A mixture preorder is a preorder on a mixture space (such as a convex set) that is compatible with the mixing operation. In decision theoretic terms, it satisfies the central expected utility axiom of strong independence. We consider when a mixture preorder has a multi-representation that consists of real-valued, mixture-preserving functions. If it does, it must satisfy the mixture continuity axiom of Herstein and Milnor (1953). Mixture continuity is sufficient for a mixture-preserving multi-representation when the dimension of the mixture (...) space is countable, but not when it is uncountable. Our strongest positive result is that mixture continuity is sufficient in conjunction with a novel axiom we call countable domination, which constrains the order complexity of the mixture preorder in terms of its Archimedean structure. We also consider what happens when the mixture space is given its natural weak topology. Continuity (having closed upper and lower sets) and closedness (having a closed graph) are stronger than mixture continuity. We show that continuity is necessary but not sufficient for a mixture preorder to have a mixture-preserving multi-representation. Closedness is also necessary; we leave it as an open question whether it is sufficient. We end with results concerning the existence of mixture-preserving multi-representations that consist entirely of strictly increasing functions, and a uniqueness result. (shrink)

A mixture preorder is a preorder on a mixture space (such as a convex set) that is compatible with the mixing operation. In decision theoretic terms, it satisfies the central expected utility axiom of strong independence. We consider when a mixture preorder has a multi-representation that consists of real-valued, mixture-preserving functions. If it does, it must satisfy the mixture continuity axiom of Herstein and Milnor (1953). Mixture continuity is sufficient for a mixture-preserving multi-representation when the dimension of the mixture (...) space is countable, but not when it is uncountable. Our strongest positive result is that mixture continuity is sufficient in conjunction with a novel axiom we call countable domination, which constrains the order complexity of the mixture preorder in terms of its Archimedean structure. We also consider what happens when the mixture space is given its natural weak topology. Continuity (having closed upper and lower sets) and closedness (having a closed graph) are stronger than mixture continuity. We show that continuity is necessary but not sufficient for a mixture preorder to have a mixture-preserving multi-representation. Closedness is also necessary; we leave it as an open question whether it is sufficient. We end with results concerning the existence of mixture-preserving multi-representations that consist entirely of strictly increasing functions, and a uniqueness result. (shrink)

In order to make scientific results relevant to practical decision making, it is often necessary to transfer a result obtained in one set of circumstances—an animal model, a computer simulation, an economic experiment—to another that may differ in relevant respects—for example, to humans, the global climate, or an auction. Such inferences, which we can call extrapolations, are a type of argument by analogy. This essay sketches a new approach to analogical inference that utilizes chain graphs, which resemble directed acyclic graphs (...) (DAGs) except in allowing that nodes may be connected by lines as well as arrows. This chain graph approach generalizes the account of extrapolation I provided in my (2008) book and leads to new insights that integrate the contributions of the other participants of this symposium. More specifically, this approach explicates the role of “fingerprints,” or distinctive markers, as a strategy for avoiding an underdetermination problem having to do with spurious analogies. Moreover, it shows how the extrapolator’s circle, one of the central challenges for extrapolation highlighted in my book, is closely tied to distinctive markers and the Markov condition as it applies to chain graphs. Finally, the approach suggests additional ways in which investigations of a model can provide information about a target that are illustrated by examples concerning nanomaterials in sunscreens and Wendy Parker’s discussion of fingerprints in climate science. (shrink)

This chapter sets out the theorems, and presents some examples that show in a rough way how the theorems work. It explains separability precisely, and states the theorems. The chapter starts the work of interpreting the theorems, and also explains the significance of their conclusions from a formal, mathematical point of view. It then discusses a significant assumption that is used in the proofs of the theorems. The published proofs of both the separability theorems depend on an assumption that may (...) be objectionable in some contexts. These theorems are about an ordering defined on a field of alternatives. If an ordering can be represented by an additively separable utility function, the theorem shows it can be represented by a whole family of additively separable functions. Each member of the family is an increasing linear transform of the others, and the family includes every increasing linear transform of each of its members. (shrink)

