HUMANITYVECTOR

Objective, 0.5x by 2040, World

Halve global under-5 mortality by 2040

What would have to happen for the world's under-5 mortality rate to fall by half by 2040?

PaceBehind the required pace2.7x recentsnapshot 2026-09-07 22:37 UTC

Current level

37.4deaths per 1,000 live birthsObserved

2024

Target level in 2040

18.7deaths per 1,000 live birthsDerived

2040

Current level times 0.5.

Required annual addition

-1.17deaths per 1,000 live births per yearDerived

2024 to 2040

(target minus current) divided by 16 years. A straight line, not a plan.

Recent pace, trailing 5-year average change

-0.44deaths per 1,000 live births per yearDerived

2019 to 2024

(2024 level minus 2019 level) divided by 5.

Forecast pace, Forecast Lab 5-year horizon

unavailableModeled

This metric is not a Forecast Lab target.

Required pace minus recent pace

-0.7287deaths per 1,000 live births per yearDerived

Positive means the objective needs a faster pace than the trailing five years delivered.

Required pace minus forecast pace

unavailableModeled

This metric is not a Forecast Lab target.

Target metric Under-5 mortality rate, entity Human health and longevity, base year 2024, 16 years to go.

Same engine, same stored rows, no AI

Explore a different target

Backward walk over requires_input, depends_on and constrains edges, depth 4, 13 constraints

Dependency tree

Objective on the left, what it needs to the right

Halve global under-5 mortality by 2040: dependency walk from human-healthhuman-health affects economic-output: Mechanism supportedhuman-health enables electricity-system: Hypothesizedeconomic-output affects ai-compute: Candidateeconomic-output enables capital-investment: Hypothesizedelectricity-system requires input power-grid: Established relationai-compute requires input ai-accelerator: Established relationai-compute requires input data-center: Established relationpower-grid requires input power-transformer: Established relationai-accelerator requires input high-bandwidth-memory: Established relationai-accelerator requires input semiconductor-fab: Established relationpower-transformer requires input copper: Established relationpower-transformer requires input aluminum: Established relationpower-transformer requires input electrical-steel: Established relationHuman health andlongevityEconomic outputElectricity systemAI computeCapital investmentTransmission anddistribution gridAI acceleratorData centerPower transformerHigh bandwidth memorySemiconductorfabrication plantRefined copperPrimary aluminumGrain-orientedelectrical steel
  • Candidate
  • Hypothesized
  • Mechanism supported
  • Causally supported
  • Established relation
depth 1 Economic outputentity

Mechanism supportedaffectsstrength 0.5confidence 0.8relationshipwhy Economic output

Higher output per person funds nutrition, sanitation, clinics, vaccines and education, and the relation between income and life expectancy across countries and time (the Preston curve) is one of the most documented in demography. The curve shifts upward over time, so part of the gain in longevity comes from knowledge and public health rather than income, and the effect flattens at high income.

Input coefficient
hypothesized dependence, no stored coefficient
Bottleneck status
no bottleneck row stored
Lead time
no cited lead time
Substitutes
none stored on this edge
Response under way
no pipeline or pulse maps to this entity
Also needed by
no other stored dependent
depth 2 AI computetechnology

Candidateaffectsconfidence 0.3relationshipwhy AI compute

Proposed: productivity effects of AI compute on output. No mechanism reviewed and no evidence attached.

Input coefficient
hypothesized dependence, no stored coefficient
Bottleneck status
no bottleneck row stored
Lead time
no cited lead time
Substitutes
none stored on this edge
Response under way
AI Infrastructure Pulse: 0.7014 fraction (2026-07-03) Derived

8 companies contributed to the stored pulse.

Also needed by
no other stored dependent
depth 3 AI acceleratorproduct

Established relationrequires inputstrength 1confidence 0.99relationshipwhy AI accelerator

Training and serving large models runs on accelerators. Compute capacity is the number of accelerators installed times their throughput.

Input coefficient
hypothesized dependence, no stored coefficient
Bottleneck status
no bottleneck row stored
Lead time
no cited lead time
Substitutes
none stored on this edge
Response under way
Semiconductor Capacity Pulse: 0.0553 fraction (2026-07-03) Derived

10 companies contributed to the stored pulse.

Also needed by
no other stored dependent
depth 4 High bandwidth memoryproduct

Established relationrequires inputstrength 0.9confidence 0.95relationshipwhy High bandwidth memory

Current accelerators are packaged with stacks of high bandwidth memory beside the logic die to feed it at the bandwidth large models need; the JEDEC standard defines that interface.

