The Procrustean Bed of AI Linguistics: How English-Centric Evaluation Systematically Mutilates Topic-Prominent Languages in the Age of LLMs

The AI research community has committed a spectacular blunder. For decades, we have measured the "intelligence" of language models using evaluation criteria that systematically penalize half the world's languages. Japanese, Chinese, Korean, and dozens of other topic-prominent languages have been forced onto a Procrustean Bed designed for English—stretched, amputated, and mutilated to fit a framework that was never built for them. This paper exposes this scandal.The received wisdom claims that Japanese is "ambiguous," "high-context," and "illogical." This is not merely wrong—it is the precise inversion of linguistic reality. Japanese explicitly marks grammatical relationships through case particles (ga, wo, ni, de, to) with a precision that Modern English lost during the Middle English period. When we claim Japanese is "implicit," we reveal only that we are measuring it against a language that has degraded in its relational encoding capacity.Drawing on Li & Thompson's (1976) linguistic typology, Mikami Akira's revolutionary "subject abolition theory," and comprehensive meta-analyses demonstrating that Hall's "high-context culture" framework has never been empirically validated (Cardon, 2008; Kittler et al., 2011), this paper advances three theses:The Inversion Thesis: It is English, not Japanese, that is the "constrained" language. The loss of Old English case inflection created a language dependent on implicit word-order conventions rather than explicit morphological marking.The Procrustean Bed Argument: Current LLM evaluation treats subject-prominent structure as the only valid grammar, systematically disadvantaging 3+ billion speakers of topic-prominent languages through tokenization, benchmarks, and evaluation tasks designed by and for English speakers.The Ritual Language Hypothesis: The "rigor" of Classical Japanese grammar developed for kotodama-based ritual precision, not logical thinking—a function parallel to Latin in Catholic liturgy, not a measure of cognitive capacity.Those who seek to create superintelligence through language must first understand language itself. No superintelligence will emerge from the careless manipulation of a language whose expressive power has been systematically misunderstood. The Logic Trap—the assumption that English grammatical categories represent universal logical structures—must be escaped before genuine progress in multilingual AI is possible.