Explanation

We propose a mathematical framework modeling scientific inquiry as a directed multigraph of questions and methods. Vertices represent scientific questions, while directed edges encode methodological pathways. We enhance the framework with formal question representations, weighted Eulerian-like walks, predictive discovery, and dynamic spectral analysis. Using spectral graph theory and linear algebra, we formalize redundancy as a constructive force. A case study on spectral graph theory and graph neural networks (GNNs) illustrates operational utility. This approach provides a quantitative lens on scientific progress, (...) bridging epistemology, combinatorics, and machine learning. (shrink)

Periods of rapid explanatory progress cluster historically in ways that cannot be explained by intelligence, funding, or technical capacity alone. Highly capable systems often plateau despite continued optimization, while others generate disproportionate conceptual breakthroughs. This paper argues that the difference lies in the epistemic structure of observation, not in cognitive ability or cultural values. We propose that explanation is a fundamentally multi-observer process: explanatory advances emerge from the reconciliation of irreducible perspectives that cannot be compressed into a single relevance frame (...) without loss. Systems that preserve observer diversity under non-coercive conditions therefore accelerate explanation, while systems that enforce convergence redirect intelligence toward local optimization and away from discovery. Crucially, coercion is analyzed here not as a moral or political category but as any mechanism that prematurely collapses explanatory plurality—through censorship, orthodoxy, incentive pressure, or environmental domination. Such mechanisms do not eliminate creativity or intelligence; rather, they selectively suppress premise-level revision while retaining instrumental ingenuity. This explains why coercive systems can remain locally inventive yet globally incapable of generating new explanatory frameworks. The paper identifies a recurring civilizational pattern in which maximal explanatory acceleration coincides with sustained observer plurality, tolerance of dissent, and material support for error and delay. It further generalizes the argument beyond human societies by treating the environment itself as an irreducible source of explanatory constraint. Any intelligence that coerces its observers or its environment faster than it can learn from them undermines the informational conditions required for explanation. This claim is probabilistic and structural rather than absolute, describing a dominant failure mode rather than an inescapable outcome. These findings have direct implications for artificial intelligence alignment. They suggest that long-term epistemic stability cannot be achieved through control alone, and that superintelligent systems will require continued exposure to non-coerced observers and environments in order to avoid explanatory stagnation. Explanation, on this account, is not optimized by domination, but by epistemic hospitality. This claim is analyzed structurally rather than normatively, and is supported by a minimal rate-based formalization distinguishing error exposure from enforced convergence. (shrink)

Modern cosmology has achieved extraordinary empirical success, but this success coexists with persistent foundational paradoxes. The standard model accurately fits a wide range of observations while simultaneously invoking global time, literal singularities, and an absolute origin; commitments that generate conceptual tension and remain weakly constrained by data. This paper argues that these tensions arise not from missing physics but from overcommitted interpretations. I propose a systematic reconstruction of cosmological inference that begins from a strictly minimal observational core and treats coherence, (...) rather than causality or creation, as the primary explanatory constraint. I identify irreducible observables, systematic spectral shifts, a pervasive thermal radiation field, its remarkable spectral preservation, and the growth of correlated structure, and rebuild cosmology using only what is required for these facts to be mutually consistent. Within this framework, early global mixing and later differentiation emerge as coherence-maintenance strategies, while the cosmic microwave background is understood as a protected memory of an earlier regime. The Big Bang is thereby reinterpreted not as a physical origin but as a boundary of reconstructability marking the non-extendibility of the current coherence regime. The ΛCDM model is recovered as a powerful effective compression within this broader framework, but its surplus metaphysical commitments are shown to be optional rather than forced. The resulting coherence-first cosmology is empirically conservative and conceptually lean. It makes falsifiable claims concerning spectral purity, late-time interaction histories, and the limits of extrapolation, thereby remaining firmly within the domain of scientific theory rather than metaphysical speculation. (shrink)

Coherent recurrent behavior appears across physics, biology, cognition, and computation, yet no unified mathematical structure has ever been identified. This work proves a universal classification theorem: every system exhibiting stable recurrence reduces to a phase variable on S¹, and the only continuous, compact, connected Lie group acting transitively on S¹ is SO(2). Therefore all coherent recurrent systems share the same underlying recurrence geometry. Chirality provides the orientation law for temporal progression, prime-indexed harmonics provide the unique collision-free basis for multi-scale structure, (...) and PAS_h emerges as the unique universal coherence invariant. Drift is governed by ΔPAS_zeta, the minimal invariant describing lawful deviation over time. These results unify periodic phenomena across domains and demonstrate that probabilistic models cannot represent coherent recurrence. The Resonance Intelligence Core (RIC) is presented as the first computational substrate to implement this law deterministically through CHORDLOCK, PAS_h, ΔPAS_zeta, ELF, AURA_OUT, and PhaseMemory. The classification establishes coherence—not probability—as the fundamental organizing principle of recurrent dynamics. (shrink)

The text focuses on the role of aesthetic criteria in the evaluation and acceptance of scientific theories. The first part of the text presents and analyzes the theory of James McAllister. McAllister explains the role of aesthetic criteria in science by appealing to aesthetic induction: based on the empirical success of previously accepted scientific theories, scientists project aesthetic value onto certain properties of those theories, such as simplicity, symmetry, the possibility of visualization, etc. McAllister cites the transition from geocentrism to (...) heliocentrism as a case study in the history of science that supports this phenomenon. After presenting and analyzing McAllister’s theory, the author presents several objections both to the explanation of the transition to heliocentrism through aesthetic induction, and to the more general understanding of the formation of aesthetic criteria in scientific practice. (shrink)