Input coefficient
hypothesized dependence, no stored coefficient
Bottleneck status
no bottleneck row stored
Lead time
no cited lead time
Substitutes
none stored on this edge
Response under way
Semiconductor Capacity Pulse: 0.0553 fraction (2026-07-03) Derived

10 companies contributed to the stored pulse.

Also needed by
no other stored dependent
depth 4 Semiconductor fabrication plantfacility36 to 60 months

Established relationrequires inputstrength 1confidence 0.99relationshipwhy Semiconductor fabrication plant

The logic die is manufactured on leading-edge process nodes in a small number of fabs.

Input coefficient
hypothesized dependence, no stored coefficient
Bottleneck status
no bottleneck row stored
Lead time
36 to 60 months (A new 300 mm fab from groundbreaking through tool installation and qualification to volume output.) Congressional Research Service Recommended

A modern fab typically requires three to five years from groundbreaking to volume production.

Substitutes
none stored on this edge
Response under way
Semiconductor Capacity Pulse: 0.0553 fraction (2026-07-03) Derived

10 companies contributed to the stored pulse.

Also needed by
no other stored dependent
depth 3 Data centerfacility

Established relationrequires inputstrength 1confidence 0.99relationshipwhy Data center

Accelerators run in racks that need power, cooling and network at data-center scale.

Input coefficient
hypothesized dependence, no stored coefficient
Bottleneck status
no bottleneck row stored
Lead time
no cited lead time
Substitutes
none stored on this edge
Response under way
AI Infrastructure Pulse: 0.7014 fraction (2026-07-03) Derived

8 companies contributed to the stored pulse.

Also needed by
no other stored dependent
depth 2 Capital investmententity

Hypothesizedenablesconfidence 0.6relationshipwhy Capital investment

Stated, not yet evidenced here: the share of output reinvested in buildings, machines and infrastructure raises the capital stock and, with a lag, output per person (the accumulation term in growth accounting). Investment also responds to expected growth, so the direction runs both ways.

Input coefficient
hypothesized dependence, no stored coefficient
Bottleneck status
no bottleneck row stored
Lead time
no cited lead time
Substitutes
none stored on this edge
Response under way
no pipeline or pulse maps to this entity
Also needed by
no other stored dependent
depth 1 Electricity systeminfrastructure system

Hypothesizedenablesconfidence 0.6relationshipwhy Electricity system

Stated, not yet evidenced here: electricity access allows refrigeration of vaccines and food, lighting in clinics, water pumping and a shift away from solid cooking fuels, all of which bear on mortality. The catalog carries both series; no study is attached.

Input coefficient
hypothesized dependence, no stored coefficient
Bottleneck status
no bottleneck row stored
Lead time
no cited lead time
Substitutes
none stored on this edge
Response under way
no pipeline or pulse maps to this entity
Also needed by
no other stored dependent
depth 2 Transmission and distribution gridinfrastructure system84 to 180 months

Established relationrequires inputstrength 1confidence 0.99relationshipwhy Transmission and distribution grid

Electricity is generated in one place and used in another. Delivering it to homes and industry physically requires transmission lines, substations and distribution networks; access statistics count connections to that network.

Input coefficient
hypothesized dependence, no stored coefficient
Bottleneck status
no bottleneck row stored
Lead time
84 to 180 months (Interstate transmission projects from initiation through permitting and construction.) U.S. Department of Energy, Grid Deployment Office Recommended

New transmission takes on average around 10 years to complete, with some projects requiring 15 years or more; permits alone average more than four years.

Substitutes
none stored on this edge
Response under way
Grid Investment Pulse: 0.3521 fraction (2025-12-31) Derived

9 companies contributed to the stored pulse.

Also needed by
no other stored dependent
depth 3 Power transformerproduct24 to 60 months

Established relationrequires inputstrength 1confidence 0.99relationshipwhy Power transformer

Power is transmitted at high voltage to limit losses and stepped down for distribution. Every generator connection, substation and distribution feeder passes through transformers, so grid expansion and interconnection queues move with transformer supply and lead times.

Input coefficient
hypothesized dependence, no stored coefficient
Bottleneck status
no bottleneck row stored
Lead time
24 to 60 months (Delivery of a large power transformer from order, at current order books; a new transformer plant takes longer.) U.S. Department of Energy Recommended

Lead times for large power transformers can reach as much as 60 months; the NIAC report of June 2024 puts current lead times at roughly two to four years.

Substitutes
none stored on this edge
Response under way
Grid Investment Pulse: 0.3521 fraction (2025-12-31) Derived

9 companies contributed to the stored pulse.

Also needed by
no other stored dependent
depth 4 Refined coppercommodity120 to 240 monthsbottleneck row

Established relationrequires inputstrength 0.8confidence 0.95relationshipwhy Refined copper

Transformer windings are conductors carrying the full load current. Copper is the standard winding material for its conductivity and mechanical strength; aluminum windings are used in many distribution transformers at a larger cross-section.

