signals" ] } ], "promotion_gates": [ "Retain the V4.3 baseline snapshot and the V5 promotion-comparison artifacts so future iterations stay auditable.", "Validation families must map cleanly to the construct they are testing: structural, transition, augmentation, or realized risk.", "Future V5.x changes should promote only after they beat the retained V5 baseline on the relevant validation family." ] }