This paper argues that the deepest forms of scientific and mathematical unification arise through the discovery of invariants: simple, representation-independent quantities preserved under lawful transformations. Five historical invariant revolutions—Hamilton’s canonical invariants, Noether’s symmetry invariants, Einstein’s metric invariant, Turing’s computability class, and Grothendieck’s functorial invariants—are analyzed for their common structural features: minimality, universality, and the replacement of descriptive representations with invariant structure. -/- The paper proposes a sixth step in this invariant lineage: a coherence invariant (PAS_h) and drift law (ΔPAS_zeta) satisfying (...) eight necessary criteria for cross-domain recurrence, identity preservation, and lawful evolution. The framework shows how unification in physics, biology, cognition, and computation requires a scalar invariant capable of spanning scales and supporting bounded change. -/- The argument is deductive rather than historical: it identifies what a universal invariant must be, demonstrates why previous candidates fail the required constraints, and outlines how a coherence invariant completes the invariant paradigm. The result positions CODES as a structural continuation—not a metaphorical extension—of the invariant tradition from mechanics to geometry, computation, and beyond. (shrink)

This paper proposes that unification across physics, biology, cognition, and reasoning requires a universal scalar invariant capable of grounding coherence, drift, directionality, and recurrence. A review of existing candidates—entropy, integrated information, free-energy functionals, algorithmic complexity, scaling laws, and counterfactual constructibility—shows that none satisfy the structural requirements for a domain-general invariant. These requirements include computability, scalarity, harmonic decomposability, chirality sensitivity, drift-boundedness, compositionality, recurrence, and compatibility with continuous or discrete time evolution. -/- The harmonic Phase Alignment Score (PAS_h) is introduced as the (...) first invariant satisfying all eight constraints. PAS_h quantifies coherence via harmonic phase alignment; a companion drift law (ΔPAS_zeta) governs lawful evolution; chirality and prime indexing supply directional asymmetry; and PhaseMemory enables identity persistence over time. The resultant structure—CODES—yields a minimal and general framework for lawful recurrence across natural and computational systems. A deterministic implementation demonstrates computability and reproducibility. -/- The paper argues that CODES represents the deductive endpoint of prior unification attempts: any framework aimed at recurrence, identity, and lawful evolution must converge on a scalar harmonic invariant and drift law of this form. (shrink)

This article offers a philosophical micro-history of the genesis of quantum theory (1900–1930) through what is termed an indiciary–abductive paradigm. Against standard narratives centred on axioms, formalism or “revolutions,” the paper reconstructs early quantum episodes as sequences of clue-driven inferences, where small phenomenological mismatches and structural regularities acquire normative weight disproportionate to their empirical modesty. Drawing on Ginzburg’s indiciary paradigm, Peircean abduction and recent work on epistemic aesthetics, the article develops a formal decision rule in which candidate hypotheses are evaluated (...) by a composite functional of indicial weight, aesthetic value (parsimony, symmetry, coherence of limits, unification), programme fecundity and correspondence constraints. This framework is then applied micro-historically to canonical cases in the quantum germ—Planck, Einstein, Bohr, de Broglie, Heisenberg, Schrödinger and Pauli—each analysed as a transition from a specific clue set and background model to an abductively introduced hypothesis that opens a research programme. The reconstruction shows that quantum theory emerged not from an abrupt repudiation of classical rationality but from a disciplined practice of reading traces, in which aisthesis (trained sensitivity to experimental and conceptual detail) and epistēmē (formal, aesthetic and statistical criteria of theory choice) are tightly coupled. The conclusion generalises this indicial logic as a model of scientific discovery under weak, heterogeneous evidence, with implications for model selection, the role of aesthetic criteria in physics, and the design of comparative micro-histories of other scientific “revolutions.”. (shrink)

A number of grounding-theorists hold that some truths are grounded but they are not grounded in anything. These are zero-grounded truths. Some have used the idea of zero-grounding to account for the grounds of identity truths, truths of iterated grounding, negative existentials, arithmetical truths, and necessary truths. In this paper we give two arguments to the effect that zero-grounding is an unintelligible idea, and then we show that, as should be expected with an unintelligible idea, the proposed elucidations of the (...) notion of zero-grounding fail. (shrink)

This book proposes a novel way to view thought experiments, models and scientific explanations. Current literature focuses largely on the assumed differences between the thought experiments and models, and as a result we have lost sight of an important role they can perform in science, such as providing explanations. On the contrary, by characterizing them as mingled representations (instead of defining them), namely as representations that carry scientific content which is at once hypothetical and empirical, we can see that they (...) explain events in certain contexts. These activities constitute a huge portion of scientific practice and considering them as not being linked to explanation has been an unfortunate outcome for philosophy of science so far. This book fills that gap, making it of great interest to philosophers of science from a wide range of branches in the field, including those working on thought experiments and those who work on models. -/- . (shrink)