Input coefficient
hypothesized dependence, no stored coefficient
Bottleneck status
Copper: insufficient data, severity 85.48 (2026-07-01) Recommended
Lead time
120 to 240 months (expansion lead time, bottlenecks table) Humanity Vector Recommended
Substitutes
  • Primary aluminum: Aluminum windings, larger cross-section for the same current; common in distribution transformers.
Response under way
Heavy Industry Pulse: no value stored Derived

No pulse stored yet (corporate.recompute_pulses has not run, or no facts are stored).

depth 4 Primary aluminumcommodity

Established relationrequires inputstrength 0.4confidence 0.9relationshipwhy Primary aluminum

Aluminum is the alternative winding conductor and is used in tank and structural parts; it is lighter and cheaper per unit of conductance but needs more volume.

Input coefficient
hypothesized dependence, no stored coefficient
Bottleneck status
no bottleneck row stored
Lead time
no cited lead time
Substitutes
Response under way
Heavy Industry Pulse: no value stored Derived

No pulse stored yet (corporate.recompute_pulses has not run, or no facts are stored).

Also needed by
no other stored dependent
depth 4 Grain-oriented electrical steelmaterial

Established relationrequires inputstrength 0.9confidence 0.95relationshipwhy Grain-oriented electrical steel

Transformer cores are stacked laminations of grain-oriented electrical steel chosen for low core loss. Amorphous alloy cores are a partial alternative in distribution units; there is no drop-in core material for large power transformers.

Input coefficient
hypothesized dependence, no stored coefficient
Bottleneck status
no bottleneck row stored
Lead time
no cited lead time
Substitutes
none stored on this edge
Response under way
Heavy Industry Pulse: no value stored Derived

No pulse stored yet (corporate.recompute_pulses has not run, or no facts are stored).

Also needed by
no other stored dependent

Arithmetic on stored values; ranges follow the inputs

Required additions

QuantityValueClassBasis
Required annual addition

(target minus current) divided by 16 years. A straight line, not a plan.

-1.17 deaths per 1,000 live births per yearDerivedobs:122450
Economic output needed per yearnot estimatedhypothesized dependencerel:ef836ac2-ad79-462a-b05e-e42c1b566e1c
Electricity system needed per yearnot estimatedhypothesized dependencerel:f913d900-026e-4232-b9aa-a617096de9f8
AI compute needed per yearnot estimatedhypothesized dependencerel:812f2c15-fcfa-420c-b874-302b1bf79647
Capital investment needed per yearnot estimatedhypothesized dependencerel:54279c4f-2a73-4737-8f09-a66c8a6b2bdb
Transmission and distribution grid needed per yearnot estimatedhypothesized dependencerel:5148efdc-e97b-4641-a51f-cf6e681c89d5
AI accelerator needed per yearnot estimatedhypothesized dependencerel:08f70642-c436-4e33-adc2-2680aa46efe1
Data center needed per yearnot estimatedhypothesized dependencerel:24d7b94a-cd57-4c73-8cc8-524f588ee6b4
Power transformer needed per yearnot estimatedhypothesized dependencerel:0f9233ff-917a-41b9-bf03-ffb05c829ced
High bandwidth memory needed per yearnot estimatedhypothesized dependencerel:7456677a-bd22-4daf-9258-a2e3a5f6ab74
Semiconductor fabrication plant needed per yearnot estimatedhypothesized dependencerel:521b668e-efb1-4c6f-8d93-8db729546bd8
Refined copper needed per yearnot estimatedhypothesized dependencerel:57478abe-2355-4de1-8b4d-be19c58b7045
Primary aluminum needed per yearnot estimatedhypothesized dependencerel:aa5d07e3-221c-4748-b5bc-d3b871fcb961
Grain-oriented electrical steel needed per yearnot estimatedhypothesized dependencerel:361814d4-9451-4107-b575-92a3073b6956

Capacity pipeline and corporate pulses that map to the walk

Current pipeline and responses

Only where a coefficient and a sourced unit cost both exist

Capital

Not estimated: no coefficient plus unit cost pair is stored for this objective.

Downstream systems that compete for the same inputs; the engine does not rank them

Tradeoffs

  • Refined copper depth 4

    Also needed by Residential construction (requires input). Pursuing this objective draws on an input those systems also need; which should have it is a choice this site does not make.

