Transferability of Token Usage Rights: A Design Space Analysis of Generative AI Services
Jaeyong Lee, Heeju Kang, Ahra Cho, Baek Eunkyung
TLDR
A design space analysis defines "Transferability" for AI token usage rights, proposing axes and types to give users more control.
Key contributions
- Defines "Transferability" of AI token usage rights, allowing flexible reallocation across time, accounts, and services.
- Identifies five design axes: Target, Direction, Unit, Control, and Reversibility for token transferability.
- Proposes five concrete transferability types: carry-over, co-management, transfer, conversion, and trade.
Why it matters
Current AI token usage is fixed, limiting user flexibility. This paper reframes tokens as a user-centered design element, proposing a framework for transferable token rights. This expands user choice and autonomy in generative AI services.
Original Abstract
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.
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