This article provides an analytical review of the collective monograph “Science Communication and Trust”, edited by Antoinette Fage-Butler, Loni Ledderer, and Kristian H. Nielsen. The monograph is distinguished by its interdisciplinary scope and by the integration of both theoretical and empirical approaches. Drawing on one of the book’s central perspectives, the review foregrounds the contemporary socio-epistemological understanding of (dis)trust as a complex, multidimensional, and context-dependent phenomenon, moving beyond the simplistic binary of “trust versus distrust”. I focus on the conceptualization of non-binary (dis)trust – how this perspective is articulated throughout the chapters and how different forms and dynamics of (dis)trust are illustrated through concrete empirical approaches, including quantitative and qualitative research, case studies, and discourse analysis. The study highlights the authors' re-examination of scientific denialism, viewing it as a socially and narratively constructed process in which a specific type of trust – embodied by the “dissident expert” – emerges as a symbol of epistemic democracy. In conclusion, I discuss both strengths and limitations of the book: on the one hand, its non-binary framework enables a nuanced analysis of trust and distrust as they actually circulate in society; on the other hand, this approach can sometimes result in postmodern ambivalence and a lack of clear answers to the challenges considered. Overall, the article emphasizes the theoretical and practical value of the book for scholars in STS, practitioners, and everyone interested in the complexities of public (dis)trust in science in the context of infodemics and socio-political transformations.
The article examines Michael Dummett’s interpretation of the ontology of time within his anti-realist project and the manifestation argument. The analysis begins with the distinction between two versions of anti-realism – T and G – which are here reconstructed on the basis of Dummett’s semantics as different ways of reconciling the manifestation principle with the idea of the past. The first strategy seeks to preserve rational discourse about the past while weakening its ontological status; the second radicalizes anti-realism, making the past entirely dependent on present linguistic and cognitive practices. Their comparison reveals the structural limits of Dummett’s anti-realist framework: any attempt to combine logical rigor with epistemic accountability generates tension between the stability of meaning and the stability of being. A central focus of the paper is the manifestation argument, according to which knowledge of meaning must be exhibited in linguistic behaviour. Through this principle, Dummett exposes a deep correlation between epistemology and ontology: if the meaning of an utterance is determined by the conditions under which it can be verified, temporal reality itself can no longer be conceived as an independent metaphysical background. Within this framework, unverifiable statements emerge not merely as a test case for distinguishing realism from anti-realism, but as a stress point that reveals the internal limits of the anti-realist position. The stricter anti-realism adheres to the manifestation principle, the closer it approaches the denial of the past as a stable domain of reality. Dummett’s two strategies mark this movement in opposite directions: T constructs a field of “possible histories” sustained by evidential coherence, whereas G dissolves the very distinction between epistemic and ontological levels. Thus, Dummett’s anti-realism does not abolish metaphysics but relocates it into the linguistic domain, where language itself becomes the site through which temporal being is constituted.
The digital today constitutes an environment of affects: it touches, enchants, captivates, incites, and frightens. What it does not do, however, is provide knowledge; rather, it takes knowledge away. Previously, the subject of cognition was the human being, though cognition itself was largely grounded in institutions, social contacts, performative rituals, and the activity of human-scale and non-human-scale collectives. Today, however, when generative AI is prone to hallucinations, when AI models are trained on content produced by other AIs – thereby accumulating errors and generating model collapse – and when algorithmic feeds and AI assistants make epistemic decisions on behalf of users by determining what is “important” or “true”, the machines of technocapitalism rupture the “contract” between human and non-human agents and monopolize the right to meaning. The fundamental stratum of reality upon which social consensus depends – namely, the experience of everyday life – becomes dubious and alien. Hence, in the context of a crisis of meaning, the right to presence assumes renewed urgency. Indeed, knowledge and science, in their foundational dimensions, are not merely a matter of institutions but rather of the ultimate aspirations of the human being – aspirations that are pre-predicative and existential in character. To this sphere belong the mystery of life, reverence before it, fate, aura – in short, the entire incomputable remainder: that ontological correlate which can be counterposed to the fatalism of algorithms and to epistemic nihilism. I seek to demonstrate that, in the era of intelligent machines, the epistemic rupture may be overcome, or at least mitigated, through a stance that may be termed existential romanticism – one in which knowledge is conceived not solely as resource, prediction, and possession, but also as event, risk, and a breakthrough toward the improbable.
This article examines the grounds for determining whether narrative can be recognized, following L. Mink, as a legitimate instrument of cognition. The primary obstacle to such recognition lies in the claim that while narratives, like scientific hypotheses, are the result of productive imagination, narrative interpretations – unlike hypotheses – cannot be confirmed or falsified. Individual statements may be verified, but a narrative is not reducible to the sum of its statements. The article demonstrates that Mink’s understanding of narrative can be developed by drawing on the analytical approach of A. Danto and the hermeneutic approach of P. Ricoeur. In this light, narrative emerges as a complex intellectual construct whose core consists in the representation of processes. The hypothesis advanced is that narrative as an instrument of cognition constitutes a highly organized form of hypothesis, one that enables the conceptualization of multifactorial, self-reinforcing processes of development within human communities.
The article begins with several critical remarks about Konstantin Ocheretyany’s paper. The conclusion of these remarks is that the dangers presented in the article under discussion, in the spirit of epistemic pessimism, are not frightening, and the problems raised are much older than the emergence of language models. The article is conceived in terms of expansion, although the conclusion seems to contrast competition for knowledge with “standing silently before the mystery”. The author sees a way out in the attitude of existential romanticism. The latter, however, presupposes a set of techniques that can only produce limited effectiveness. This article proposes an alternative: since language models today pass the Turing test quite successfully, we cannot accept large language models as a tool, and we must describe interaction with them as distributed knowledge. For objects of distributed knowledge, it is essential whether this object is accessible to everyone or whether it cannot be accessible to everyone or even many (such as secrets). Since interaction with large language models, in our view, belongs to the second class, we will need to pursue a corresponding strategy. Finally, we propose an improvement to the Turing test, the Pico test, which would require the test subject to describe a selected object (for example, a literary work) in as much detail as possible and subsequently change their perspective in describing and interpreting it. The tester would need to pay attention to the natural difficulty humans have in abandoning their initial position, whereas a machine would be more easily able to change perspective, description, and style.