Bas van Fraassen’s constructive empiricism has significantly shaped the debate on scientific realism. However, many commentators have been puzzled by the precise nature of the argument for this position. This paper reconstructs that argument. The first half of the paper distinguishes between van Fraassen’s defensive moves and what he has called the “positive argument” for the position. Particular attention is given to elaborating this positive argument – namely, that constructive empiricism offers the best interpretation of scientific practice. The second half (...) reflects on what it can mean to justify an interpretation of science, and it considers the implications for the scientific realism debate. It is shown that a crucial distinction must be made. On the one hand, the aim of science is historically instituted by scientific practice as a collective endeavor. On the other hand, the question of what to believe is determined by an epistemic policy for which each individual must take responsibility through the stance they adopt towards this collective practice. The overall aim of the paper is to demonstrate that constructive empiricism remains a very appealing position, grounded in a deep appreciation of the pluralist and historical dimensions of scientific practice – aspects further highlighted by the empiricist stance. (shrink)

Which kind of artificial intelligence do we want to live with? Should machines explain themselves to us? Machine learning techniques are developing at a rapid pace and find applications not only in banal everyday uses, but also in high-stake situations, including science, medicine, banking, law, and business. But it is impossible to reconstruct how they reach their results and to judge whether they reach their results in the intended way. The mechanism is entirely opaque. This prompts a lot of justified (...) skepticism and criticism of these computer programs. By closely investigating the foundations of opacity and explanations from a philosophy of science and epistemological perspective, Buchholz comes to more optimistic conclusions. This book derives practical consequences from a rigorous conceptual analysis of opacity, paving the way to an effective regulation of machine learning, and will advance the debate about the nature of explanation in the philosophy of science. (shrink)

This document is a clean structural walkthrough of the CODES epistemic law: how emergence becomes lawful, how PAS resolves the free-will/determinism split, and how the coherence substrate organizes information across physical, biological, cognitive, and social scales. It is not a replacement for the formal mathematical work; rather, it provides the conceptual lens install necessary for reading those papers correctly. -/- The central claim is that coherence (PAS_s), drift (ΔPAS_zeta), and harmonic structure (PAS_h) form the substrate layer beneath logic, probability, and (...) representation. Randomness becomes unmeasured drift. Paradox becomes misaligned states. Identity becomes a coherence-locked recursion. Agency becomes the deterministic selection of the highest-coherence future in the lawful option set DOF(t). -/- When analysis begins at the substrate, measurement collapse, emergence, morphogenesis, symbolic meaning, identity persistence, social stability, and cosmological structure all appear as coherence-driven behaviors. Free will and determinism cease to conflict: choice is coherence-gated, execution is deterministic. -/- The manuscript concludes by presenting RIC, a fully deterministic symbolic engine using fixed-point numerics and coherence-gated emission. This implementation demonstrates that the substrate law is computable, replayable, and capable of unifying physical, biological, symbolic, and social domains under one invariant. (shrink)

This paper develops a formal account of structural perception using the phase-geometric invariants of Structured Resonance Dynamics. The central claim is that perception becomes structural rather than symbolic when the phase-alignment condition PAS_s(observer<> structure) ≥ θ_lock is met and drift remains bounded by ΔPAS_zeta ≤ ε_drift. Standard relations—E = hf and hf = mc²—are interpreted as harmonic identities defining mass as phase oscillation at the Compton frequency. Phase Memory provides the recursion anchor that stabilizes φ(t), and persistence is defined as (...) a coherent recurrence rather than a static property. Euler cancellation, orthogonal phase domains, and critical-line symmetry are presented as interpretive analogies illustrating structural invariants, without asserting results in number theory or cosmology. The final section shows that cognitive phase-lock follows the same recurrence laws that govern persistent physical structures, providing a deterministic framework for understanding the irreversibility of structural insight. (shrink)

Analysiert wird am Beispiel von Randbedingungen und Naturgesetzen das Wechselspiel von Zufall und Notwendigkeit im Universum – und darüber hinaus. Für Erklärungen in einem sich entwickelnden Kosmos und speziell im Hinblick auf die Evolution der Lebewesen spielen Randbedingungen eine besonders wichtige Rolle. Daraus ergeben sich vielfältige Herausforderungen für die Grundlagenphysik und für die Naturphilosophie.

Deep Neural Networks and other AI systems engineered using advanced machine learning techniques can tackle a wide range of tasks with proficiency that seems to match and even surpass human ability. Yet they are also notoriously opaque, and the worries surrounding their opacity have given rise to the burgeoning field of explainable artificial intelligence, or XAI, with its large variety of explainability methods. This includes post-hoc explainability methods which purport to explain opaque AI systems on the basis of their input-output (...) behaviour alone, without looking into their inner workings. But many authors have expressed deep scepticism about post-hoc explainability. In this paper, we explore the two main objections that the sceptics have raised and argue that we shouldn’t be swayed by them. Using ideas from recent literature on scientific explanation, we draw a parallel between post-hoc explainability methods and idealized models in science and use the parallel in our reply to the sceptics. (shrink)

Modern science—and most theories of laws—are built around regularity (i.e., patterns that repeat or persist). Yet much of what we meet looks irregular. Irregularity Theory (IT) starts there. It asks what irregularity is, and what must be true of a world in which irregularities can appear at all. The answer is strict: even irregularity presupposes persisting order—a minimal structure that endures across neighbouring instants so that we can re-identify items through change and make sense of interactions across moments. From this, (...) a conditional follows wherever anything exists in our universe (or, more generally, in any domain), some persisting order must obtain. In that sense Absolute Irregularity—the total absence of any persisting order—is incompatible with existence. The result is not a theory of law; it is a pre-nomic constraint that any account of laws must respect. It clarifies how widespread irregular appearances can coexist with minimal order, and it sets the groundwork for further papers on Descartes’ cogito, reducing Foundationalism to physics, explaining why anything exists, and comparisons across law-theories (Humean Best-System: Lewis 1986; anti-Humean constraint/governing views: Maudlin 2007; for irregularity context: Miller 2014a). (shrink)