Autism Spectrum Disorder (ASD) is extremely heterogeneous clinically and genetically. There is a pressing need for a better understanding of the heterogeneity of ASD based on scientifically rigorous approaches centered on systematic evaluation of the clinical and research utility of both phenotype and genotype markers. This paper presents a holistic PheWAS-inspired method to identify meaningful associations between ASD phenotypes and genotypes. We generate two types of phenotype-phenotype (p-p) graphs: a direct graph that utilizes only phenotype data, and an (...) indirect graph that incorporates genotype as well as phenotype data. We introduce a novel methodology for fusing the direct and indirect p-p networks in which the genotype data is incorporated into the phenotype data in varying degrees. The hypothesis is that the heterogeneity of ASD can be distinguished by clustering the p-p graph. The obtained graphs are clustered using network-oriented clustering techniques, and results are evaluated. The most promising clusterings are subsequently analyzed for biological and domain-based relevance. Clusters obtained delineated different aspects of ASD, including differentiating ASD-specific symptoms, cognitive, adaptive, language and communication functions, and behavioral problems. Some of the important genes associated with the clusters have previous known associations to ASD. We found that clusters based on integrated genetic and phenotype data were more effective at identifying relevant genes than clusters constructed from phenotype information alone. These genes included five with suggestive evidence of ASD association and one known to be a strong candidate. (shrink)

Gene discovery reveals new biology, expands the utility of marker‐assisted selection, and enables targeted mutagenesis. Still, such discoveries can take over a decade. We present a general strategy, “Agile Genetics,” that uses nested, structured populations to overcome common limits on gene resolution. Extensive simulation work on realistic genetic architectures shows that, at population sizes of >5000 samples, single gene‐resolution can be achieved using bulk segregant pools. At this scale, read depth and technical replication become major drivers of resolution. Emerging (...) enrichment methods to address coverage are on the horizon; we describe one possibility – iterative depth sequencing (ID‐seq). In addition, graph‐based pangenomics in experimental populations will continue to maximize accuracy and improve interpretation. Based on this merger of agronomic scale with molecular and bioinformatic innovation, we predict a new age of rapid gene discovery. (shrink)

"The best book available for non-mathematicians." — Contemporary Psychology. Superb nontechnical introduction to game theory and related disciplines, primarily as applied to the social sciences. Clear, comprehensive coverage of utility theory, 2-person zero-sum games, 2-person non-zero-sum games, n-person games, individual and group decision-making, much more. Appendixes. Bibliography. Graphs and figures.

Various causal details of the genetic process of translation have been singled out to account for its privileged status as a ‘code'. We explicate the biological uses of coding talk by characterizing a class of special causal processes in which topological properties are the causally relevant ones. This class contains both the process of translation and communication theoretic coding processes as special cases. We propose a formalism in terms of graphs for expressing our theory of biological codes and discuss its (...) utility in understanding biological systems. *Received May 2007; revised May 2008. †To contact the authors, please write to: Department of Philosophy, Baker Hall 135, Carnegie Mellon University, Pittsburgh, PA 15213; e-mail: [email protected] or [email protected]. (shrink)

Building on the computer science concept of _code smells_, we initiate the study of _law smells_, i.e., patterns in legal texts that pose threats to the comprehensibility and maintainability of the law. With five intuitive law smells as running examples—namely, duplicated phrase, long element, large reference tree, ambiguous syntax, and natural language obsession—, we develop a comprehensive law smell taxonomy. This taxonomy classifies law smells by when they can be detected, which aspects of law they relate to, and how they (...) can be discovered. We introduce text-based and graph-based methods to identify instances of law smells, confirming their utility in practice using the United States Code as a test case. Our work demonstrates how ideas from software engineering can be leveraged to assess and improve the quality of _legal_ code, thus drawing attention to an understudied area in the intersection of law and computer science and highlighting the potential of computational legal drafting. (shrink)

