Robert Chis-Ciure

In anyone but oneself, experience is always inferred, never observed. This leads to the consciousness attribution problem. The field’s working strategy to address it is comparative and tentative, extrapolating from the neurotypical adult human case to developmentally different or disordered brains, and then, with less confidence, to other animal clades. In these cases, the extrapolation presupposes that several functional-behavioral proxies covary with their neurobiological realizations, which are, at least partially, conserved due to evolutionary kinship. The possibility of artificial consciousness, or synthetic phenomenality, collapses exactly this covariation: an engineered system can simulate or, in the future, perhaps even emulate an experiencer’s proxy profile while sharing none of the realizers that made those proxies worth trusting in the epistemically less problematic cases of neuroatypical humans and some metazoans. I model the whole inferential difficulty along two axes of attribution. On the horizontal axis lies a system’s proxy profile, which denotes the structured pattern it presents from the outside, across behavior, report, functional organization, computational architecture, and any other observer-recoverable representation. The vertical axis concerns the realization base, meaning the substrate-specific and scale-relative organization by which a system jointly generates and maintains the very functional-behavioral proxies it exhibits. While mostly entangled in the human and animal cases, the horizontal and vertical axes come apart in the experiencing machines scenario, revealing two symmetric errors of sufficiency. To defend against both, I introduce a grain-sensitive consciousness attribution policy that calibrates the evidential calculus across the two axes when their intersection is partial at best, theory-laden, and revisable. Applied to disembodied, stored-program statistical computation such as LLMs, the policy yields a defeasible negative worth-attributing verdict. Nevertheless, whether a machina experiens is nomologically possible in other classes of engineered systems stays wholly open. The lesson for the field is that proxy success increases, not cancels, the demand for a realizer story.

A success in adversarial testing of scientific theories reaches only as deep as its matching failure would have cut. I call this the Reach Principle, and the goal of this chapter is to build the instrument that enforces it. Adversarial tests of consciousness theories can turn into a one-way evidential ratchet. When a preregistered prediction passes, the success is claimed for the research program; when it fails, the failure lands on an auxiliary involved in measurement or implementation. The ratchet turns wherever attribution is settled after the outcome is known. Against it, I define a preregisterable test object, putting the attribution policy on the record before the result, comprising what is compared, under which assumptions, when data suffice to settle an outcome, and which targets of a dated theory version each outcome exposes. The Measure Centrality Index 2.0 extends the original version to the positive-evidence side, recording for every possible outcome what it would count against and what its proponent has agreed to change. I run the framework on Cogitate’s third prediction, where the preregistered target was the posterior-connectivity implementation and the mathematical or computational core of both Global Neuronal Workspace Theory and Integrated Information Theory stood outside the test. The record shows that a pass could have been claimed at any depth, because nothing fenced success the way the failure was bound. The next preregistration can set reach in advance, and support for a theory then reaches only what was exposed ex ante.

In this paper we provide a philosophical analysis of the Hard Problem of consciousness and the implications of conceivability scenarios for current neuroscientific research. In particular, we focus on one of the most prominent neuroscientific theories of consciousness, Integrated Information Theory (IIT). After a brief introduction on IIT, we present Chalmers’ original formulation and propose our own Layered View of the Hard Problem, showing how two separate issues can be distinguished. More specifically, we argue that it’s possible to disentangle a Core Problem of Consciousness from a Layered Hard Problem, the latter being essentially connected to Chalmers’ conceivability argument. We then assess the relation between the Hard Problem and IIT, showing how the theory resists conceivability scenarios, and how it is equipped to face up to the hard problem in its broadest acceptation.

This paper formalizes biological intelligence as search efficiency in multi-scale problem spaces, aiming to resolve epistemic deadlocks in the basal “cognition wars” unfolding in the Diverse Intelligence research program. It extends classical work on symbolic problem-solving to define a novel problem space lexicon and search efficiency metric. Construed as an operationalization of intelligence, this metric is the decimal logarithm of the ratio between the cost of a random walk and that of a biological agent. Thus, the search efficiency measures how many orders of magnitude of dissipative work an agentic policy saves relative to a maximal-entropy search strategy. Empirical models for amoeboid chemotaxis and barium-induced planarian head regeneration show that, under conservative (i.e., intelligence-underestimating) assumptions, even ‘simple’ organisms are from two-hundred- to sextillion-fold more efficient in problem space exploration. In this sense, the deep insights of neuroscience are not about neurons per se, but about the policies and patterns of physics and mathematics that function as a kind of “cognitive glue” binding parts toward higher levels of collective intelligence in wholes of highly diverse composition and origin. Therefore, our synthesis argues that the “mark of the cognitive” is perhaps better sought in the measurable efficiency with which living systems, from single cells to complex organisms, traverse energy and information gradients to tame combinatorial explosions-one problem space at a time.

This paper links mathematical consciousness science, particularly Integrated Information Theory (IIT), to Immanuel Kant's philosophy. Skeptics of IIT's theoretical foundation often target its fundamental identity between an experience and Φ-structure. My account brings in the Kantian notion that this identity is a constitutive a priori principle and responds to some objections by drawing on Michael Friedman's defense of similar principles in spacetime physics. As constitutive a priori, the 〈Experience =Φ-structure〉 principle serves various intra-theory functions: (i) enables the application of the intrinsic information formalism to the axioms' phenomenology; (ii) gives empirical meaning to phenomenological concepts; (iii) ensures the possibility of scientific assessment of theory's predictions and explanations; (iv) constructs the theory's explanandum: consciousness as structured, maximally irreducible, specific, intrinsic cause-effect power; and (v) makes possible other a priori explanatory principles. Generalizing beyond IIT, this paper advocates for using constitutive apriority tools to refine the epistemological foundations of other mathematical and scientific consciousness theories. Leveraging the neo-Kantian philosophy of consciousness science research program, it highlights the potential for connecting phenomenological descriptions, physical principles, and mathematical formalism to render current theories more transparent, rigorous, and empirically tractable – a move toward a more mature consciousness science.

