Year and volume: 2026 (Vol. 45).

Author(s): Emma Soane.

Abstract: Organizational risk is the possibility of events preventing the achievement of objectives and disrupting organizational viability. Developing understanding of organizational risk is necessary to allow realization of opportunities and protection from harm. However, much existing theorizing focuses on either a higher level of analysis, for example, studies of organizational risk culture, or a lower level of analysis, such as studies of individual perception, personality, and risk-taking. One way to advance theorizing involves connecting both levels of analysis. These connections are central to a microfoundations perspective that suggests organizational phenomena can be understood by linking macrolevel contexts with microlevel contexts and actions. I draw on this perspective to develop a model of organizational risk and explain how cross-level processes connect macro- and microlevel concepts. I focus on the organizational psychology literature that encompasses higher and lower levels of analysis to select and examine relevant concepts. I explain how organizational cultures create contexts for individual risk-taking that are homogeneous when constraints are strong and directional or variable when constraints are weak and ambiguous. These behaviors aggregate within and across units to influence organizational risk. Individual risk-taking also influences organizational risk via autonomy and discretion. In developing the model, I show how theories of cross-level processes extend understanding of organizational risk. I discuss implications for advancing theorizing about organizational risk by encompassing its microfoundations and linking them with managerial actions and objectives. Future research could examine these mechanisms through empirical studies and shed light on how leaders influence processes and change organizational risk.

Doi: https://doi.org/10.1007/s11229-025-05044-0

Biddle, Justin B. 2022. “On Predicting Recidivism: Epistemic Risk, Tradeoffs, and Values in Machine Learning.” Canadian Journal of Philosophy 52: 321-341. doi: https://doi.org/10.1017/can.2020.27.

Brown, Matthew J., and Jacob Stegenga. 2023. “The Validity of the Argument from Inductive Risk.” Canadian Journal of Philosophy 53: 187-190. doi: https://doi.org/10.1017/can.2023.37.

Harvard, Stephanie, and Eric Winsberg. 2022. “The Epistemic Risk in Representation.” Kennedy Institute of Ethics Journal 32: 1-31. doi: https://doi.org/10.1353/ken.2022.0001.

Harvard, Stephanie, and Eric Winsberg. 2026. “Representational Risk Revisited.” In The Routledge Handbook of Values and Science, ed. Kevin C. Elliott, and Ted Richards, 95-105. Routledge. doi: https://doi.org/10.4324/9781003469100-10.

Kukla, Rebecca, and Justin B. Biddle. 2017. “The Geography of Epistemic Risk.” In Exploring Inductive Risk: Case Studies of Values in Science, ed. Kevin C. Elliott, and Ted Richards, 215-238. Oxford University Press. doi: https://doi.org/10.1093/acprof:oso/9780190467715.003.0011. Note: Please visit Quill Kukla’s homepage for citation instructions.

Year: 2025.

Editor(s): Jan G. Michel (University of Düsseldorf).

Editorial status: closed for submissions.

URL: https://link.springer.com/collections/jdcaafgfjh

Year and Volume: 2024 (Vol. 54).

Author(s): Justin B. Biddle; John P. Nelson; Olajide E. Olugbade.

Abstract: Many AI development organizations advertise that they have offices of ethics that facilitate ethical AI. However, concerns have been raised that these offices are merely symbolic and do not actually promote ethics. We address the question of how we can know whether an organization is engaging in ethics washing in this way. We articulate an account of organizational power, and we argue that ethics offices that have power are not merely symbolic. Furthermore, we develop a framework for assessing whether an organization has an empowered ethics office—and, thus, is not ethics washing via a symbolic ethics office.

Doi: https://doi.org/10.1017/can.2025.9

Year and volume: 2024 (Vol. 84).

Author(s): Phillip Hintikka Kieval.

Abstract: State-of-the-art machine learning systems now routinely exceed benchmarks once thought beyond the ken of artificial intelligence (AI). Often these systems accomplish tasks through novel, insightful processes that remain inscrutable to even their human designers. Taking AlphaGo’s 2016 victory over Lee Sedol as a case study, this paper argues that such accomplishments manifest the essential features of achievements as laid out in Bradford’s 2015 book Achievement. Achievements like these are directly attributable to AI systems themselves. They are artificial achievements. This opens the door to a challenge that calls out for further inquiry. Since Bradford grounds the intrinsic value of achievements in the exercise of distinctively human perfectionist capacities, the existence of artificial achievements raises the possibility that some achievements might be valueless.

