Foundations of Science最新文献

Abstract

Recent developments in artificial intelligence urge clarification of its ethical and legal status. The issue revolves around the concept of subjectness, distinguishing active and responsible conduct from inert performance. We analyze this notion from a physical viewpoint, building on the quantum-theoretic refinement of the concept of uncertainty into quantum and classical types: quantum uncertainty refers to an objective freedom to construct the future, while classical uncertainty denotes subjective ignorance of present states of nature. Subjectness of intelligence is then defined by the kind of uncertainty it is capable to resolve. To analyze different aspects of intelligence, quantum-inspired definitions of decision, subjectness, originality, and meaning are introduced on this basis. These concepts are first calibrated on natural intelligence and then applied to artificial systems, classified as classical and quantum. Classical AI then appears fundamentally alien to subjectness due to its algorithmic nature, limited to the resolution of classical uncertainty. Quantum AI, in contrast, breaks this limit by hosting some degree of proto-subjectness on the level of elementary particles, involved in its operation. Fundamentally, our approach tracks alternative views on subjectness of intelligence to the interpretations of quantum randomness, identifying both as different sides of the same ethical dilemma. Quantum physics then provides fertile ground for possible solutions, aligned with Eastern and Western views on freedom and constraint, subject and context in social life. These results offer a scientific approach to the controversial challenges of socio-technological development, integrating physical and humanitarian perspectives.

The article focusses on grey system theory and its methodological foundations. Key topics include: axiomatisation of the concept of grey, comparison of grey systems theory with fuzzy logic and probabilistic approaches, and methodological development of the systems approach in grey data modelling. The article discusses in detail the challenges of defining grey space, grey functions, and their applications in solving the methodological problems of grey systems theory. The differences between grey systems theory and other analytical methodologies are highlighted, paying attention to the specifics of the data and the research context and epistemological perspective.

In 1976, I met John Bell several times in CERN and we talked about a possible violation of optical theorem, purity tests, EPR paradox, Bell’s inequalities and their violation. In this review, I resume our discussions, and explain how they were related to my earlier research. I also reproduce handwritten notes, which I gave to Bell during our first meeting and a handwritten letter he sent to me in 1982. We have never met again, but I have continued to discuss BI-CHSH inequalities and their violation in several papers. The research stimulated by Bell’s papers and experiments performed to check his inequalities led to several important applications of quantum entanglement in quantum information and quantum technologies. Unfortunately, it led also to extraordinary metaphysical claims and speculations which in our opinion John Bell would not endorse today. BI-CHSH inequalities are violated in physics and in cognitive science, but it neither proved the completeness of quantum mechanics nor its nonlocality. Quantum computing advantage is not due to some magical instantaneous influences between distant physical systems. Therefore one has to be cautious in drawing-far-reaching philosophical conclusions from Bell’s inequalities. The true resource for quantum computing is contextuality and not nonlocality.

Abstract

The question of whether mathematics depends on experience, including experience of the external world, is problematic because, while it is clear that natural sciences depend on experience, it is not clear that mathematics depends on experience. Indeed, several mathematicians and philosophers think that mathematics does not depend on experience, and this is also the view of mainstream philosophy of mathematics. However, this view has had a deleterious effect on the philosophy of mathematics. This article argues that, in fact, the view is not valid. Mathematics depends on experience because experience influences the making of mathematics, indeed much mathematics arises from experience and is evaluated on the basis of experience.

Pictorial representations such as diagrams and figures are widely used in scientific literature for explanatory and descriptive purposes. The intuitive nature of pictorial representations coupled with texts foster a better understanding of the objects of study. Biological mechanisms and processes can be clearly illustrated and grasped in pictures. I argue that pictorial representations describe biological phenomena by telling stories. I elaborate on the role of narrative structures of pictures in the frontier research using a case study in immunology. I articulate that pictures with an inherent narrative structure are crucial in biological sciences.

In this paper we present a paradigmatic example of the use in knowledge management of techniques from other fields, namely mathematical analysis. We also highlight that the Jacobi method presented here takes precedence over the better known Hungarian method. Finally, we signify that the Jacobi method represents the first known or recognized case of serendipity in both knowledge management and operational research. This paper thus demonstrates the intersection between knowledge management, mathematical analysis and operational research and how taking historical perspectives are important for recognising future applications of knowledge management. This results in a better understanding of knowledge management and how it can be applied in the future. It has been shown how knowledge management relates to historical mathematical principles.

In this paper, we examine the issue of the empirical or non-empirical status of philosophical metatheories. In particular, we ask whether a specific type of metatheoretical product, formal reconstructions of scientific theories, can be empirically tested. To answer this, we take Metatheoretical Structuralism as a metatheory and Classical Mechanics as our case studies. We show how classical mechanics can be reconstructed from structuralism. We then present a computer program, called Reconstructor, and show how it can be used to test the adequacy of the reconstruction. Finally, we discuss some philosophical points regarding these tests, namely, the issues of holism, circularity and metatheoretical predictions.

Insofar as disagreement may in principle regard most of (maybe all) facets of information system ontologies’ [ISOs] debate, it may also produce a plurality of views – sometimes inconsistent with each other – on ISOs’ development and design. This paper analyzes a view that makes the recognition of – and provides a theoretical foundation for – such a plurality of views a trademark: perspectivism (on ISOs). The aim is to show what exactly endorsing perspectivism consists of, and how perspectivism differs from different, competing views. Section 2 introduces the main claims of perspectivism, and remarks that perspectivism mainly deals with ISOs’ development and design. As for ISOs’ development, Sect. 3 considers domain’s partition and systematization, by distinguishing perspectivism from realism and relativism. Section 3 also shows that perspectivism implies some sort of variantism on ISOs’ representational primitives, about which perspectivism may not differ from its rivals. As for the ISOs’ design, Sect. 4 points out that despite perspectivism grants the possibility to use any procedural approach, principle, and ontological language, it is not committed to uphold that all those approaches, principles, and languages are legitimate. Finally, Sect. 5 focuses on both perspectivism’s weaknesses and (theoretical) contribution to ISOs’ debate.

I identify two versions of the scientific anti-realist's selectionist explanation for the success of science: Bas van Fraassen's original and K. Brad Wray's newer interpretation. In Wray's version, psycho-social factors internal to the scientific community - viz. scientists' interests, goals, and preferences - explain the theory-selection practices that explain theory-success. I argue that, if Wray's version were correct, then science should resemble art. In art, the artwork-selection practices that explain artwork-success appear faddish. They are prone to radical change over time. Theory-selection practices that explain theory-success in science are however not faddish. They are mostly stable; that is, long-lived and consistent over time. This is because scientists (explicitly or implicitly) subscribe to what I will call the testability norm: scientific theories must make falsifiable claims about the external physical world. The testability norm and not psycho-sociology explains the theory-selection practices that explain theory-success in science. Contra Wray, scientific anti-realists can then maintain that the external physical world (as expressed in the testability norm) explains theory-success.

Supplementary information: The online version contains supplementary material available at 10.1007/s10699-023-09907-y.