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Perturbative Causality
Full text linkThis paper examines the development of causal perturbation theory, a reformulation of perturbative quantum theory (QFT) starting from a causality condition rather than a time-evolution equation. We situate this program alongside other causality-based reformulations of relativistic quantum theory which flourished in the post-war period, contrasting it in particular with axiomatic QFT. Whereas the axiomatic QFT tradition tried to move beyond the perturbative expansion, causal perturbation theory can be thought of as a foundational investigation of this approximation method itself. Otur reconstruction of this forgotten research program offers new perspectives on contemporary debates about relativistic causality conditions and the problem of ultraviolet divergences
Extrapolating other consciousnesses: the prospects and limits of analogical abduction
Full text linkAdvances in animal sentience research, neural organoids, and artificial intelligence reinforce the relevance of justifying attributions of consciousness to non-standard systems. Clarifying the argumentative structure behind these attributions is important for evaluating their validity. This paper addresses this issue, concluding that analogical abduction – a form of reasoning combining analogical and abductive elements – is the strongest method for extrapolating consciousness from humans to non-standard systems. We argue that the argument from analogy and inference to the best explanation, individually taken, do not meet the criteria for successful extrapolations, while analogical abduction offers a promising approach despite limitations in current consciousness science
Transitioning Regulatory Kinds: Why Gender Transition Isn’t Analogous to ‘Race Transition’
Full text linkThis article offers a hybrid account of regulatory kinds and subjective fit to explain why the oft-invoked analogy between gender transition and so-called race transition fails both conceptually and normatively. The argument—recently circulated in popular commentary and endorsed by figures such as Richard Dawkins—suggests that if gender transition is legitimate on the basis of social construction, then racial transition should be equally so. Yet since racial transition is generally regarded as illegitimate, the analogy concludes that gender transition must be suspect. I argue that this inference rests on a category error: it conflates social construction with norm-governed intelligibility. Drawing on Brewer’s framework of regulatory kinds, I show that while both race and gender are socially constructed kinds, they are constituted by distinct clusters of norms regulating membership, uptake, and legitimacy. Gender, as a regulatory kind, includes historically evolving norms that accommodate agent-led transitions—reflecting the social uptake of authenticity, lived identity, and self-determination. Race, by contrast, embeds genealogical and cultural norms that systematically exclude such transitions from intelligibility. I supplement this account with Cosker-Rowland’s theory of subjective fit to illuminate why the phenomenological texture of gender identity has become central to normative recognition, whereas race has not. By clarifying the regulatory asymmetry between these kinds, the paper shows that the race/gender analogy fails not because the categories differ in kind or in construction, but because their underlying normative architectures license different forms of legitimate change. Recognizing this distinction is not merely a matter of conceptual hygiene, but a moral and political necessity
In defense of reliabilist epistemology of algorithms
Full text linkIn a reliabilist epistemology of algorithms, a high frequency of accurate output representations is indicative of the algorithm’s reliability. Recently, Humphreys challenged this assumption, arguing that reliability depends not only on frequency but also on the quality of outputs. Specifically, he contends that radical and egregious misrepresentations have a distinct epistemic impact on our assessment of an algorithm’s reliability, regardless of the frequency of their occurrence. He terms these statistically insignificant but serious errors (SIS-Errors) and maintains that their occurrence warrants revoking our epistemic attitude towards the algorithm’s reliability. This article seeks to defend reliabilist epistemologies of algorithms against the challenge posed by SIS-Errors. To this end, I draw upon computational reliabilism as a foundational framework and articulate epistemo logical conditions designed to prevent SIS-Errors and thus preserve algorithmic reliability
24 Philosophical Issues in Medical Imaging
Full text linkThis chapter aims to shed light on the normative questions raised by medical imaging (MI), paving the way for interdisciplinary dialogue and further philosophical exploration. MI comprises noninvasive techniques aimed at visualizing internal human body structures to aid in explanation, diagnosis, and monitoring of health conditions. MI requires interpretation by specialized professionals, and is routinely employed across medical disciplines. It is entrenched in clinical guidelines and therapeutic interventions. Moreover, it is a dynamic research field, witnessing ongoing technological advancements. After surveying philosophical issues arising from MI, which are relatively unexplored, the chapter focuses on the epistemology of diagnostic imaging. Specifically, it delves into what constitutes an image as evidence and how radiological procedures generate knowledge. The discussion dissects three facets of the radiological process: image interpretation, radiological reporting, and semantic analysis. Each facet carries distinct epistemic implications, as errors can manifest in various ways, affecting the acquisition of patient-relevant knowledge
