Sebastian Saviano

AI systems do not act. They generate coherent outputs under constraint. The persistence of agency attribution in artificial intelligence governance arises not from the presence of intention in these systems, but from a structural feature of their design: sufficiently constrained systems operating over structured data reliably produce the observable markers—coherence, responsiveness, apparent goal-directedness—that humans use to infer agency in other contexts. The inference is not irrational. It is misplaced. This paper identifies that misplacement as the central, undertheorized problem in AI governance. Across philosophy of mind, legal scholarship, and science and technology studies, AI systems are treated as candidates for agency—as full agents, quasi-agents, or distributed actants—despite the absence of the conditions agency requires. This paper argues that these frameworks share a category error: the conflation of output coherence with underlying subjectivity or purposive action. Drawing on philosophy of mind, legal theory, and science and technology studies, it develops a non-agentic model of AI systems as constraint-bound output generators and demonstrates how prevailing frameworks—the intentional stance, legal doctrines of responsibility, and distributed agency models—fail on their own terms when applied to systems of this kind. The governance consequences are direct. Misattributed agency produces unstable liability regimes, because responsibility cannot be correctly located when the wrong entity is treated as its source. It produces conceptual drift in policy language, as terms such as “AI decision-making” and “AI autonomy” migrate from heuristic to descriptive and embed false ontological assumptions in regulatory design. And it produces misplaced regulatory targets, directing institutional attention toward the system rather than toward the human decisions—in design, deployment, and use—where governance can actually take hold. This paper proposes a framework grounded in operational classification rather than metaphoric attribution. The reframing does not alter who bears responsibility—designers, deployers, and users remain accountable—but whether responsibility can be deflected. The agency frame grants AI systems enough ontological status to absorb causal attribution without bearing legal responsibility, creating a structural gap in accountability. The non-agentic model closes that gap: a constraint-bound output generator cannot function as a deflection point, and the defense—“the algorithm decided,” “the system determined”—becomes categorically unavailable. Every outcome traces to a human decision. That is what correct classification makes possible.

Research on conspiracy thinking has largely centered belief as its primary object of explanation, attributing conspiratorial beliefs to cognitive bias, psychological predisposition, or informational distortion. While this literature has generated important insights into individual-level mechanisms, it has struggled to account for the persistence, diffusion, and cross-context recurrence of conspiratorial belief — patterns that suggest the presence of upstream structural conditions. This article argues that these limitations stem from a mis-specified analytic focus: belief is treated as a causal variable rather than as an outcome shaped by institutional conditions. Drawing on a selective review of psychological, sociological, and media-oriented approaches, the article identifies a shared assumption underlying belief-centered models — that conspiratorial belief reflects epistemic deficiency rather than rational adaptation to institutional environments characterized by opacity, weak accountability, and narrative insufficiency. Under such conditions, belief correction alone cannot stabilize authoritative interpretation, and debunking interventions consistently underperform. Rather than proposing a comprehensive theory, the article offers a reframing intervention that shifts analytic attention from belief content to the institutional conditions that structure credibility, epistemic authority, and interpretive stability. This shift has implications for research design, measurement, and comparative analysis — and for understanding why institutional trust erodes even in the absence of deliberate deception. This working paper develops the conceptual framework expanded and applied in Legitimate Distrust: Why Conspiracy Theories Grow When Institutions Fail (Statera Press, 2026), Book Two of The Collapse of Trust series.

This article develops Potentialism as a framework for understanding how uncertainty, observation, and reflexivity structure social transformation — and advances the Quantum-Continuity Model (QCM) as its theoretical instantiation. QCM adapts the epistemic logic of superposition, collapse, and measurement into three social analogues: Transition Zones, Quantum Thresholds, and Quantum Measurement Events. Rather than positing that social systems are literally quantum, it deploys quantum-theoretic reasoning as an epistemological resource for conceptualizing indeterminacy, metastability, and discontinuous resolution in complex social systems. The framework is developed in direct dialogue with complexity theory, constructivism, and reflexivity-based approaches in IR and political sociology. Where complexity theory identifies turbulence but not its resolution, and reflexivity captures feedback but not the moment perception crystallizes into action, QCM specifies the mechanism connecting the two: observation that is not merely passive but constitutive. The model explains how multiple potential futures coexist within metastable social conditions and how interpretive or communicative acts precipitate the abrupt consolidation of one trajectory over others. An illustrative case from the Arab Spring demonstrates how authoritarian regimes persisted within Transition Zones, how legitimacy dissolved through threshold crossings, and how acts of observation — amplified through media and networked communication — reconfigured collective expectations into decisive outcomes. Comparative extensions to the 2008 financial crisis and the #MeToo movement suggest the framework's applicability across domains where metastable equilibria resolve suddenly through constitutive observation. More broadly, QCM clarifies how uncertainty functions as a structural feature of social life rather than a deficit of information, reorienting social and political theory from prediction toward the navigation of potentiality. The framework carries implications for research methodology, governance, and policy — offering tools for identifying when systems are near threshold, when measurement becomes intervention, and when uncertainty is irreducible rather than merely incomplete. This article elaborates the core theoretical framework of a full manuscript that has undergone external peer review. Author's Note This article elaborates the core theoretical framework of A Quantum-Continuity Model for the Social Sciences: Reimagining Uncertainty, Reflexivity, and Emergence in Social Systems (manuscript), which successfully completed external peer review at a major academic press. The working paper develops the epistemological foundations and primary social analogues of that larger project, which extends QCM across elections, financial markets, diplomacy, governance, and research methodology.

Moral progress is not one movement but two. The first raises the floor: it deepens what counts as an impermissible harm. The second expands the radius: it widens the class of persons to whom the floor is owed. Classical Rome protected the freeborn child against sexual violation with real legal force, but the enslaved child of the same age, in the same act, fell outside protection entirely. Extending protection to the enslaved child would have widened the radius without raising the floor. Counting subtler harms against freeborn children as wrongs of the same order would have raised the floor without widening the radius. Different reforms, different beneficiaries, different moral recognitions. These two movements are logically independent, they have usually been run together, and the conflation disarms the progressive narrative against the relativist it most wants to refute: if the floor just is the leading edge of the radius, there is no fixed moral object the radius is moving toward. Holding the floor and the radius apart restores the stable moral object the conflation removed — but only on two separated tracks. On a reality-track, three justificatory traditions selected for the substantial differences in their moral vocabularies — Roman status-honor, the Hebrew covenantal-pollution register, canon-law infantia — converge on the same protected boundary, warranted by the Shklarian priority of injury over principle. On an authority-track, the Street–Joyce debunking objection is confined rather than defeated. Causal explanation cannot, by itself, settle justificatory content for those already engaged in giving and asking for reasons. The genealogy explains why we reason morally at all; it does not determine what our reasoning concludes. The two tracks are analytically distinct: advances on one dimension do not entail advances on the other. History can establish the object; it cannot establish the object’s authority. The paper does not pretend to deliver both from one source. The keystone is that the moral floor is a doctrine about victims, not agents, grounded in vulnerability rather than rational capacity. The consequence is that Kantian content (the Formula of Humanity) can be recruited without Kantian grounding. The framework is deliberately hybrid. Its individual components have clear precedents in the literature, but their combination yields a distinctive argumentative result.