Philosophy of Science

Abstract The study of the certainty and inexorability of mathematical theorems is one of the important topics in the philosophy of mathematics. Various schools such as logicism, intuitionism, Platonism and naturalism have tried to present theories on this subject. These schools usually seek the foundation for mathematics in order to justify the certainty of mathematical theorems and logic. This has always been accompanied by numerous failures. In this article, we try to examine this issue from Wittgenstein's point of view. That is, instead of asking "What is the foundation of logic and mathematics?" we ask "Why does mathematics need the foundation?". Therefore, we first examine foundationalism. Then we show that mathematics is a language-game. In this regard, we examine geometry and logic as two language-games in mathematics. Finally, we show that, according to Wittgenstein's philosophy, the certainty and inexorability of a valid inference or a correct calculation comes from the practical procedure of inference and calculation.

Abstract Drawing on Daniel Dennett’s intentional stance, Christian List advances a pragmatist framework according to which any system—human or artificial—that satisfies three macro-level conditions—intentional agency, alternative possibilities, and causal control—may be ascribed free will, even in the absence of phenomenal consciousness. Employing conceptual analysis and engaging with prominent critiques in the philosophical literature—including Robert Kane’s account of the origination problem, Nancey Murphy and Warren Brown’s critiques of downward causation and emergence, and empirical findings by Eddy Nahmias on the role of P. F. Strawson’s reactive attitudes in free will ascription—this paper argues that List’s framework suffers from a structural ambiguity in distinguishing between “functional autonomy” and “responsibility-grounding free will.” Reducing free will to mere “explanatory sufficiency” not only results in conceptual inflation but also opens the door to “algorithmic responsibility evasion,” whereby developers and institutions may deflect accountability by appealing to the system’s agency. In response, the paper proposes a three-level framework that distinguishes functional autonomy (Level 1), robust free will (Level 2), and moral responsibility (Level 3), and introduces a threshold condition for robust free will: the capacity to revise one’s ultimate ends in light of evaluative commitments. This condition presupposes phenomenal consciousness and P. F. Strawson-style reactive attitudes, thereby clarifying why no contemporary artificial system—even the most advanced language models—possesses robust free will. By resolving the ambiguity in List’s account, the proposed distinction carries important normative implications for AI ethics, legal responsibility, and technology policy.

Abstract About two decades ago, “The Gap of Responsibility” as a problem was firstly introduced by Matthias for referring to an ethical challenge of AI. Due to their ability to learn, AI technologies are able to function beyond the control and anticipation of designers and users. Matthias argues that in this case, the necessary and sufficient conditions of responsibility wouldn’t be satisfied neither for designers, nor for users. And that is the gap of responsibility. The problem of responsibility gap has invited many researchers to explore for solutions. There is significant divergence among current accounts of responsibility gap, which mainly results from their basic theoretical assumptions. In this paper, we categorize the responses to three approaches: dissolving the problem, filling the gap by attributing responsibility to AI, and filling the gap by attributing responsibility to human agents. By analyzing the social and practical aspects of the concept of responsibility, we defend a compound, contextual, and gradual notion of responsibility. On this basis, we claim that two first approaches are not successful, due to being grounded on the poor concepts of responsibility. Hence, the third approach is more plausible. Moreover, since in the familiar cases of responsibility gap we fill the gap through revising social roles, in the case of AI-based responsibility gap we can follow the similar solution too, as suggested in some works of the third approach. Finally, we discuss some of remained challenges for the third approach.

Abstract A social subject, such as the university, is involved in a wide range of issues, and social research on the university is conducted to address them. In the studies, multiple methods are used, each of which can examine the university only from a specific perspective and with an emphasis on specific concepts. Government sponsors and industrial investors, who are only interested in some of the university's functions, also support only the research they are interested in, thereby leading to the more “valuable”, more prominent, and more strengthened concepts that are important to those investors and sponsors outside the university. The result of such a process is the destruction of the university's internal norms and, as a consequence, scientific and financial misconduct. For decades, critical theory scholars have been concerned with this issue: the importance of considering the totality of a social issue rather than addressing only a specific aspect. The present article, by describing the methodology of critical theory, and by presenting a discussion of Iranian university-related researches, claims that Iranian traditional (positivistic) researches, by highlighting some interests of specific groups, and eliminating public considerations, such as ideas related to the ethics of science, may lead to the weakening of the functioning, or even the collapse, of the institution of science and the university.