In Nozick’s rendition of the decision situation given in Newcomb’s Paradox dominance and the principle of maximum expected utility recommend different strategies. While evidential decision theory seems to be split over which principle to apply and how to interpret the principles in the first place, causal decision theory seems to go for the solution recommended by dominance. As a reply to the CDT proposal by Wolfgang Spohn, who opts for “one-boxing” by employing reflexive decision graphs, I will draw on (...) the framework of causal knowledge patterns, i.e., Bayes net causal models, augmented by non-causal knowledge, to finally arrive at “one-boxing” – more intuitively and more closely to what actually is in Nozick’s story. This proposal allows the careful re-examination of all relevant concepts in the original story and might cast new light on the following questions: How may causality in general be understood to allow causal inference from hybrid patterns encoding subjective knowledge? How can the notion of prediction be analyzed – philosophically and formally? And what’s the decision-maker’s conceptualization of the situation he will act upon? (shrink)

In 1907, German anthropologist Theodor Mollison invented a unique method for racial differentiation, called ‘deviation curves’. By transforming anthropometric data matrices into graphs, Mollison’s method enabled the simultaneous comparison of a large number of physical attributes of individuals and groups. However, the construction of deviation curves had been highly desultory, and their interpretation had been prone to various visual misjudgements. Despite their methodological shortcomings, deviation curves became very popular among racial anthropologists. This positive reception not only stemmed from the method’s (...) utilities, but was related to additional interests of its protagonists which the method helped promote. Deviation curves provided a unique solution to the holistic–atomistic controversy in German anthropology. By giving separate measurements a consolidated visual form, they substantiated the idea that the attributes of certain social groups were part of distinct racial compounds. Deviation curves thus reinforced racial suppositions, in face of severe criticism on the ontological reality of race itself. Finally, deviation curves emphasized the biological singularity of disadvantaged human groups – Jews, Africans and also women – and of their divergence from ideologically defined physical norms. Disciplinary and social interests thus became intertwined in the formation of a scientific method, which is used to this day in physical anthropology. (shrink)

Measuring neuronal activity with electrophysiological methods may be useful in detecting neurological dysfunctions, such as mild traumatic brain injury (mTBI). This approach may be particularly valuable for rapid detection in at-risk populations including military service members and athletes. Electrophysiological methods, such as quantitative electroencephalography (qEEG) and recording event-related potentials (ERPs) may be promising; however, the field is nascent and significant controversy exists on the efficacy and accuracy of the approaches as diagnostic tools. For example, the specific measures derived from an (...) electroencephalogram (EEG) that are most suitable as markers of dysfunction have not been clearly established. A study was conducted to summarize and evaluate the statistical rigor of evidence on the overall utility of qEEG as an mTBI detection tool. The analysis evaluated qEEG measures/parameters that may be most suitable as fieldable diagnostic tools, identified other types of EEG measures and analysis methods of promise, recommended specific measures and analysis methods for further development as mTBI detection tools, identified research gaps in the field, and recommended future research and development thrust areas. The qEEG study group formed the following conclusions: 1. Individual qEEG measures provide limited diagnostic utility for mTBI. However, many measures can be important features of qEEG discriminant functions, which do show significant promise as mTBI detection tools. 2. ERPs offer utility in mTBI detection. In fact, evidence indicates that ERPs can identify abnormalities in cases where EEGs alone are nondisclosing. 3. The standard mathematical procedures used in the characterization of mTBI EEGs should be expanded to incorporate newer methods of analysis including nonlinear dynamical analysis, complexity measures, analysis of causal interactions, graph theory and information dynamics. 4. and 5. are too long to include here. (shrink)

