Causality is fundamental to agency. Intelligent agents learn about causal relationships by interacting with their environments and use their causal knowledge to choose actions intended to bring about desired outcomes. This paper considers a causal question that is central to the very meaning of agency, that of how a physically embodied agent effects intentional action in the world. The prevailing assumption is that both biological and computer agents are automatons whose decisions are determined by the physical processes operating in their information processing apparatus. As an alternative hypothesis, this paper presents a mathematical model of causally efficacious agency. The model is based on Stapp’s theory of efficacious choice in physically embodied agents. Stapp’s theory builds on a realistic interpretation of von Neumann’s mathematical formalization of quantum theory. Because it is consistent with the well-established precepts of quantum theory, Stapp’s theory has been dismissed as metaphysical and unfalsifiable. However, if taken seriously as a model of efficacious choice in biological agents, the theory does have empirically testable implications. This paper formulates Stapp’s theory as an interventionist causal theory in which interventions are ascribed to agents and can have macroscopically distinguishable effects in the world. Empirically testable implications of the theory are discussed and a path toward scientific evaluation is proposed. Implications for artificial intelligence are considered.
Causality is fundamental to agency. Intelligent agents learn about causal relationships by interacting with their environments and use their causal knowledge to choose actions intended to bring about desired outcomes. This paper considers a causal question that is central to the very meaning of agency, that of how a physically embodied agent effects intentional action in the world. The prevailing assumption is that both biological and computer agents are automatons whose decisions are determined by the physical processes operating in their information processing apparatus. As an alternative hypothesis, this paper presents a mathematical model of causally efficacious agency. The model is based on Stapp’s theory of efficacious choice in physically embodied agents. Stapp’s theory builds on a realistic interpretation of von Neumann’s mathematical formalization of quantum theory. Because it is consistent with the well-established precepts of quantum theory, Stapp’s theory has been dismissed as metaphysical and unfalsifiable. However, if taken seriously as a model of efficacious choice in biological agents, the theory does have empirically testable implications. This paper formulates Stapp’s theory as an interventionist causal theory in which interventions are ascribed to agents and can have macroscopically distinguishable effects in the world. Empirically testable implications of the theory are discussed and a path toward scientific evaluation is proposed. Implications for artificial intelligence are considered.
For all our familiarity with mental processes, their nature remains elusive, and the lessons offered so far by artificial intelligence seem at best incomplete. This reaffirms the need for a conceptually different approach. Recent developments in quantum mechanics, involving nothing larger (or smaller) than tabletop setups, shed light on the issue by showing that events do not always follow a fixed causal order, and that processes exist that are causally non-separable. While experiments have so far preceded theory, fueling debate about the physical interpretation of key results, this mirrors an earlier controversy where results at odds with prevailing paradigms were subsequently vindicated, giving rise to a quantum formalism that is now canonical. In this instance, validation would yield a precise definition of causal agency as an intent-bearing process, the behavior of which is nonrandom, not determined by preceding events, and not derivable from sequential events within the process itself. By focusing on causality rather than on freedom and its interpretive pitfalls, this definition allows to make headway in an old metaphysical discussion.
Sustainability science requires both a descriptive understanding and a normative approach. Modern science, however, began as purely descriptive knowledge, the core of which is that matter is dynamically inert and without purpose. The British philosopher David Hume concluded that the only type of causation in the material world is “efficient causation,” which supported this purposeless view of a deterministic world “governed” by the causal laws of dynamics. But Hume did not argue against the existence of efficacious causation, only the error of humans projecting the mind’s efficacy to objects. Though dynamically inert, a material object away from equilibrium can be thermodynamically reactive, sug-gesting the possibility of the object being efficaciously managed for a purpose. Furthermore, quantum physics has replaced classical physics as the fundamental theory of the material world. Its basic equation, the Schrödinger wave-equation, is deterministic but causally inert—it cannot govern, leaving the determinism door unlocked. This causal gap, according to the von Neumann-Stapp quantum measurement/activation theory, necessitates the pragmatic existence in an irreversible universe of the causal efficacy of mental effort and information management. The resulting “bigger” empirical science has room for “descriptive determinism” and “normative action,” both of which are utterly essential in formulating sustainability science as an integral discipline.
Intervention theories of causality define a relationship as causal if appropriately specified interventions to manipulate a putative cause tend to produce changes in the putative effect. Interventionist causal theories are commonly formalized by using directed graphs to represent causal relationships, local probability models to quantify the relationship between cause and effect, and a special kind of conditioning operator to represent the effects of interventions. Such a formal model represents a family of joint probability distributions, one for each allowable intervention policy. This paper interprets the von Neumann formalization of quantum theory as an interventionist theory of causality, describes its relationship to interventionist theories popular in the artificial intelligence literature, and presents a new family of graphical models that extends causal Bayesian networks to quantum systems.
The observer effect is typically framed as an external intervention: apparatus or agent “measures,” a quantum state “collapses,” and classical facts appear. I propose a complementary, operational reframing: **particle agency**—the idea that elementary systems possess an internally parameterized, interaction-local “policy” that constrains how information about them is externalized during measurement‐like interactions. Formally, I model this by allowing quantum instruments (completely positive (CP) instruments implementing POVMs) to depend on a **latent, endogenous state** (a) that is locally updated by interactions but remains strictly non-signalling at the operational level. This yields two tracks: (i) a **purely interpretive** reading (equivalent to standard quantum mechanics for (a) unobservable and α=0), and (ii) a **mechanistic** reading where weak, testable corrections ((\alpha>0)) subtly alter interference visibility or outcome statistics in autonomous, feedback-capable environments (including living systems) while preserving no-signalling and Born-rule consistency to leading order. I outline falsifiable postulates, a minimal formalism, and three small experiments—two photonic and one solid-state/biophysical—that can bound or detect agency strength. The point is not metaphysics. It’s a crisp operational question: **does endogenous, adaptive structure in the measured system modulate the information map realized by measurement?** If yes, we gain levers for new physics at the quantum–life interface; if no, we gain hard bounds.
Henry Stapp's realistically interpreted orthodox quantum mechanics suggests that when a question is asked, Nature answers. In this formalism, "the thought itself is the thinker," which clears the way for any thinker-human or other-to be an actively creative agent. In this process, an ensuing succession of questions arising in the minds of observers is received and responded to by a "Nature" that chooses and implements responses in accordance with Born's Rule in a physically described universe represented by evolving quantum mechanics states. This paper explores what results might be expected if and when artificial general intelligence (AGI) asks questions, based on Stapp's orthodox interpretation.
What are the physical requirements for agency? We investigate whether a purely quantum system (one evolving unitarily in a coherent regime without decoherence or collapse) can satisfy three minimal conditions for agency: an agent must be able to create a world-model, use it to evaluate the likely consequences of alternative actions, and reliably perform the action that maximizes expected utility. We show that the first two conditions conflict with the no-cloning theorem, which forbids copying unknown quantum states: world-model construction requires copying information from the environment, and deliberation requires copying the world-model to assess multiple actions. Approximate cloning strategies do not permit sufficient fidelity or generality for agency to be viable in purely quantum systems. The third agency condition also fails due to the linearity of quantum dynamics. These results imply four key consequences. First, agency requires significant classical resources, placing clear constraints on its physical basis. Second, they provide insight into how classical agents emerge within a quantum universe. Third, they show that quantum computers cannot straightforwardly simulate agential behavior without significant classical components. Finally, they challenge quantum theories of agency, free will, and consciousness.