Nicholaos Jones

This is an attempt to explain, in a way familiar to contemporary ways of thinking about mereology, why someone might accept some prima facie puzzling remarks by Fazang, such as his claims that the eye of a lion is its ear and that a rafter of a building is identical to the building itself. These claims are corollaries of the Huayan Buddhist thesis that everything is part of everything else, and it is intended here to show that there is a rational basis for this thesis that involves a nonstandard notion of parthood and, importantly, that does not violate the principle of noncontradiction.

Idealizing conditions are scapegoats for scientific hypotheses, too often blamed for falsehood better attributed to less obvious sources. But while the tendency to blame idealizations is common among both philosophers of science and scientists themselves, the blame is misplaced. Attention to the nature of idealizing conditions, the content of idealized hypotheses, and scientists’ attitudes toward those hypotheses shows that idealizing conditions are blameless when hypotheses misrepresent. These conditions help to determine the content of idealized hypotheses, and they do so in a way that prevents those hypotheses from being false by virtue of their constituent idealizations

When comparing alternative courses of action, modern military decision makers often must consider both the military effectiveness and the ethical consequences of the available alternatives. The basis, design, calibration, and performance of a principles-based computational model of ethical considerations in military decision making are reported in this article. The relative ethical violation (REV) model comparatively evaluates alternative military actions based upon the degree to which they violate contextually relevant ethical principles. It is based on a set of specific ethical principles deemed by philosophers and ethicists to be relevant to military courses of action. A survey of expert and non-expert human decision makers regarding the relative ethical violation of alternative actions for a set of specially designed calibration scenarios was conducted to collect data that was used to calibrate the REV model. Perhaps unsurprisingly, the survey showed that people, even experts, disagreed greatly amongst themselves regarding the scenarios’ ethical considerations. Despite this disagreement, two significant results emerged. First, after calibration the REV model performed very well in terms of replicating the ethical assessments of human experts for the calibration scenarios. The REV model outperformed an earlier model that was based on tangible consequences rather than ethical principles, that earlier model performed comparably to human experts, the experts outperformed human non-experts, and the non-experts outperformed random selection of actions. All of these performance comparisons were measured quantitatively and confirmed with suitable statistical tests. Second, although humans tended to value some principles over others, none of the ethical principles involved—even the principle of not harming civilians—completely overshadowed all of the other principles.

One recent priority of the U.S. government is developing autonomous robotic systems. The U.S. Army has funded research to design a metric of evil to support military commanders with ethical decision-making and, in the future, allow robotic military systems to make autonomous ethical judgments. We use this particular project as a case study for efforts that seek to frame morality in quantitative terms. We report preliminary results from this research, describing the assumptions and limitations of a program that assesses the relative evil of two courses of action. We compare this program to other attempts to simulate ethical decision-making, assess possibilities for overcoming the trade-off between input simplification and output reliability, and discuss the responsibilities of users and designers in implementing such programs. We conclude by discussing the implications that this project highlights for the successes and challenges of developing automated mechanisms for ethical decision making.

While mechanistic explanation and, to a lesser extent, nomological explanation are well-explored topics in the philosophy of biology, topological explanation is not. Nor is the role of diagrams in topological explanations. These explanations do not appeal to the operation of mechanisms or laws, and extant accounts of the role of diagrams in biological science explain neither why scientists might prefer diagrammatic representations of topological information to sentential equivalents nor how such representations might facilitate important processes of explanatory reasoning unavailable to scientists who restrict themselves to sentential representations. Accordingly, relying upon a case study about immune system vulnerability to attacks on CD4+ T-cells, I argue that diagrams group together information in a way that avoids repetition in representing topological structure, facilitate identification of specific topological properties of those structures, and make available to controlled processing explanatorily salient counterfactual information about topological structures, all in ways that sentential counterparts of diagrams do not.

This paper elaborates upon various responses to the Problem of the One over the Many, in the service of two central goals. The first is to situate Huayan's mereology within the context of Buddhism's historical development, showing its continuity with a broader tradition of philosophizing about part-whole relations. The second goal is to highlight the way in which Huayan's mereology combines the virtues of the Nyāya-Vaisheshika and Indian Buddhist solutions to the Problem of the One over the Many while avoiding their vices.