This paper offers a nuanced interpretation of Kant’s conception of the a priori, particularly in the context of constitutive principles. Contrary to the received view that separates necessity/universality from constitutivity—a distinction Kant allegedly failed to make—I propose a dual interpretation of the a priori that reconciles these aspects. This interpretation differentiates between a priori as ground (a priori-g) and as knowledge (a priori-k). The a priori-g, rooted in our mind’s invariant structure, encompasses pure intuitions, concepts, and apperception, underpinning all knowledge and embodying constitutivity. Conversely, the a priori-k, deriving its necessity and universality from the a priori-g, is explained by the immutable subjective constitution. This paper argues that Kant implicitly prefigured Reichenbach’s distinction between necessity/universality and constitutivity, viewing their interconnectedness as justifying an extension of the former “marks” to all apriority. My analysis focused less on the synthetic a priori or the synthetic method and more on the constitutive, transcendental dimension of apriority, revealing Kant’s reasoning within the systematic context of the first Critique. It makes explicit Kant’s multiple notions of experience and a priori and his interconnected reasons for them—something that tends to be passed over in contemporary literature on constitutive a priori principles.

In this paper we provide a philosophical analysis of the Hard Problem of consciousness and the implications of conceivability scenarios for current neuroscientific research. In particular, we focus on one of the most prominent neuroscientific theories of consciousness, Integrated Information Theory. After a brief introduction on IIT, we present Chalmers’ original formulation and propose our own Layered View of the Hard Problem, showing how two separate issues can be distinguished. More specifically, we argue that it’s possible to disentangle a Core Problem of Consciousness from a Layered Hard Problem, the latter being essentially connected to Chalmers’ conceivability argument. We then assess the relation between the Hard Problem and IIT, showing how the theory resists conceivability scenarios, and how it is equipped to face up to the hard problem in its broadest acceptation.

In this paper we provide a philosophical analysis of the Hard Problem of consciousness and the implications of conceivability scenarios for current neuroscientific research. In particular, we focus on one of the most prominent neuroscientific theories of consciousness, integrated information theory (IIT). After a brief introduction on IIT, we present Chalmers’ original formulation and propose our own layered view of the hard problem, showing how 2 separate issues can be distinguished. More specifically, we argue that it’s possible to disentangle a core problem of consciousness from a layered hard problem, the latter being essentially connected to Chalmers’ conceivability argument. We then assess the relation between the Hard Problem and IIT, showing how the theory resists conceivability scenarios, and how it is equipped to face up to the hard problem in its broadest acceptation.

This paper deals with a foundational aspect of Integrated Information Theory (IIT) of consciousness: the nature of the relation between the axioms of phenomenology and the postulates of cause-effect power. There has been a lack of clarity in the literature regarding this crucial issue, for which IIT has received much criticism of its axiomatic method and basic tenets. The present contribution elucidates the problem by means of a categorial analysis of the theory’s foundations. Its main results are that: (i) IIT has a set of nine fundamental concepts of reason, called categories, which constitute its categorial lexicon and through which it formulates a system of principles incorporating the axioms, the postulates, and the central identity; and (ii) the connection between the axioms and postulates is grounded by their common root in this categorial lexicon, the categories of which find their justification by means of a phenomenological and transcendental deduction. Some further results are the unique origin of axioms and postulates in the categories; the distinction between conceptual and formalized postulates; a clarification of the uniqueness problem of categorial lexica in general; and an IIT account of objectivity by explicating how the physical is (re)defined by means of categories. All of this is put to use against various criticism targeting IIT’s theoretical core. If successful, the proposed interpretation illuminates a central issue in the contemporary study of consciousness and contributes to an environment of mutual understanding between defenders and critics of the theory.

In this paper, we take a meta-theoretical stance and aim to compare and assess two conceptual frameworks that endeavor to explain phenomenal experience. In particular, we compare Feinberg & Mallatt’s Neurobiological Naturalism (NN) and Tononi’s and colleagues' Integrated Information Theory (IIT), given that the former pointed out some similarities between the two theories (Feinberg & Mallatt 2016c-d). To probe their similarity, we first give a general introduction to both frameworks. Next, we expound a ground plan for carrying out our analysis. We move on to articulate a philosophical profile of NN and IIT, addressing their ontological commitments and epistemological foundations. Finally, we compare the two point-by-point, also discussing how they stand on the issue of artificial consciousness.

In this paper we provide a philosophical analysis of the Hard Problem of consciousness and the implications of conceivability scenarios for current neuroscientific research. In particular, we focus on one of the most prominent neuroscientific theories of consciousness, integrated information theory (IIT). After a brief introduction on IIT, we present Chalmers’ original formulation and propose our own layered view of the hard problem, showing how 2 separate issues can be distinguished. More specifically, we argue that it’s possible to disentangle a core problem of consciousness from a layered hard problem, the latter being essentially connected to Chalmers’ conceivability argument. We then assess the relation between the Hard Problem and IIT, showing how the theory resists conceivability scenarios, and how it is equipped to face up to the hard problem in its broadest acceptation.