Year and volume: 2025.

Author(s): Andreas Bilstrup Finsen; Jean Wagemans.

Abstract: Metaphors abound in scientific discourse. Well-known examples include ‘the brain as a computer’ and ‘the organism as a machine’. Such metaphors, we argue, have both a theoretical and a practical aspect: they may serve as explanatory models, but also guide technological development, influence policy, reflect ideological assumptions, and reshape how we understand ourselves. These practical dimensions have prompted growing concern about the risks associated with metaphor use in science. While this concern has been widely noted, less attention has been paid to the argumentative forms such criticism may take. This article addresses that gap by reconstructing resistance to scientific metaphors—specifically computer and machine metaphors—as a form of pragmatic argumentation, in which metaphor use is challenged on the basis of its practical consequences. It further shows how such argumentation may be supported by subordinate causal arguments that appeal to the metaphor’s highlighting/hiding structure. Drawing on the pragma-dialectical theory of argumentation, and analyzing examples from cognitive science, philosophy, and bioethics, the article demonstrates how metaphor resistance can be understood as a reconstructable form of argumentative critique—one in which metaphors become sites of normative contestation.

Doi: https://doi.org/10.1007/s10503-025-09675-y

Year and volume: 2026.

Author(s): Phillip H. Kieval.

Abstract: See the introduction to the article.

Doi: https://doi.org/10.1007/s10670-026-01111-1

Year and volume: 2026 (Vol. 91).

Author(s): Malvina Ongaro.

Abstract: Decision theories have largely ignored the step of decision making in which the agent models the situation. Given that a decision can be represented with different models, and that these can lead to different recommendations, then without a principled way to assess them the agent’s choice is under-determined. As models require the agent to select the aspects that matter to the decision, an account of rational decision modelling must include a notion of relevance. I propose that the most rational model is the one taking into account all and only the considerations relevant for the decision. I define relevance for a decision as a matter of providing reasons for some option, and I identify four functional types of reasons leading to four corresponding types of relevance. I focus on what I call “constitutive relevance”, which provides the content of the decision model, and propose a formal definition of this concept: the central idea is that the model should include all and only those considerations the inclusion of which changes the utility of at least one of the alternative options.

Doi: https://doi.org/10.1007/s10670-025-00964-2

Year and volume: 2025 (Vol.62).

Author(s): Emanuele Ratti; Mark Graves.

Abstract: We propose a conceptualization and implementation of AI ethics via the capability approach. We aim to show that conceptualizing AI ethics through the capability approach has two main advantages for AI ethics as a discipline. First, it helps clarify the ethical dimension of AI tools. Second, it provides guidance to implementing ethical considerations within the design of AI tools. We illustrate these advantages in the context of AI tools in medicine, by showing how ethics-based auditing of AI tools in medicine can greatly benefit from our capability-based approach.

Doi: https://doi.org/10.5406/21521123.62.1.01

Year and volume: 2025 (Vol. 5).

Author(s): David B. Resnik; Mohammad Hosseini.

Abstract: Using artificial intelligence (AI) in research offers many important benefits for science and society but also creates novel and complex ethical issues. While these ethical issues do not necessitate changing established ethical norms of science, they require the scientific community to develop new guidance for the appropriate use of AI. In this article, we briefly introduce AI and explain how it can be used in research, examine some of the ethical issues raised when using it, and offer nine recommendations for responsible use, including: (1) Researchers are responsible for identifying, describing, reducing, and controlling AI-related biases and random errors; (2) Researchers should disclose, describe, and explain their use of AI in research, including its limitations, in language that can be understood by non-experts; (3) Researchers should engage with impacted communities, populations, and other stakeholders concerning the use of AI in research to obtain their advice and assistance and address their interests and concerns, such as issues related to bias; (4) Researchers who use synthetic data should (a) indicate which parts of the data are synthetic; (b) clearly label the synthetic data; (c) describe how the data were generated; and (d) explain how and why the data were used; (5) AI systems should not be named as authors, inventors, or copyright holders but their contributions to research should be disclosed and described; (6) Education and mentoring in responsible conduct of research should include discussion of ethical use of AI.

Doi: https://doi.org/10.1007/s43681-024-00493-8

Year: 2026.

Editor(s): Steven S. Gouveia.