In his _Treatise on the Golden Lion_, Fazang says that wholes are _in_ each of their parts and that each part of a whole _is_ every other part of the whole. In this paper, I offer an interpretation of these remarks according to which they are not obviously false, and I use this interpretation in order to rigorously reconstruct Fazang's arguments for his claims. On the interpretation I favor, Fazang means that the presence of a whole's part suffices for the presence of the whole and that the presence of any such part is both necessary and sufficient for the presence of any other part. I also argue that this interpretation is more plausible than its extant competitors

Theology involves inquiry into God's nature, God's purposes, and whether certain experiences or pronouncements come From God. These inquiries are metaphysical, part of theology's concern with the veridicality of signs and realities that are independent from humans. Several research programs concerned with the relation between theology and science aim to secure theology's intellectual standing as a metaphysical discipline by showing that it satisfies criteria that make modern science reputable, on the grounds that modern science embodies contemporary canons of respectability for metaphysical disciplines. But, no matter the ways in which theology qua metaphysics is shown to resemble modern science, these research programs seem destined for failure. For, given the currently dominant approaches to understanding modern scientific epistemology, theological reasoning is crucially dissimilar to modern scientific reasoning in that it treats the existence of God as a certainty immune to refutation. Barring the development of an epistemology of modern science that is amenable to theology, theology as metaphysics is intellectually disreputable.

Mengzi 孟子 6A2 contains the famous water analogy for the innate goodness of human nature. Some evaluate Mengzi’s reasoning as strong and sophisticated; others, as weak or sophistical. I urge for more nuance in our evaluation. Mengzi’s reasoning fares poorly when judged by contemporary standards of analogical strength. However, if we evaluate the analogy as an instance of correlative thinking within a yin-yang 陰陽 cosmology, his reasoning fares well. That cosmology provides good reason to assert that water tends to flow downward, not because of available empirical evidence, but because water correlates to yin and yin correlates to naturally downward motion. Substantiating these contentions also gives occasion to better understand the nature of correlative reasoning in classical Chinese philosophy.

When do data provide good evidence for a hypothesis, evidence that warrants an inference to the hypothesis? Standard answers either reject the legitimacy of induction or else allow warranted inference from data to hypothesis when there are suitable relationships between and among the data and hypotheses. The severity account rejects all of these, maintaining instead that the good evidence relation concerns not only relations between data and hypotheses but also the methods for obtaining the data and the sensitivity of these methods to detecting falsehood. So, for example, the severity account allows two rival hypotheses to fit the data equally well, even to the point of having the same prior and posterior probabilities relative to those data, while the data nonetheless favour one hypothesis over the other by virtue of those data providing a severe test of one hypothesis and not the other. The contributions to Error and Inference variously trace the genesis of the severity account from statistics-oriented sciences, elaborate upon the account’s details, apply the account to various philosophical issues, and offer challenges to the account’s adequacy and replies to major criticisms. The editors have developed the severity account in detail elsewhere, and this anthology is an effort …

Life scientists increasingly rely upon abstraction-based modeling and reasoning strategies for understanding biological phenomena. We introduce the notion of constraint-based reasoning as a fruitful tool for conceptualizing some of these developments. One important role of mathematical abstractions is to impose formal constraints on a search space for possible hypotheses and thereby guide the search for plausible causal models. Formal constraints are, however, not only tools for biological explanations but can be explanatory by virtue of clarifying general dependency-relations and patterning between functions and structures. We describe such situations as constraint-based explanations and argue that these differ from mechanistic strategies in important respects. While mechanistic explanations emphasize change-relating causal features, constraint-based explanations emphasize formal dependencies and generic organizational features that are relatively independent of lower-level changes in causal details. Our distinction between mechanistic and constraint-based explanations is pragmatically motivated by the wish to understand scientific practice. We contend that delineating the affordances and assumptions of different explanatory questions and strategies helps to clarify tensions between diverging scientific practices and the innovative potentials in their combination. Moreover, we show how constraint-based explanation integrates several features shared by otherwise different philosophical accounts of abstract explanatory strategies in biology.