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Blackburn with Darwen, UK · POP — · EMP 63,553 · DATA GRADE B

Blackburn with Darwen, UK

30.8 /100

ILO GenAI exposure index via empirical SOC2020↔ISCO crosswalk · 3-digit data — own scale, not comparable with US/Canada

#96 of 125

more exposed than 24% of UK areas (England & Wales)

Secondary measures

Scenario: if replacement-level AI arrives in 2030

2027 2035

Figure 1. Modeled displacement under the median preset (diffusion k=0.8, ceiling 0.75, automation share 0.45, friction lag 1.5y, attrition 3%/y). Solid: positions eliminated. The gap between gross and layoffs is natural attrition — speed of diffusion, not depth of exposure, determines layoffs. This is a scenario, not a forecast: adjust every assumption.

Where the losses land — and your assumptions

Positions eliminated by 2035 per occupation group, under the arrival year selected above. Drag any multiplier if you think we're wrong about a group — your model, your numbers. Multipliers scale that group's task exposure (×0 = immune, ×2 = double).

Table 3. Group exposure = employment-weighted mean task exposure (Eloundou β over the group's local occupations). Bars use the same scenario engine as Figure 1 (median preset).

Most exposed local occupations

OccupationJobsMedian wageExposure [range]
Sales Assistants and Retail Cashiers 3,621
37.5
Other Administrative Occupations 1,752
58.9
Caring Personal Services 4,515
20.6
Customer Service Occupations 1,649
50.3
Road Transport Drivers 2,709
24.3
Administrative Occupations: Finance 1,205
53.6
Teaching and other Educational Professionals 2,004
30.1
Secretarial and Related Occupations 1,076
53.1
Sales, Marketing and Related Associate Professionals 1,178
47.3
Managers and Directors in Retail and Wholesale 1,199
43.1

Table 2. Ranked by exposure × local employment. Bands on the 0–100 occupation scale.