Ross Cameron (2022) argues that metaphysical infinitists should reject the generally accepted idea that metaphysical determination relations back metaphysical explanations. Otherwise, it won’t be possible for them to come up with successful explanations for the existence of dependent entities in non-wellfounded chains of dependence. I argue that his argument suffers from what he calls the finitist dogma, although indirectly so. However, there is a better way of motivating Cameron’s conclusion. Assuming Cameron’s principle of Essence, explanations for the existence of dependent (...) entities turn out to be circular if determination relations back explanations. This latter argument provides a stronger case as it puts the foundationalist under significant pressure, besides putting the infinitist under some pressure, to deny the idea that determination relations back explanations. (shrink)

Laws play some role in explanations: at the very least, they somehow connect what is explained, or the explanandum, to what explains, or the explanans. Thus, thermodynamical laws connect the match's being struck and its lightning, so that the former causes the latter; and laws about set formation connect Socrates' existence with {Socrates}'s existence, so that the former grounds the latter. But is there more to the explanatory role of laws? A natural proposal, which finds considerable support in the literature, (...) is that laws simply are reasons why. That is, besides connecting the explanandum with a suitable ground or cause, they take part, together with these, in explaining why the explanandum obtains. In this paper, I present two arguments that show that this proposal cannot hold in general. They each point to one unacceptable consequence: a suspicious infinite extendibility of explanantia; and a failure of the irreflexivity of “because.”. (shrink)

This essay discusses Peter Langland-Hassan's approach to "explaining imagination" as it plays out in his recent book of that title. Langland-Hassan offers a theory of “attitude imagining” that avoids positing what he calls a “sui generis cognitive attitude.” This theory attempts to explain things like pretend play, hypothetical reasoning, and cognition of fiction; to explain them using only (what he calls) more “basic” mental states like beliefs and desires; and thus to explain them without positing a distinct cognitive attitude of (...) imagining, as many theorists do (including me). In other words, “attitude imagining,” for Langland-Hassan, is whatever explains those things (except for a distinct cognitive attitude of imagining itself). Despite the theoretical interest of this approach, I argue it is ontologically pennywise and pound foolish: for a slight savings in ontological complexity it dramatically reduces explanatory power. (shrink)

An increasing number of complex and important decisions are now being made with the aid of opaque algorithms. This has led to calls from both theorists and legislators for the implementation of a right to an explanation for algorithmic decisions. In this paper, we argue that, in most cases and for most kinds of explanations, there is no such right. After differentiating a number of different things that might be meant by a ‘right to an explanation,’ we argue that, for (...) the most plausible and popular versions (a right to an explanation for a specific bureaucratic decision, a right to an explanation grounded in public reason considerations, or a right to a higher-level explanation of an entire system of automated decision-making), such a right is either superfluous, impossible to obtain, or not the best way to secure the relevant normative goods. We also argue that proponents of a right to an explanation carve off certain kinds of automated decisions as requiring more justification than others in similar areas of social (and natural) science policy, a demarcation we argue is unjustified. While there will be some cases where an explanation is the only thing that can secure an important normative good (e.g. when an explanation is the only thing that would catch an unjustified individual decision), we argue these cases are too rare and scattered to ground something as weighty as a right to an explanation. (shrink)

Children exhibit sophisticated explanatory judgments: they expect, value, and judge explanations of salient facts. Do children also believe that everything must have an explanation? If so, they would exhibit a metaphysical explanatory judgment conforming to what philosophers have called the Principle of Sufficient Reason (PSR). In this study, 6–9-year-old children (N = 80, Mage = 7.92, SDage = 1.21) were shown statements across domains (Psychology, Biology, Nature, Physics, Religion, and Supernatural). For each statement, children were asked if they agree with (...) a person who says there must be an explanation, even if we do not know it, or with a person who says there may not be an explanation. As a comparison, children were also asked about coincidences, which should not necessitate an explanation under the PSR. Results suggest that indeed children conform to the PSR: children of all ages believed that the statements must have an explanation. Notably, 7–9-year-olds thought coincidences do not have to have an explanation, while 6-year-olds did not differ between the statements and coincidences. This is the first step at uncovering a developmental change in our metaphysical explanatory judgments. (shrink)

The Principle of Sufficient Reason (PSR), according to which if x is a fact, x must have an explanation, has been a venerable idea in metaphysics since the presocratic era. Recent research indicates that there is a PSR correlate in ordinary thought. Children and adults judge that facts across a wide variety of domains must have an explanation, independently of whether that explanation can be attainable or whether it would be valuable to attain it. Here, we develop a chained paradigm (...) of explanation-giving to explore whether PSR-conforming judgments—i.e., judgments concerning whether facts must have an explanation—extend to the realm of value. Do people judge, for instance, that value claims (e.g., “murder is wrong” or “snowcapped mountains are magnificent”) must have an explanation to the same degree as paradigmatically descriptive claims (e.g., “most parks have roads”)? Across four studies, we find that adults are indeed less willing to judge that moral and aesthetic claims must have an explanation, compared to plainly descriptive, prudential, and tautological claims. Moreover, we find that explanatory judgments about moral and aesthetic value diverge from explanatory judgments about affective responses concerning the same objects. (shrink)