Doi: https://doi.org/10.1093/analys/anad052

Year and volume: 2023 (Vol. 74).

Author(s): Oliver M. Lean; Luca Rivelli; and Charles H. Pence.

Abstract: Empirical philosophers of science aim to base their philosophical theories on observations of scientific practice. But since there is far too much science to observe it all, how can we form and test hypotheses about science that are sufficiently rigorous and broad in scope, while avoiding the pitfalls of bias and subjectivity in our methods? Part of the answer, we claim, lies in the computational tools of the digital humanities, which allow us to analyse large volumes of scientific literature. Here we advocate for the use of these methods by addressing a number of large-scale, justificatory concerns—specifically, about the epistemic value of journal articles as evidence for what happens elsewhere in science, and about the ability of digital humanities tools to extract this evidence. Far from ignoring the gap between scientific literature and the rest of scientific practice, effective use of digital humanities tools requires critical reflection about these relationships.

Doi: https://doi.org/10.1086/715049

Year and volume: 2025 (Vol. 7).

Author(s): Sabina Leonelli.

Abstract: As an alternative to the long history of interpreting artificial intelligence (AI) as the attempt to rationalize and mechanize human ingenuity, thereby transcending nature and its perceived limits, this article proposes an interpretation of the conceptual foundations of environmental intelligence (EI) as the effort to develop digital technology and data-intensive algorithmic systems to sustain and enhance life on this planet. Thus articulated, EI provides a framework to challenge and redefine the philosophical premises of AI in ways that can explicitly spur the responsible and sustainable development of computational technologies toward public interest goals.

Doi: https://doi.org/10.1162/99608f92.ac7c1504

Year and volume: 2019 (Vol. 100).

Author(s): Candace Vogler.

Abstract: Properly interpreted, Aquinas supports a transformative rather than an additive understanding of how the human intellect relates to the capacities human beings share with other animals, an understanding founded in a metaphysics. The soul (‘life-form’) is the substantial form that maintains an organism as a single being throughout life, and Aquinas holds that the human soul is the only substantial form in the human being. He respects the variety of appetitive and apprehensive capacities displayed by different animals, and has a high view of the perceptive (even inductive) powers of the higher animals: they ‘share somewhat in reason’. It is no surprise that we cannot easily identify a rigid boundary between our intellectual powers and the cognitive and conative powers we share with other animals; rather, the powers not only interact, they qualify each other. As Stephen Brock put it, ‘Rationality is a mode of intellect … intrinsically connected to the life of the senses, and therefore to the sense-organs … and to matter itself.’

DOI: https://doi.org/10.1111/nbfr.12503

Year and volume: 2023 (Vol. 36).

Author(s): Sybren Heyndels.

Abstract: This paper clarifies and answers the following question: is technology morally neutral? It is argued that the debate between proponents and opponents of the Neutrality Thesis depends on different underlying assumptions about the nature of technological artifacts. My central argument centres around the claim that a mere physicalistic vocabulary does not suffice in characterizing technological artifacts as artifacts, and that the concepts of function and intention are necessary to describe technological artifacts at the right level of description. Once this has been established, I demystify talk about the possible value-ladenness of technological artifacts by showing how these values can be empirically identified. I draw from examples in biology and the social sciences to show that there is a non-mysterious sense in which functions and values can be empirically identified. I conclude from this that technology can be value-laden and that its value-ladenness can both derive from the intended functions as well as the harmful non-intended functions of technological artifacts.

Doi: https://doi.org/10.1007/s13347-023-00672-1

Year and volume: 2025 (Vol. 92).

Author(s): Torsten Wilholt.

Abstract: Although fundamental arguments have been presented to support the value-laden nature of all scientific research, they appear to be difficult to apply to basic research in physics. To explain this, I argue that basic research in physics is, in a very specific respect, often value-laden to a lesser degree. To spell this out, I refer to the different signal-to-noise ratios that can be achieved in different fields of research. I also argue that having a very low degree of value-ladenness in the very specific respect that I identify does not mean that the research is not value-laden at all.

Doi: https://doi.org/10.1017/psa.2025.10142