On Axiological Loneliness
Full text linkRecently, Alvarado (2024) provided a conceptual framework to individuate and identify a specific kind of loneliness, namely epistemic loneliness. According to him, epistemic loneliness arises in virtue of and responds primarily to an absence of epistemic partners— i.e., willing, able, and actually engaged epistemic peers — as well as the lack of opportunities to engage with such. In this paper I argue that Alvarado’s framework and conceptual analysis of epistemic loneliness allows us to identify yet another kind of loneliness, namely one that can only be addressed at an axiological level. As we will see, this loneliness arises in virtue of and is particularly responsive to value-affirming, value-creating, and value exchanging circumstances, peers and contexts. Given its source and the factors which have an effect on it (either increase it or decrease it), this kind of loneliness is significantly distinct from epistemic loneliness. As will be shown here, we can have axiologically antagonistic epistemic partners. If this is so, it is possible that one can have epistemic partners, in the sense defined by Alvarado, and still be axiologically lonely. Axiological loneliness may prove to be even more central than epistemic loneliness already is to a person’s social, psychological and personal sense of belonging and hence of well-being
Aimless Progress and the Myth of the Constitution-Promotion Distinction
Full text linkA central question in philosophy of science and epistemology of science concerns the characterization of the progress of science. Many philosophers of science and epistemologists have developed accounts of scientific progress, laying down desiderata for and providing success criteria of any account of scientific progress. Extant accounts of scientific progress are surveyed and critically assessed and it is shown that all face the same problem. The constitution-promotion distinction – a commitment shared by all the accounts – is identified as the root of the problem for the extant accounts. In their place, a novel way of understanding scientific progress – inspired by pragmatic philosophy of science and zetetic epistemology – which rejects the problematic constitution-promotion distinction, and importantly, which provides a vision of scientific progress without depending on the aim of science is developed
Intervention and Experiment
Full text linkThe received view of scientific experimentation holds that science is characterized by experiment and experiment is characterized by active intervention on the system of interest. Although versions of this view are widely held, they have seldom been explicitly defended. The present essay reconstructs and defuses two arguments in defense of the received view: first, that intervention is necessary for uncovering causal structures, and second, that intervention conduces to better evidence. By examining a range of non-interventionist studies from across the sciences, I conclude that interventionist experiments are not, ceteris paribus, epistemically superior to non-interventionist studies and that the latter may thus be classified as experiment proper. My analysis explains why intervention remains valuable while at the same time elevating the status of some non-interventionist studies to that of experiment proper
Decidable and Undecidable in Quantum Mechanics
Full text linkThis work shows that the ontic-epistemic dichotomy is insufficient to capture the different levels of ignorance and their implications for probability theories. It proposes an essentially epistemic interpretation of quantum mechanics, built on an operational basis firmly anchored to experimental data and scientific methods. This approach enables a rigorous treatment of numerical values obtained from experiments without resorting to unnecessary ontological or metaphysical assumptions
A Literary Illusion: Artificial Literature
Full text linkThis study examines how large language models (LLMs) transform knowledge and literature from a technocentric perspective. While LLMs centralize human knowledge and reconstruct it in a relational memory framework, research indicates that when trained on their own data, they experience “model collapse.” Experiments reveal that as generations progress, language deteriorates, variance decreases, and perplexity increases. While humans refine their language through reading, machines encounter epistemological ruptures due to statistical errors. Artificial literature diverges from human literature; machine-generated texts are a literary illusion. LLMs can be regarded as a technological phenomenon that instrumentalizes human knowledge, tilting the subject-object balance in favor of the machine and creating its own “culture.” They signal a shift from a human-centered paradigm to a knowledge-centered approach. This study questions the boundaries of artificial literature and whether machine language can be considered “knowledge,” while exploring the transformations in the human-machine relationship