Fluid Agency in AI Systems: A Case for Functional Equivalence in Copyright, Patent, and Tort

TL;DR

This paper argues that AI systems exhibit fluid agency, making traditional attribution of authorship and liability infeasible, and proposes functional equivalence as a pragmatic legal framework to allocate rights and responsibilities.

Contribution

It introduces the concept of fluid agency in AI, explaining its impact on legal doctrines, and advocates for functional equivalence as a practical solution for attribution and responsibility.

Findings

Fluid agency challenges traditional attribution models.

Functional equivalence provides a stable legal default.

Proposes pragmatic rules for copyright, patent, and tort law.

Abstract

Modern Artificial Intelligence (AI) systems lack human-like consciousness or culpability, yet they exhibit fluid agency: behavior that is (i) stochastic (probabilistic and path-dependent), (ii) dynamic (co-evolving with user interaction), and (iii) adaptive (able to reorient across contexts). Fluid agency generates valuable outputs but collapses attribution, irreducibly entangling human and machine inputs. This fundamental unmappability fractures doctrines that assume traceable provenance -- authorship, inventorship, and liability -- yielding ownership gaps and moral "crumple zones." This Article argues that only functional equivalence stabilizes doctrine. Where provenance is indeterminate, legal frameworks must treat human and AI contributions as equivalent for allocating rights and responsibility -- not as a claim of moral or economic parity but as a pragmatic default. This principle stabilizes doctrine across domains, offering administrable rules: in copyright, vesting ownership in human orchestrators without parsing inseparable contributions; in patent, tying inventor-of-record status to human orchestration and reduction to practice, even when AI supplies the pivotal insight; and in tort, replacing intractable causation inquiries with enterprise-level and sector-specific strict or no-fault schemes. The contribution is both descriptive and normative: fluid agency explains why origin-based tests fail, while functional equivalence supplies an outcome-focused framework to allocate rights and responsibility when attribution collapses.