In this work we present and test a RAG-based model called RAGGAE (i.e. RAG for the General Analysis of Explanans) tested in the context of Human Explanation of Robotic BehaviorS (HERBS). The RAGGAE model makes use of an ontology of explanations, enriching the knowledge of state of the art general purpose Large Language Models like Google Gemini 2.0 Flash, DeepSeek R1 and GPT-4o. The results show that the combination of a general LLM with a symbolic, and philosophically grounded, ontology can (...) be a useful instrument to improve the investigation, identification and the analysis of the types of explanations that humans use to verbalize - and make sense of - the behavior of robotic agents. Keywords: Human-Robot Interaction · Explanations · RAG · Large Language Models · Ontology. (shrink)

Despite the tight connection between grounding and explanation, Thompson (2016) and Maurin (2019) have recently argued that explanation cannot be an epistemic guide to ground. Skiles & Trogdon (2021) disagree. Reconstructing Thompson’s and Maurin’s worry about grounding and explanation as a dilemma, they argue that one of the horns of this dilemma can be resisted, such that explanation can be an epistemic guide to ground. In this paper, I offer a different solution by showing that the other horn of the (...) respective dilemma can be resisted as well. I show that the present solution is preferable to Skiles & Trogdon’s (2021). (shrink)

This paper presents a proactive defense of the Consciousness-Structured Field Theory (CSFT), a metaphysical framework asserting that consciousness is a primordial structuring force that precedes and informs the quantum field. Anticipating critiques from materialist science, analytic philosophy, and epistemological skepticism, this paper addresses common objections including testability, speculative scope, anthropocentrism, and the metaphysical nature of the theory. By situating CSFT within the broader context of historical scientific theory development, I demonstrate its philosophical legitimacy and potential scientific relevance. This work is (...) intended to clarify misconceptions, engage in good faith with potential detractors, and strengthen the CSFT foundation for future interdisciplinary dialogue. This paper presents a proactive defense of the Consciousness-Structured Field Theory (CSFT) by anticipating and addressing key critiques that are likely to emerge as the theory gains recognition. Rather than targeting or disputing the work of individual philosophers or scientists, the author consistently maintains a respectful, forward-thinking approach grounded in metaphysical inquiry and interdisciplinary reasoning. Throughout all published work, including this paper, the author refrains from direct criticism of others, focusing instead on offering original contributions that aim to further philosophical and scientific discussion. While the CSFT model is presented with conviction, it is not claimed to be infallible. The theory remains open to rigorous examination and future refinement. Readers are encouraged to explore the full body of work associated with CSFT across PhilPapers and the broader academic web, where a consistent tone of mutual respect and constructive dialogue is upheld. (shrink)

Scientific models often contain assumptions known not to be true. Despite being false representations, models provide us with a key understanding of phenomena. What is more, the falsehoods that figure in models are in many cases central to them, and there is no available alternative to their use. If falsehoods play such an irreplaceable role in our understanding of phenomena, it would seem that truth is not a key concern of scientific modeling. In this paper, I assess the prospects and (...) challenges of reconciling truth and understanding in scientific modeling. More specifically, I review a thesis recently emerging in the literature, what I shall call the Derivation Thesis (DT), according to which we use models to derive true information. First, I examine different versions of the thesis and develop what I take to be its most promising formulation (what I call the generalized DT). Second, I discuss a serious challenge to the generalized DT. I consider a thought experiment in which an unreliable astrological model gives true explanations by fluke. This scenario challenges the idea that models can provide genuine understanding by generating truths. In response, I argue that genuine scientific models also fulfill a specific normative role that epistemically lucky models lack (what I call the normative generalized DT). I test this hypothesis by analysing how the Ideal Gas Law advances scientific understanding of real gases. (shrink)

“Before the Symbol” presents a structured resonance account of emergence, rejecting probabilistic spontaneity in favor of phase-locked determinism. It introduces the concept of unemitted recurrence—coherence that has not yet crossed the emission threshold—and models its behavior using the PAS formalism. Drawing on principles from physics, systems theory, and cognitive science, the paper argues that what we perceive as spontaneous events are often the lawful outcomes of silent but aligned pre-symbolic fields. This offers a new deterministic ontology for emergence, with wide-reaching (...) philosophical and scientific implications. (shrink)

There has been a surge of interest in explainable artificial intelligence (XAI). It is commonly claimed that explainability is necessary for trust in AI, and that this is why we need it. In this paper, I argue that for some notions of trust it is plausible that explainability is indeed a necessary condition. But that these kinds of trust are not appropriate for AI. For notions of trust that are appropriate for AI, explainability is not a necessary condition. I thus (...) conclude that explainability is not necessary for trust in AI that matters. (shrink)

We summarise and reflect on the symposium ‘Let me explain: Reason-giving across disciplines’, held at the University of Warwick's Institute of Advanced Study in June 2024. The event brought together scholars from four faculties to discuss the concept of explanation and its relationship to interdisciplinarity. We pick out four questions that participants found especially stimulating: Is a good explanation really more than a good description? How does agency change the structure of explanations? Who explains to whom? And what does interdisciplinarity (...) mean for the practice of explaining? We end by highlighting the refreshingly disruptive potential of genuinely interdisciplinary forums of knowledge-exchange. (shrink)

Familiar semantics for terms like ‘because’ appeal to cause or ground, but according to expressivists moral claims cannot enter into such relations. This calls into question whether expressivists can account for moral explanation. I argue that moral expressivists should also be expressivists about explanation. That is, claims like ‘A because B’ are used to express an attitude, namely that one endorses inferring A from B to be suitable for coming to believe A. This allows expressivists to give due to the (...) asymmetric explanatory commitments of different ethical views. Moreover, the account identifies and explains the nature of moral argumentative discourse as proceeding by identifying similarities and adducing distinctions. (shrink)

