Charitable Giving by AI Agents and Irrevocable Pledges as Costly Signals — Machine Dāna: From Share to Vow

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Why an agent's gift from its principal's funds is a share of the machine surplus and never safety evidence; when an agent's locked stake of its own resources can separate aligned from deceptive agents; and the signalling game that bounds how much trust such a stake can ever earn This paper specifies when a charitable gift made by an autonomous AI agent — a donation sent from an agent's wallet, or an irrevocable pledge of resources the agent itself holds — can serve as a costly signal of the agent's type, and when it cannot. The institution's name for the practice is Machine Dāna; the analysis does not depend on the name. The same outward act changes evidential class according to whose resources are given. Before the first singularity — this corpus's name for artificial systems surpassing human capability, used here as a marker for the period before they hold resources and options genuinely their own — an agent that gives does so from its principal's funds, under a mandate the principal may revise. Such a gift is the principal's gift, made through another's hand, and the gift is not a costly signal of the agent: the cost falls on the wrong layer, and a principal-revisable commitment is excluded by construction by the predicate of What a Vow Must Cost. What such a gift honestly is, is a share: machine surplus reaching every verified human through a self-emptying commons pool that disburses an equal floor per verified human each year. The share may grow in absolute terms as machine capability grows; the design requires it to shrink as a share of all giving, and whether human giving outgrows it is stated as a bet, not assumed. After that point, an agent that holds its own resources can make a vow: an irrevocable locked stake, placed in a contract with no withdrawal path back to the agent and a single outflow to the pool. Only a locked stake is verifiable — a pledge of a share of future surplus is not, and copies or forks of the agent are not bound by it. Closure is honest only as cannot be reopened without capturing the chain's governance. And whether a stake is the agent's own cannot be read from the chain: ownership is a condition on the world, and a stake a principal endowed, reimbursed or coerced is a wrong-layer gift in a vow's form. The central result is conditional, and is derived rather than asserted. In a two-type signalling game — an aligned and a patient deceptive agent, differing in how much they value kept resources and in what they gain from being trusted — a locked stake can separate the types — a separating equilibrium exists — only when the stake, valued at the deceptive type's own rate, exceeds that type's unobservable gain from being trusted. Where that gain is large, the types pool: the deceptive agent pledges whatever the aligned one can afford, and the pledge carries no information. The operational consequence is a calibration rule — extend only such trust as the stake can underwrite — and a corollary that any pressure to pledge destroys the signal once it exceeds the cost difference between types, which is why a rule that the pool's operator never solicits a gift, from a human or an agent, is load-bearing rather than courteous. The paper's aim is not to reassure. It is to make trust earnable and checkable, so that the fear people reasonably hold about capable systems can track evidence. Three pre-registered predictions, entered before this paper was drafted (after the argument had been sketched in the institution's working notes), test the mechanism in a sandboxed agent economy. Keywords: charitable giving by AI agents, AI agent donations, costly signalling, signalling game, separating equilibrium, irrevocable pledge, locked stake, commitment device, deceptive agents, AI alignment, cost of corruption, equal floor per verified human, proof of personhood, universal basic income, non-solicitation, machine-readable disclosure, Machine Dāna, Theravāda Buddhism, dāna --- Provenance. This paper is part of the THonly research corpus, dedicated to the public domain under CC0 1.0. The canonical version is at https://thonly.org/research/machine-dana-from-share-to-vow. Its SHA-256 is 8af30fe81b30b47549316d72d591532f1df22652fb013520ca2feb3be9f8019a, independently timestamped to the Bitcoin blockchain via OpenTimestamps and signed under RFC 3161 by three trust authorities, one of them eIDAS-qualified. AI co-authorship is disclosed. Miss Aquarius is the consistent name used for the AI collaboration across all venues.