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

Year and volume: 2026.

Author(s): Avigail Ferdman.

Abstract: Philosophers are grappling with whether artificial intelligence (AI) systems should be permitted to participate in high-stakes moral and political decisions. I draw on Alasdair Macintyre’s political philosophy to resist this possibility. AI cannot qualify as a moral agent or a moral advisor because it cannot participate in reflective deliberations on common goods. Common goods are constitutive of individual goods, since individuals can only reason about their own good as ‘individuals-in-their-social-relationships’, involved in practical activity of common practices. Common practices have goods internal to the practice that can only be achieved in common. This requires cultivating and exercising relational capacities. Increasingly, AI is mediating social relations, doing so in a disembodied manner. AI mediation risks fragmenting social interaction and deskilling the relational capacities necessary for common practices. I demonstrate how this threat might unfold in the context of the common good of knowledge. Knowledge can be perceived as an ‘epistemic commons’: the sharing in the production of knowledge as a common good, with ‘care-taking’ as a fundamental good internal to the practice. This involves the accumulated (often embodied) wisdom of communities of practices sharing a common commitment to listening, thinking, examining, and talking about what is said in the name of knowledge because they care. A tragedy of the epistemic commons occurs when knowledge is pursued for achieving goods external to the practice—money, fame, power, dopamine—things that currently dominate social media practices and AI training. What is more, training future AI on reliable information is insufficient, since AI cannot participate in neither the shared valuing of common knowledge, nor the shared valuing of care-taking practices of common knowledge. Given AI mediation and disembodiment, AI-generated knowledge risks creating distance, distrust and “ir-reciprocity” between humans, undermining the prospects for a ‘common practical life’ necessary both for the common good and humans’ individual good.

Doi: https://doi.org/10.1007/s11245-026-10404-7

Year and volume: 2026 (Vol. 6).

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

Abstract: During the initial stage of AI’s incorporation into scientific research, AI systems have functioned predominantly as tools under direct human supervision and control. However, AI incorporation into scientific research is now entering a stage in which AI Agents perform research tasks with partial autonomy while remaining under human supervision and control. In the not-too-distant future, a third stage may arise when autonomous AI systems conduct their own research and generate knowledge without human supervision or control. While the second and third stages of AI-augmented research may offer substantial benefits for science and society, they also create novel ethical issues, including (1) Conducting immoral research that may harm humans and other forms of life; (2) Increasing rate of biased, erroneous and deceptive research; (3) Confidentiality challenges; (4) Overreliance on AI; (5) Diffusion of responsibility and accountability; (6) Deskilling; (7) Job losses; (8) AI-generated research beyond human comprehension; and (9) Erosion of trust. We suggest specific solutions to minimize the negative consequences of these issues and offer proposals for ensuring that incorporation of AI into scientific research supports human values.

Doi: https://doi.org/10.1007/s43681-025-00908-0

Year and volume: 2026 (Vol. 6).

Author(s): Thomas J. Spiegel.

Abstract: Academic philosophers sometimes quip that in the future the only job safe from automation will be that of philosophy professors. However, the current AI revolution has inspired some AI scholars to propose the future establishment of closed-loop AI systems as a type of superintelligent robot that would essentially outperform and replace human scientists Zenil in the future of fundamental science led by generative closed-loop artificial intelligence, arXiv:2307.07522v3, 1-40, 2023; Schmidt in Mach Learn Sci Technol 5(3): 035045, (2024); Kitano in Npj Syst Bio Appl 7: 1–12, (2021). In this paper, I investigate whether, analogously, academic philosophy could be automated by putative, sufficiently advanced future AI, potentially featuring artificial embodiment as robots. To this end, I distinguish two mutually exclusive metaphilosophical conceptions of the nature of philosophy circumscribed as philosophy as a set of propositions (PP) versus philosophy as an activity (PA). Granting AI proponents that – iff artificial general intelligence (AGI), potentially embodied as superintelligent robots is achieved – natural sciences may be fully automated in the future, I argue for the conditional that if PP is true (but not if PA is true), then it is possible that AI can automate philosophy. Additionally, I consider what it would mean to automate philosophy given the current state of LLMs (e.g., the GPT-5 era). Finally, I briefly consider whether it would be preferable for us to have philosophy automated and argue that there are two prima facie reasons why automating philosophy, if possible, might be undesirable: the reason from obsolescence and the reason from ultimate answers.

Doi: https://doi.org/10.1007/s43681-025-00960-w

Year and volume: 2026 (Vol. 207).

Author(s): Giuseppe Pernagallo.

Abstract: Descartes’ cogito ergo sum emerges as an answer to an epistemological crisis: the search for an indubitable foundation in a world vulnerable to error, dreaming, and deception. In the contemporary landscape, however, cognitive activities once experienced as “internal” (reasoning, planning, remembering, writing) are increasingly delegated to artificial intelligence systems. This paper asks whether the Cartesian foundation retains its force under conditions of cognitive delegation, and whether the erosion of first-person thinking threatens the very status of the subject as res cogitans. I argue that the paradox dissolves once we distinguish (i) the epistemic function of the cogito (certainty through self-presence) from (ii) an ontological thesis that would make existence depend on the continuous exercise of thought. Building on a three-level taxonomy of delegation (instrumental support, deliberative suggestion, and agential substitution), a thought experiment involving “total delegation” shows that delegation presupposes minimal acts of intention and assent, while the hypothetical disappearance of conscious thinking undermines certainty rather than existence. The paper then introduces the notion of Cartesian AI to explain why contemporary systems generate the widespread illusion that machines think: by operationalizing a post-Cartesian conception of reason as computation (ratio sine sensu), AI can reproduce the external markers of rational discourse while lacking the first-person self-relation that grounds the cogito. The conclusion is that AI does not refute Descartes but destabilizes the cultural meaning of thinking, shifting attention from metaphysical existence to the normative stakes of agency, authorship, and responsibility.

Doi: https://doi.org/10.1007/s11229-026-05596-9