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<p>Gian-Carlo Rota’s “The barrier of meaning” (1986) is often read as an elegiac tribute to Stanisław Ulam or as an early anticipation of later critiques of symbolic AI. This article argues that its enduring value lies elsewhere: Ulam and Rota isolate the <i>as</i>-relation—taking something&#xa0;as&#xa0;something—as the hinge between formal operations and lived meaning. Through a close reading of Rota’s text, contextualized against 1980s’ expert systems and knowledge representation, I reconstruct the “logic of&#xa0;<i>as</i>” as an ascription problem: formal systems can be exact, and today’s foundation models can capture large-scale patterns of use, yet neither precision nor fluency settles what an output&#xa0;counts as&#xa0;in a concrete situation. I then show how foundation models and co-creative, mixed-initiative systems relocate rather than remove the barrier, distributing semantic responsibility across prompts, interfaces, institutional settings, and human judgment. Finally, I assess hybrid semantic formalisms (neurosymbolic and grounding-oriented) as partial responses to Ulam’s challenge and derive implications for human–AI interaction: evaluating aspect-shift robustness, increasing scrutability of ascriptions, and aiming for calibrated reliance rather than anthropomorphic “understanding.” The analysis clarifies foundational premises of human–computer interaction by treating meaning as a norm-governed, historically situated achievement of practice rather than an internal property of models.</p>

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The logic of as and the historicity of meaning: Gian-Carlo Rota, Stanisław Ulam, and the barrier of meaning in human–AI interaction

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  • 发表日期：

    2026年6月22日

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  • Alberto Bardi

摘要

Gian-Carlo Rota’s “The barrier of meaning” (1986) is often read as an elegiac tribute to Stanisław Ulam or as an early anticipation of later critiques of symbolic AI. This article argues that its enduring value lies elsewhere: Ulam and Rota isolate the as-relation—taking something as something—as the hinge between formal operations and lived meaning. Through a close reading of Rota’s text, contextualized against 1980s’ expert systems and knowledge representation, I reconstruct the “logic of as” as an ascription problem: formal systems can be exact, and today’s foundation models can capture large-scale patterns of use, yet neither precision nor fluency settles what an output counts as in a concrete situation. I then show how foundation models and co-creative, mixed-initiative systems relocate rather than remove the barrier, distributing semantic responsibility across prompts, interfaces, institutional settings, and human judgment. Finally, I assess hybrid semantic formalisms (neurosymbolic and grounding-oriented) as partial responses to Ulam’s challenge and derive implications for human–AI interaction: evaluating aspect-shift robustness, increasing scrutability of ascriptions, and aiming for calibrated reliance rather than anthropomorphic “understanding.” The analysis clarifies foundational premises of human–computer interaction by treating meaning as a norm-governed, historically situated achievement of practice rather than an internal property of models.