AI and Public Finance · Türkiye Most of the debate about AI and labor markets is a debate about workers. Almost none of it is about the entity standing quietly behind every payroll. Moving from employment-share exposure to labor-tax-revenue exposure changes which occupations matter — and which policies do. Results draw on ongoing joint work with Dhushyanth Raju applying the Richmond (2026) AI transition framework to Türkiye's 2024 Household Labour Force Survey Most of the debate about AI and labor markets is a debate about workers: who gets displaced, who gets augmented, who gets retrained. Almost none of it is about the entity standing quietly behind every payroll: the treasury. Governments in most middle- and high-income countries raise roughly half of their revenue from labor — personal income tax plus social security contributions. If AI-driven capital deepening shifts factor income from labor toward capital, that base erodes at precisely the ...
Beyond Exposure AI and Labor Markets · Türkiye Occupational exposure to AI identifies where technology may affect work, but not whether employment will contract, reorganize, or expand. Applying the Richmond (2026) AI Jobs Transition Framework to Türkiye's 2024 Household Labour Force Survey, the dominant high-exposure archetype is not automation. It is reorganization. Mpumelelo Nxumalo and Dhushyanth Raju · Summary of the working paper Beyond Exposure: AI and Labor Market Reorganization in Türkiye Most discussion of AI and jobs runs on a single number: how much of an occupation's task content a model can perform. That number identifies where technology reaches. It does not say what happens next. An exposed occupation may shed workers, or it may keep them while the work itself is rebuilt around the technology. Those are different outcomes, they call for different policy, and exposure alone cannot tell them apart. Applying the Richmond (202...