Transferability of Token Usage Rights: A Design Space Analysis of Generative AI Services
For designers and policymakers of generative AI services, this work provides a conceptual framework to understand and implement flexible token usage rights, though it is an incremental conceptual analysis without empirical validation.
This paper defines and analyzes the transferability of token usage rights in generative AI services, identifying five design axes and five transferability types through analysis of four major LLM services. It reframes tokens as a user-centered design element to enhance user choice and autonomy.
With the rapid spread of generative AI services, the token has gained value not only as a technical unit of language processing but also as an economic currency for accessing AI services. Major AI model providers have adopted token-based billing as their default service model, requiring users to purchase platform-bound, fixed token usage rights. However, the fixedness of these usage rights is grounded in the billing-policy decisions of service providers rather than in any technical necessity. This study defines the Transferability of token usage rights as a design property that allows users to flexibly reallocate purchased data resources free from the constraints of time, account, and service. Drawing on the Design Space Analysis framework of MacLean et al. (1991), we identify five design axes (Target, Direction, Unit, Control, Reversibility) and five concrete Transferability types (carry-over, co-management, transfer, conversion, and trade) by analyzing the billing policies and terms of service of four major LLM services (ChatGPT, Claude, Gemini, Grok). Our analysis reframes the token from a purely economic-technical primitive into a core element of user-centered system design that expands user choice and autonomy.