Description: This Handbook explores the ethical dimensions of Artificial Intelligence (AI) across philosophical, legal, and applied perspectives. Bringing together leading scholars and practitioners, the handbook examines key issues in this field, including algorithmic bias, privacy, responsibility, and AI’s impact on human rights and democracy. It also explores sector-specific challenges in healthcare, law, finance, art and many more, offering a multidisciplinary approach to AI Ethics. With a balance of theoretical insights and practical studies and with a diversity of authorship, this handbook serves as an essential resource for academics, policymakers, and technology professionals navigating the ethical challenges of AI in the 21st century.

Publisher: Palgrave Macmillan Cham.

Doi: https://doi.org/10.1007/978-3-032-15112-4

Year: 2010.

Author(s): Stephen Biddle.

Abstract: In war, do mass and materiel matter most? Will states with the largest, best equipped, information-technology-rich militaries invariably win? The prevailing answer today among both scholars and policymakers is yes. But this is to overlook force employment, or the doctrine and tactics by which materiel is actually used. In a landmark reconception of battle and war, this book provides a systematic account of how force employment interacts with materiel to produce real combat outcomes. Stephen Biddle argues that force employment is central to modern war, becoming increasingly important since 1900 as the key to surviving ever more lethal weaponry. Technological change produces opposite effects depending on how forces are employed; to focus only on materiel is thus to risk major error—with serious consequences for both policy and scholarship.

In clear, fluent prose, Biddle provides a systematic account of force employment’s role and shows how this account holds up under rigorous, multimethod testing. The results challenge a wide variety of standard views, from current expectations for a revolution in military affairs to mainstream scholarship in international relations and orthodox interpretations of modern military history.

Military Power will have a resounding impact on both scholarship in the field and on policy debates over the future of warfare, the size of the military, and the makeup of the defense budget.

Publisher: Princeton University Press.

URL: https://press.princeton.edu/books/ebook/9781400837823/military-power

Year: 2016.

Author(s): Patrick Thaddeus Jackson.

Abstract: The Conduct of Inquiry in International Relations provides an introduction to the philosophy of science issues and their implications for the study of global politics. The author draws attention to the problems caused by the misleading notion of a single unified scientific method, and proposes a framework that clarifies the variety of ways that IR scholars establish the authority and validity of their empirical claims. Jackson connects philosophical considerations with concrete issues of research design within neopositivist, critical realist, analyticist, and reflexive approaches to the study of world politics. Envisioning a pluralist science for a global IR field, this volume organizes the significant differences between methodological stances so as to promote internal consistency, public discussion, and worldly insight as the hallmarks of any scientific study of world politics.

In this second edition, Jackson has centralised the philosophical history of the ‘science question’ into a single chapter, providing a clearer picture of the connections between contemporary concerns about the status of knowledge and classic philosophical debates about the relationship between human beings and the world they inhabit. The central chapters feature more detailed and pedagogically useful illustrations of the methodological positions discussed, making the book even better suited to clarify the philosophical distinctions with respect to which a scientific researcher must locate herself.

The second edition will continue to be essential reading for all students and scholars of International Relations, Political Science and Philosophy of Science.

Publisher: Routledge.

Doi: https://doi.org/10.4324/9781315731360

Year and volume: Forthcoming.

Author(s): Amit Karmon.

Abstract: The standard Bayesian solution to the paradox of the ravens maintains that the degree of confirmation provided by seeing a non-black non-raven is positive but negligible compared to that provided by seeing a black raven. I show that, unless we impose severe and unmotivated restrictions on the subject’s priors, this has the consequence that the cumulative confirmation provided by all the non-black non-ravens the subject expects to see is non-negligible compared to the cumulative confirmation provided by all the black ravens the subject expects to see. If this is so, however, then the paradox retains its full force.

Doi: https://doi.org/10.1017/psa.2026.10207

Year and volume: 2020 (Volume 87).

Author(s): Mathias Frisch.

Abstract: Using climate policy debates as a case study, I argue that a certain response to the argument from inductive risk, the hedging defense, runs afoul of a reasonable ethical principle: the no-passing-the-buck principle according to which scientists ought to offer their scientific judgment when such judgment is both possible and needed in public policy debates.

Doi: https://doi.org/10.1086/710538