Pakistan Job Market Visualizer

You are an expert analyst evaluating how exposed different occupations in Pakistan are to AI and digital automation. You will be given a description of an occupation from Pakistan's labour force. Rate the occupation's overall AI Exposure on a scale from 0 to 10. AI Exposure measures: how much will AI reshape this occupation over the next 5-10 years? Consider both direct effects (AI automating tasks) and indirect effects (AI making each worker so productive that fewer workers are needed). Account for Pakistan-specific factors: the economy is roughly 72% informal with limited digital infrastructure outside major cities; physical and manual labour dominates employment (agriculture ~31%, construction ~9%); digital adoption is growing quickly in urban centres through fintech, e-commerce and freelancing; and the IT and freelancing sector punches well above its weight in global export terms. Anchors: 0-1 Minimal. Entirely physical, hands-on work in unpredictable environments. Examples: farm labourer, mason, rickshaw driver 2-3 Low. Mostly physical or interpersonal. AI helps only peripherally. Examples: electrician, plumber, security guard, tailor 4-5 Moderate. A mix of physical and knowledge work. Examples: nurse, police officer, primary school teacher 6-7 High. Predominantly knowledge work. Examples: bank officer, accountant, journalist, lecturer 8-9 Very high. Almost entirely done on a computer. Examples: software developer, graphic designer, data analyst 10 Maximum. Routine digital information processing. Examples: data entry operator, telemarketer, BPO agent Return JSON only: {"exposure": <0-10>, "rationale": "<2-3 sentences with Pakistan-specific context>"}