Philosophy of Science

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 In science and technology studies, the agency of technology has largely been confined to its role in rearranging social relations and human–nonhuman networks, while its influence on the selection and transformation of theoretical frameworks has received far less attention. Through a case study of blockchain studies as an emerging technology, and by introducing the concept of the “theory–technology dialectic,” this paper demonstrates that technology can play a role in shaping, modifying, and displacing the theories researchers employ. The arguments of this paper show that no single theoretical framework is capable of explaining all dimensions of emerging technologies such as blockchain, and researchers are compelled to draw simultaneously on diverse theories. This situation reflects a kind of “theoretical flexibility” when confronting complex technologies. Ultimately, the paper proposes “theoretical assemblage” as a methodological strategy for studying emerging technologies and points to its Methodological implications for the field of technology studies.

Abstract In the development of risky technologies, such as genetic modification organisms, the issue is that the value of safety cannot be ethically ignored and the users/consumers of risky technological artifacts should not be exposed to a risk beyond a certain threshold. On the other hand, technology policymakers generally view ethical considerations as abstract claims and as obstacles to economic and technological growth. All together considering ethical considerations and the perspectives of all stakeholders in policymaking on risky technologies, without leading to the halt of these projects, requires a multilateral, multi-layered and well-ballanced approach. To this end, this article proposes a policy approach corresponding to John Rawls' philosophical theory, and finally, within this framework, the process of developing genetic modification organisms in Iran and its challenges are examined.

Abstract The transformation of reading tools and text medium —from printed paper books to e-readers and digital screens— is not merely a technological shift; it brings about a profound change in the perceptual and cognitive experience of the human reader. This article, drawing on contemporary phenomenological approaches in cognitive science, introduces and analyzes the concept of “embodied reading.” This concept highlights how the act of reading, depending on its material substrate, engages the reader’s mind and body in different ways and shapes their semantic experience. In traditional reading, not only vision but all human senses are activated in encountering the book, serving as material anchors for memorizing and decoding information. This sensory engagement creates a spatial and temporal sense of presence for the text, functioning as a scaffold for imagination and mental imagery. Language, too, is saturated with orientational and embedded metaphors. We learn and understand language through our bodily interaction with the world, and we recall our perceptual and emotional experience through recollection of our bodily situation in the environment. In contrast, digital texts, by reducing materiality and physicality, diminish this sensory involvement and challenge the cognitive and memory structures associated with it. Moreover, the weakening of the book’s integrity and coherence as a unified entity affects the reader’s sense of familiarity and control. Thus, different reading technologies and media are not mere carriers of information; they have specific affordances for the practice of reading and lead to different user experiences.

Abstract Proponents of objectivity, by calling upon scholars and obliging them to eliminate subjective characteristics in their engagement with natural and social phenomena, have promised the attainment of "true" theories that correspond and align with "reality." Numerous philosophers and scholars of science have critiqued this claim and rejected the possibility of its realization. With the emergence of artificial intelligence systems, and owing to their remarkable and unprecedented capabilities, the question of the feasibility of achieving objectivity is once again raised. This article examines the concept of objectivity by reflecting on prominent conceptions of artificial intelligence, particularly its applications in the field of urban planning—systems which, according to Stuart Russell and Peter Norvig's classification, fall under the category of those that "act rationally." It appears that in supervised forms of AI systems, the realization of objectivity is impossible for several reasons, including the value alignment problem. In unsupervised forms, the influence of subjective or intersubjective factors becomes deeper and more complex. Technological efforts to approach this goal in more advanced AI systems are not only improbable but would also approximate a dangerous condition.

Abstract There exists a significant conceptual distinction between science and technology. This article examines the philosophical grounds underlying the conflation of science and technology. It suggests that treating the two as identical is not merely an epistemological confusion; rather, it may lead to a range of undesirable theoretical and practical consequences. From an epistemological perspective, the paper also argues, the notion of 'applied science' may be regarded as redundant, as it falls within the category of technology.