What is unavailable, hypothesized or modeled

Uncertainty

  • Forecast pace: This metric is not a Forecast Lab target.
  • Economic output: hypothesized dependence, no stored coefficient, so no quantity of it is computed.
  • Electricity system: hypothesized dependence, no stored coefficient, so no quantity of it is computed.
  • AI compute: hypothesized dependence, no stored coefficient, so no quantity of it is computed.
  • Capital investment: hypothesized dependence, no stored coefficient, so no quantity of it is computed.
  • Transmission and distribution grid: hypothesized dependence, no stored coefficient, so no quantity of it is computed.
  • AI accelerator: hypothesized dependence, no stored coefficient, so no quantity of it is computed.
  • Data center: hypothesized dependence, no stored coefficient, so no quantity of it is computed.
  • Power transformer: hypothesized dependence, no stored coefficient, so no quantity of it is computed.
  • High bandwidth memory: hypothesized dependence, no stored coefficient, so no quantity of it is computed.
  • Semiconductor fabrication plant: hypothesized dependence, no stored coefficient, so no quantity of it is computed.
  • Refined copper: hypothesized dependence, no stored coefficient, so no quantity of it is computed.
  • Primary aluminum: hypothesized dependence, no stored coefficient, so no quantity of it is computed.
  • Grain-oriented electrical steel: hypothesized dependence, no stored coefficient, so no quantity of it is computed.
  • Capital not estimated for Economic output, Electricity system, AI compute, Capital investment, Transmission and distribution grid, AI accelerator, Data center, Power transformer, High bandwidth memory, Semiconductor fabrication plant, Refined copper, Primary aluminum, Grain-oriented electrical steel: no coefficient plus unit cost pair is stored for them.

Stated, versioned, and shown before the numbers are trusted

Assumptions

  • Base year 2024: the required pace divides the whole gap evenly over 16 years.
  • The constraint walk follows requires_input, depends_on and constrains edges to depth 4; an entity reached twice is listed once at its shortest depth. Anything the curated graph does not store is not listed.
  • No requires_input, depends_on or constrains edge leaves the target entity, so the walk was widened to the weaker enables, affects, consumes, supplied_by, causes_supported and mitigates edges; each still shows its own status badge.
  • Lead times are order-to-delivery or discovery-to-production ranges from the cited documents; they do not include financing or permitting unless the source says so.

AI-written from the numbers above, grok-4.3, prompt 1.0.0, validated against the packet

Narrative

The objective asks for a level of 18.7 deaths per 1,000 live births in 2040 [q:target] from the observed 37.4 deaths per 1,000 live births in 2024 [q:current]. The required annual addition is -1.16875 deaths per 1,000 live births per year [q:required]. The recent pace is -0.44000000000000056 deaths per 1,000 live births per year [q:recent]. The data are consistent with the recent pace being slower than required [q:gap_recent].

Deepest lead times first: [rel:57478abe-2355-4de1-8b4d-be19c58b7045] lead time 120 to 240 months, substitutes Primary aluminum, competes for refined copper with Residential construction. [rel:5148efdc-e97b-4641-a51f-cf6e681c89d5] lead time 84 to 180 months. [rel:521b668e-efb1-4c6f-8d93-8db729546bd8] lead time 36 to 60 months. [rel:0f9233ff-917a-41b9-bf03-ffb05c829ced] lead time 24 to 60 months. [rel:ef836ac2-ad79-462a-b05e-e42c1b566e1c] depth 1 Economic output affects. [rel:f913d900-026e-4232-b9aa-a617096de9f8] depth 1 Electricity system enables hypothesized. [rel:812f2c15-fcfa-420c-b874-302b1bf79647] depth 2 AI compute affects candidate. [rel:54279c4f-2a73-4737-8f09-a66c8a6b2bdb] depth 2 Capital investment enables hypothesized. [rel:08f70642-c436-4e33-adc2-2680aa46efe1] depth 3 AI accelerator requires input. [rel:24d7b94a-cd57-4c73-8cc8-524f588ee6b4] depth 3 Data center requires input. [rel:7456677a-bd22-4daf-9258-a2e3a5f6ab74] depth 4 High bandwidth memory requires input. [rel:aa5d07e3-221c-4748-b5bc-d3b871fcb961] depth 4 Primary aluminum requires input. [rel:361814d4-9451-4107-b575-92a3073b6956] depth 4 Grain-oriented electrical steel requires input.

Forecast pace unavailable [q:forecast] because this metric is not a Forecast Lab target. Some relations are hypothesized or candidate. Lead times appear as ranges in the stored relations. [q:response:3] unavailable because no pulse stored yet.

ai run 758a79e4-1c31-41ac-9b9a-a74064d8e574, 2026-09-07 22:37 UTC. The model restates computed values and cites packet ids; it adds no figure and makes no recommendation.

Version objectives_v1, as of 2026-09-07. 23 stored ids cited. The objective was selected by a reader; the engine evaluates it and shows what competes with it, and does not decide that it should be pursued.