Token Taxes: mitigating AGI's economic risks

Lucas Irwin, Tung-Yu Wu, Fazl Barez

Track: Track 2: Socio-Economical and Future Visions

Keywords: robot taxes, economic risks, post-AGI economy, resource curse, global inequality

TL;DR: In this paper, we argue that the economic risks posed by a post-AGI world can be effectively mitigated by token taxes: usage-based surcharges on model inference applied at the point of sale.

Abstract:

The development of AGI threatens to erode government tax bases, lower living
standards, and disempower citizens—risks that make the 40-year stagnation of
wages during the first industrial revolution look mild in comparison. While AI
safety research has focused primarily on capability risks, comparatively little work
has studied how to mitigate the economic risks of AGI. In this paper, we argue that
the economic risks posed by a post-AGI world can be effectively mitigated by to-
ken taxes: usage-based surcharges on model inference applied at the point of sale.
We situate token taxes within previous proposals for robot taxes and identify two
key advantages: they are enforceable through existing compute governance in-
frastructure, and they capture value where AI is used rather than where models
are hosted. We then present a research roadmap. For enforcement, we outline a
staged audit pipeline — black-box token verification, norm-based tax rates, and
white-box audits. For impact, we highlight the need for agent-based modeling of
token taxes’ economic effects. Finally, we discuss alternative approaches includ-
ing FLOP taxes, and how to prevent AI superpowers vetoing such measures.

Anonymization: This submission has been anonymized for double-blind review via the removal of identifying information such as names, affiliations, and identifying URLs.

Presenter: ~Lucas_Irwin1

Format: Maybe: the presenting author will attend in person, contingent on other factors that still need to be determined (e.g., visa, funding).

Funding: Yes, the presenting author of this submission falls under ICLR’s funding aims, and funding would significantly impact their ability to attend the workshop in person.

Submission Number: 5