Ecological economics is an interdisciplinary science that is primarily concerned with developing interventions to achieve sustainable ecological and economic systems. While ecological economists have, over the last few decades, made various empirical, theoretical, and conceptual advancements, there is one concept in particular that remains subject to confusion: critical natural capital. While critical natural capital denotes parts of the environment that are essential for the continued existence of our species, the meaning of terms commonly associated with this concept, such as ‘non-substitutable’ (...) and ‘impossible to substitute,’ require a clearer formulation then they tend to receive. With the help of equations and graphs, this article develops new definite account of critical natural capital that makes explicit what it means for objective environmental conditions to be essential for continued existence. The second main part of this article turns to the question of formally modeling the priority of conserving critical natural capital. While some ecological economists have maintained that, beyond a certain threshold, critical natural capital possesses absolute infinite value, absolute infinite utility models encounter significant problems. This article shows that a relative infinite utility model provides a better way to model the priority of conserving critical natural capital. (shrink)

As a compact representation of joint probability distributions over a dependence graph of random variables, and a tool for modelling and reasoning in the presence of uncertainty, Bayesian networks are of great importance for artificial intelligence to combine domain knowledge, capture causal relationships, or learn from incomplete datasets. Known as a NP-hard problem in a classical setting, Bayesian inference pops up as a class of algorithms worth to explore in a quantum framework. This paper explores such a research direction (...) and improves on previous proposals by a judicious use of the utility function in an entangled configuration. It proposes a completely quantum mechanical decision-making process with a proven computational advantage. A prototype implementation in Qiskit (a Python-based program development kit for the IBM Q machine) is discussed as a proof-of-concept. (shrink)

Few studies have been conducted into the use of mobile technologies at community-based organizations. Community sport organizations (CSOs) typically operate within a defined geographic area and rely on the primary support of volunteers. Based on the characteristics of mobile-based information services, this article proposes a model that provides a guide for CSOs to classify mobile applications through four mobile utility factors and three innovation adoption determinants (cost, skill requirements, and compatibility). The model is supported visually by the use of (...) Microsoft Excel generated “radar graphs” to illustrate desired practical and actual performance. The contribution of the theoretical model is one of providing a vehicle for evaluating mobile technology applications by CSOs to identify the potential effectiveness of mobile devices, particularly in a preadoption scenario. (shrink)

Theory of networks serves as a mathematical foundation for the construction and modeling of chemical structures and complicated networks. In particular, chemical networking theory has a wide range of utilizations in the study of chemical structures, where examination and manipulation of chemical structural information are made feasible by utilizing the numerical graph invariants. A network invariant or a topological index is a numerical measure of a chemical compound which is capable to describe the chemical structural properties such as melting (...) point, freezing point, density, pressure, tension, and temperature of chemical compounds. Wiener initiated the first distance-based TI which is considered to be the most important TI to preserve the chemical and physical properties of chemical structures. Later on, degree-based TI was introduced to find the π -electron energy of molecules. Recently, connection number-based TIs are studied which are more efficient than degree and distance-based TIs. In this paper, we compute the connection number-based TIs of the structure of crystal cubic carbons which are one of the most significant and interesting composites in modern resources of science due to the involvement of carbon atoms. (shrink)

Emptiness in India has a subtly different flavor from emptiness in China, inflected as the latter had been with a metaphysical framework inherited from the Daoist and Confucian traditions. The Huayan tradition universalizes the idea of interdependence. According to philosophers in this tradition, it is not merely that everything depends upon some other things, but that everything depends upon all other things, and that each phenomenon interpenetrates every other phenomenon. The Net of Indra is a dominant metaphor of Huayan Buddhism, (...) but its exact content is somewhat obscure. Drawing on a graph-theoretic representation of the key notion of emptiness, this chapter delivers a precise account of the metaphor, showing how it does justice to core Huayan views. It demonstrates the utility of contemporary logical-mathematical tools for making precise classical Buddhist doctrines, and for defusing suspicions of mystical incoherence. (shrink)