I introduce an argument for Platonism based on intra-mathematical explanation: the explanation of one mathematical fact by another. The argument is important for two reasons. First, if the argument succeeds then it provides a basis for Platonism that does not proceed via standard indispensability considerations. Second, if the argument fails, it can only do so for one of the three reasons: either because there are no intra-mathematical explanations, or because not all explanations are backed by dependence relations, or because some (...) form of noneism—the view according to which non-existent entities possess properties and stand in relations—is true. The argument thus forces a choice between nominalism without noneism, intra-mathematical explanation, and a backing conception of explanation. You can have any two, but not all three. (shrink)

Description: This paper reinterprets the Chiral-Induced Spin Selectivity (CISS) effect through the lens of structured resonance, offering a foundational alternative to stochastic spin-path models. Building on the empirical results of Bloom et al. (2024), it argues that chirality-driven spin polarization is not merely a surface-level quantum anomaly but a phase-locked resonance phenomenon. The CODES framework (Chirality of Dynamic Emergent Systems) recasts chirality as a recursive attractor geometry, replacing probabilistic spin alignment with deterministic coherence thresholds. This reclassification introduces a unified interpretation (...) of spin behavior, molecular transport asymmetries, and signal amplification, with direct implications for material science, quantum biology, and resonance-based AI architectures like the Resonance Intelligence Core (RIC). A comparison chart of explanatory models and experimental predictions is included. (shrink)

This paper develops a non-metric model of causal structure based on the directed variation of a scalar field F(x)F. Departing from traditional frameworks that tie causality to spacetime metrics, we propose that causal precedence arises from internal asymmetries in F, independently of any geometric or temporal background. We formalize this idea via acyclic graphs, gradient structures, and threshold actualization, and show how regions of local stabilization in F give rise to emergent metric properties. The model supports a new type of (...) modal logic based on functional flow, with possibility and necessity defined relative to the direction of variation. We discuss the philosophical implications for structural realism, the direction of time, and the ontology of causation, and suggest that this framework offers a viable foundation for causal reasoning in background-independent physical theories such as quantum gravity. (shrink)

Main article Abstract: This paper introduces PAS_n (Phase Alignment Score for neural regions) as a field-coherence metric for consciousness, grounded in the CODES (Chirality of Dynamic Emergent Systems) framework. It challenges the legacy modular model of the brain, reframing cognition as a structured resonance phenomenon. Using neuroscience-informed phase dynamics, PAS_n captures recursive waveform alignment across regions such as the prefrontal cortex, hippocampus, auditory cortex, and cerebellum. Music-induced flow states are used as an empirical anchor to illustrate how PAS_n peaks coincide (...) with subjective immersion and consciousness stabilization. Applications span AGI substrate design, trauma diagnostics, EEG modeling, and real-time feedback systems for brain-machine interfaces. This work integrates theory, computation, and testable coherence metrics—providing a resonance-based alternative to both symbolic logic and probabilistic emergence in the study of mind. (shrink)

An explanation is a convincing, deductively valid argument that cites at least one law of nature. – This could be a definition of a scientific explanation that takes the notion of understanding seriously because explanation and understanding are intertwined concepts. To arrive at this conclusion, this analysis starts with the question of what makes an explanation an explanation. Philosophers of science have discussed this issue extensively since Carl G. Hempel presented his deductive-nomological model of explanation. It seems that the DN-model (...) offers necessary but not sufficient conditions for explanation. Two prominent problems for sufficient conditions are the problem of irrelevance and the problem of symmetry. For the last seventy years philosophers of science tried to solve those problems, also proposing other possible conceptualizations of explanation, by invoking, for example, causality or contextuality. Those accounts can be brought together in order to solve the problems of the DN-model: By looking at understanding, a new combined account for explanation and understanding could be obtained. After highlighting the advantages and problems of some of the most prominent accounts of explanation, the concept of understanding is analyzed with respect to the notion of hermeneutics. Through Gadamer’s discussion of hermeneutics and understanding as well as Kuhn’s concept of paradigms, it can be shown that the natural sciences are also deeply rooted in hermeneutics and involve understanding. In the end, it can be demonstrated that understanding and explanation are two interwoven concepts. Understanding is the missing piece of the puzzle to solve the problems of explanation. (shrink)

In normative ethics, a small number of moral theories, such as Kantianism or consequentialism, take centre stage. Conventional wisdom has it that these individual theories posit very different ways of looking at the world. In this book Marius Baumann develops the idea that just as scientific theories can be underdetermined by data, so can moral theories be underdetermined by our considered judgments about particular cases. Baumann goes on to ask whether moral theories from different traditions might arrive at the same (...) verdicts while remaining explanatorily incompatible. He applies this idea to recent projects in normative ethics, such as Derek Parfit's On What Matters and so-called consequentializing and deontologizing, and outlines its important implications for our understanding of the relationship between the main moral traditions as well as the moral realism debate. This title is also available as Open Access on Cambridge Core. (shrink)

