Tutoring the Enemy No. 2 — Wages, Rents and Rights

The second paper of Tutoring the Enemy. It starts from one question: what do you rent out to make a living? In two sessions with a machine, on 9 and 11 November 2026, the author proposed three baskets. Capacity is present labour, and earns a wage. Property is rights to past labour, inherited or saved, and earns a rent. Loyalty is a place in the compact between generations and citizens, and earns redistribution. The author came back to the second session unconvinced by his own first draft, with a working question: how is the labour market of the European Union likely to be affected by an AI disruption, and what options are at hand? The questions and objections are the author's; the figures and studies are presented as the machine's input, and its own estimates are marked as such. The paper opens with what was learned so far. An Automat is any machine an AI can drive. By the machine's estimate, not a measurement, Automats could do about 34 per cent of the paid hours worked in the EU with today's technology in today's workplaces, and up to about 80 per cent with projected technology in workplaces rebuilt for them, leaving out the work people would want to keep. People stay where a human must answer, and where a human is what is bought. What the disruption frees is time, not goods, and free time is leisure only when a claim on output comes with it. A right is a human-made product, so the claims on what Automats make are designed, not given. What is scarce earns extra, and places, time, permission and title stay scarce. Nobody holds a key unchecked. As Automats take more of the execution, more of everyone's income comes from rent and redistribution, both made by authority, and the paper proposes a test for every claim: what would it cost to take it away? A claim that is costly to remove is a right; one that is cheap to remove is a favour. The European Union is the case studied: its claims of loyalty are promised in Europe, while much of the rent on the machines may be collected elsewhere. One disagreement is recorded and left open: the machine argues that people lose a lever when their work is needed less; the author sees nothing new in it. The paper ends with eight open questions and an addendum: the model in symbols (version 0.4), an evidence table graded A to C that says which figures were checked during the sessions, the correction log in both directions, and the version log of both sessions. Every conclusion is temporary, and open to a better one. Terms proposed: Automat and the Automat disruption; the three baskets (capacity, property, loyalty); needed and wanted work; the test of a right against a favour (who coined what is set out in addendum E). Written in part with Claude (Anthropic), an AI model. The ideas, editorial decisions and responsibility for the content are the author's.