Corporate tax systems were designed for an era when revenue growth closely tracked job creation. Policies like the Chicago Corporate Head Tax show how labor-based taxation can unintentionally discourage hiring by increasing costs as firms add workers. This page is a personal research sandbox where I’m playing with a concept, using the Equitable Automation Tax (EAT) as a thought experiment, using Google Gemini, to explore how taxation might adapt as AI changes how revenue is generated, with the explicit goal of encouraging job creation rather than punishing it.
Equitable Automation Tax (EAT)
Transitioning from Labor-Based to Value-Added AI Taxation
Policy Rationale
As AI efficiency increases, revenue decouples from headcount. EAT shifts the tax burden from hiring people to leveraging algorithms.