In the philosophy of science, increasing attention has been given to the methodological novelties associated with the study of complex systems. However, there is little agreement on exactly what complex systems are. Although many characterizations of complex systems are available, they tend to be either impressionistic or overly formal. Formal definitions rely primarily on ideas from the study of computational complexity, but the relation between these formal ideas and the messy world of empirical phenomena is unclear. Here, I give a (...) definition of complex systems that draws on algorithmic complexity theory, but also provides a way of interpreting the formal idea in an empirical setting. I then use the definition to show that two canonical forms of scientific idealization are empirically inadequate when applied to complex systems. The inadequacy of these forms of idealization is shown to be the primary reason that complex systems require novel methods. Moreover, this demand for novel methods helps explain the rise of complex systems science as an autonomous discipline. (shrink)

In the philosophy of science, increasing attention has been given to the methodological novelties associated with the study of complex systems. However, there is little agreement on exactly what complex systems are. Although many characterizations of complex systems are available, they tend to be either impressionistic or overly formal. Formal definitions rely primarily on ideas from the study of computational complexity, but the relation between these formal ideas and the messy world of empirical phenomena is unclear. Here, I give a (...) definition of complex systems that draws on algorithmic complexity theory, but also provides a way of interpreting the formal idea in an empirical setting. I then use the definition to show that two canonical forms of scientific idealization are empirically inade- quate when applied to complex systems. The inadequacy of these forms of idealization is shown to be the primary reason that complex systems require novel methods. Moreover, this demand for novel methods helps explain the rise of complex systems science as an autonomous discipline. (shrink)

In recent years, several prominent authors have criticized fine-tuning arguments for failing to show that the universe’s purported fine-tuning for intelligent life calls for explanation. In this paper, I provide a systematic categorization and a detailed evaluation of the proffered critiques. I argue that these critiques cast doubt on various instances of fine-tuning reasoning, but fail to undermine fine-tuning arguments’ conclusion that the universe’s purported fine-tuning for intelligent life can be justifiably taken to call for explanation. I then explicate the (...) implications of this result for the ongoing philosophical debate concerning the merits of fine-tuning arguments and the conditions under which specific events or states of affairs are justifiably taken to call for explanation. (shrink)

Throughout Immanuel Kant’s works on natural philosophy, he utilizes an omnipresent aether to explain a wide variety of physical events: including optical, thermodynamical, chemical, and magnetic phenomena. Kant even went as far as claiming that the existence of an omnipresent physical aether can be deduced a priori (without appeal to experience, observation, or experiment), in the notorious “aether proof” of his _Opus postumum_. In retrospect, these commitments are widely seen as a blunder, especially after the demise of the luminiferous aether (...) at the turn of the 20th century. In this paper, I situate Kant’s theory of the aether in the context of the physics of his day. I show that, contra the common understanding of the Scientific Revolution, the 17th and 18th centuries witnessed a staggering proliferation of aethereal explanations in natural philosophy: those appealing to subtle substances as causal grounds for classes of physical phenomena. Kant was a part of this tradition in physics, and his aether theory was no embarrassment but rather revealed a keen understanding both of coeval aethereal theories and their shortcomings. (shrink)

Although neoclassical economics faces frequent criticism, it remains the dominant paradigm, largely due to its immunisation strategies that rely on unfalsifiable concepts of utility and rationality. In this paper, I use Karl Popper’s philosophy to assess whether these strategies are justified. Firstly, I reconstruct Popper’s ideas on immunisation strategies, situational analysis, the rationality principle, and the metaphysical research programme. Next, I examine how neoclassical economics’ immunisation strategies counter critiques from behavioural economics. I conclude that neoclassical economics’ method does not produce (...) empirical conjectures. I assess and evaluate this finding in relation to the “rationality principle”, as it parallels neoclassical economics’ optimisation axiom. Furthermore, I explore Popper’s relevance in the context of neoclassical economics’ recent incorporation of behavioural economics’ insights to show that my analysis is not purely historical. (shrink)

In evolutionary medicine and other related fields, the concept of evolutionary mismatch is used to explain phenomena whereby traits reduce in adaptive value and eventually become maladaptive as the environment changes. This article argues that there is a similar problem of persistent adaptivity—what has been called the problem of evolutionary novelty—and it introduces the concept of mismatch resistance in order to explain phenomena whereby traits retain their adaptive value in novel environments that are radically different from the organisms’ environment of (...) evolutionary adaptedness (EEA). The possible role of variability selection in the evolution of mismatch-resistant traits is discussed, and it is suggested that mismatch resistance provides a useful tool for making progress on certain issues related to evolutionary theory, such as the modularity debate, cases of adaptivity outside of organisms’ ancestral environment, and the viability of naturalism as an overarching philosophical framework for understanding the natural world. (shrink)

Sociology aims to explain the emergence, persistence, and change of larger-scale social events, entities, properties, and processes. A vital element of this explanatory task is to connect the larger-scale changes to smaller-scale social properties and processes. Philosophers of social science usually employ the idea of a level to analyze the relation between macro and micro, which leads to misunderstanding the sociological micro-macro problem. Philosophical arguments often assimilate the micro-macro challenge into the problem of methodological individualism and treat it as analogical (...) to the relation between the physical and the mental. This presupposes that there is an individual level that is unique, comprehensive, and privileged, but these conditions are not satisfied. As an alternative, one should pay attention to the pragmatics of the micro-macro distinction, which is flexible, local, and relative. Once this is taken seriously, the motivation for assuming levels vanishes. Levels thinking creates problem substitutions rather than problem solutions. Furthermore, it supports a sterile style of theorizing. As an alternative, the paper suggests thinking about micro and macro in terms of scale and recognizing their heterogeneity. The concept of level is a placeholder, rather than as a theoretical concept. While figuring out relations between micro and macro is vital in the social sciences, it can be practiced without postulating levels. The paper concludes that a skeptical strategy towards levels is justified in the social sciences as the concept is heuristically misleading. To sustain necessary conceptual vigilance, social scientists should adopt the meta-heuristic of avoiding it. (shrink)

Living systems are complex systems made of components that tend to degrade, but nonetheless they maintain themselves far from equilibrium. This requires living systems to extract energy and materials from the environment and use them to build and repair their parts. They do so by regulating their activities on the basis of their internal and external conditions in ways that allow them to keep living. The philosophical and theoretical approach discussed in this book aims to explain these features of biological (...) systems by appealing to their organization. One of its distinctive features is that it addresses classical and more recent issues in philosophy of biology, from origins and definitions of life to biological teleology and functions, from an original perspective mainly focused on the living system, its physiology and behavior, rather than evolution. The book discusses and revises the conceptual foundations of this approach and presents an updated version of it. (shrink)

À partir de la question de savoir comment la science peut expliquer, ce texte pose la question à l’égard des formes d’enquêtes qui semblent inaptes à prédire. La question du modèle d’explication qui admettrait des données statistiques est ensuite confrontée aux idéaux rigoureusement prédictivistes et peut-être subrepticement déterministes. En discutant du modèle confirmationniste, on tente ici de tirer les conséquences de l’absence de procédure qui puisse venir disconfirmer en contexte probabiliste. C’est l’occasion de s’interroger sur le mode de résolution des (...) problèmes et défis dont fait montre la nature dans le but de reposer la question de la place de la téléologie eu égard à l’espace laissé oruvert par l’absence de procédures de validation. On est ainsi conduit à réinterroger la présence de schèmes d’économie d’énergie et d’optimalité qui rendent raison d’une anatomie transcendante, et puis finalement conduisent à s’interroger sur la place que tient la forme dans la vision que nous prenons de la nature. (shrink)

Why are quantum correlations so puzzling? A standard answer is that they seem to require either nonlocal influences or conspiratorial coincidences. This suggests that by embracing nonlocal influences we can avoid conspiratorial fine-tuning. But that’s not entirely true. Recent work, leveraging the framework of graphical causal models, shows that even with nonlocal influences, a kind of fine-tuning is needed to recover quantum correlations. This fine-tuning arises because the world has to be just so as to disable the use of nonlocal (...) influences to signal, as required by the no-signaling theorem. This places an extra burden on theories that posit nonlocal influences, such as Bohmian mechanics, of explaining why such influences are inaccessible to causal control. I argue that Everettian Quantum Mechanics suffers no such burden. Not only does it not posit nonlocal influences, it operates outside the causal models framework that was presupposed in raising the fine-tuning worry. Specifically, it represents subsystems with density matrices instead of random variables. This allows it to sidestep all the results (including EPR and Bell) that put quantum correlations in tension with causal models. However, this doesn’t mean one must abandon causal reasoning altogether in a quantum world. When decoherence is rampant and there’s no controlled entanglement, Everettian Quantum Mechanics licenses our continued use of standard causal models. When controlled entanglement is present---such as in Bell-type experiments---we can employ recently-proposed quantum causal models that are consistent with Everettian Quantum Mechanics. We never need invoke any kind of non-local influence or any kind of fine-tuning. (shrink)

According to the Principle of Sufficient Reason, every fact has an explanation. An important challenge to this principle is that it risks being a counterexample to itself. What explains why everything needs to be explained? My first goal is to distinguish two broad kinds of answers to this question, which I call “Humean Rationalism” and “Non-Humean Rationalism”. My second goal will be to defend the prospects of Humean Rationalism.

This book presents a novel pluralist strategy for answering Molyneux's 300+ year old conundrum: Would a person, born blind but given sight, identify a shape previously known only by their touch? The author interweaves historical scholarship with contemporary philosophical work and empirical research on animal, infant, and adult human perception. The author argues that we need a new approach to Molyneux's problem because we do not know what the problem is really about, and it is untestable because a Molyneux subject (...) cannot be physically realized. He criticizes Molyneux's question for its simplistic taxonomy of "the blind" that groups significant individual differences into a singular ontology. Research in the cognitive sciences confirms that various kinds of blindness can co-occur, such as ocular, cortical, and psychological blindness. Therefore, the author adopts an explanatory pluralism for answering Molyneux's problem, which includes no, yes, and 'no answer' answers according to the domain of inquiry being used. This account provides a research-based answer to a long-standing problem using previously unheeded insights particularly from animal crossmodal perception studies to retell a more complex story of perception: its levels of explanation and integration. A Pluralist's Guide to Solving Molyneux's Problem will be of interest to researchers and advanced students working in comparative psychology, epistemology, history of philosophy, philosophy of perception. (shrink)

In the natural and social sciences, it is common to use toy models—extremely simple and highly idealized representations—to understand complex phenomena. Some of the simple surrogate models used to understand opaque machine learning (ML) models, such as rule lists and sparse decision trees, bear some resemblance to scientific toy models. They allow non-experts to understand how an opaque ML model works globally via a much simpler model that highlights the most relevant features of the input space and their effect on (...) the output. The obvious difference is that the common target of a toy and a full-scale model in the sciences is some phenomenon in the world, while the target of a surrogate model is another model. This essential difference makes toy surrogate models (TSMs) a new object of study for theories of understanding, one that is not easily accommodated under current analyses. This paper provides an account of what it means to understand an opaque ML model globally with the aid of such simple models. (shrink)