The epistemic position of an agent often depends on their position in a larger network of other agents who provide them with information. In general, agents are better off if they have diverse and independent sources. Sullivan et al. [19] developed a method for quantitatively characterizing the epistemic position of individuals in a network that takes into account both diversity and independence; and presented a proof-of-concept, closed-source implementation on a small graph derived from Twitter data [19]. This paper reports (...) on an open-source reimplementation of their algorithm in Python, optimized to be usable on much larger networks. In addition to the algorithm and package, we also show the ability to scale up our package to large synthetic social network graph profiling, and finally demonstrate its utility in analyzing real-world empirical evidence of ‘echo chambers’ on online social media, as well as evidence of interdisciplinary diversity in an academic communications network. (shrink)

This book is the sixth volume in the series of Collected Papers on Advancing Uncertain Combinatorics through Graphization, Hyperization, and Uncertainization: Fuzzy, Neutrosophic, Soft, Rough, and Beyond. Building upon the foundational contributions of previous volumes, this edition focuses on the exploration and development of Various New Uncertain Concepts, further enriching the study of uncertainty and complexity through innovative theoretical advancements and practical applications. The volume is meticulously organized into 15 chapters, each presenting unique perspectives and contributions to the field. From (...) theoretical explorations to real-world applications, these chapters provide a cohesive and comprehensive overview of the state of the art in uncertain combinatorics, emphasizing the versatility and power of the newly introduced concepts and methodologies. The first chapter (SuperHypertree-depth – Structural Analysis in SuperHyperGraphs) explores the concept of SuperHypertree-depth, an extension of the classical graph parameter Tree-depth and its hypergraph counterpart Hypertree-depth. By introducing hierarchical nesting within SuperHyperGraphs, where both vertices and edges can represent recursive subsets, this study investigates the mathematical properties and structural implications of these extended parameters. The findings highlight the relationships between SuperHypertree-depth and its traditional graph-theoretic equivalents, providing a deeper understanding of their applicability to hierarchical and complex systems. The second chapter (Obstructions for Hypertree-width and SuperHypertree-width) examines the role of ultrafilters as obstructions in determining Hypertree-width and extends the concept to SuperHypertree-width. Building on hypergraph theory, which abstracts traditional graph frameworks into more complex domains, the study investigates how recursive structures within SuperHyperGraphs redefine the computational and structural properties of these parameters. Ultrafilters, with their broad mathematical significance, serve as critical tools for understanding the limitations and potentials of these advanced graph metrics. The third chapter (SuperHypertree-Length and SuperHypertree-Breadth in SuperHyperGraphs) investigates the extension of the graph-theoretic parameters Tree-length and Tree-breadth to the realms of hypergraphs and SuperHyperGraphs. By leveraging the hierarchical nesting of SuperHyperGraphs, the study explores how these parameters adapt to increasingly complex and multi-level structures. Comparative analyses between these extended parameters and their classical counterparts reveal new insights into their relevance and utility in advanced graph and hypergraph theory. Plithogenic Sets, which generalize Fuzzy and Neutrosophic Sets, are extended in the fourth chapter (Extended HyperPlithogenic Sets and Generalized Plithogenic Graphs) to Extended Plithogenic Sets, HyperPlithogenic Sets, and SuperHyperPlithogenic Sets. This study further investigates their application to graph theory through the concepts of Extended Plithogenic Graphs and Generalized Extended Plithogenic Graphs. The chapter provides a concise exploration of these frameworks, offering insights into their potential for addressing uncertainty and complexity in graph structures. Soft Sets provide an effective framework for decision-making by mapping parameters to subsets of a universal set, addressing uncertainty and vagueness. The fifth chapter (Double-Framed Superhypersoft Set and Double-Framed Treesoft Set) introduces the Double-Framed SuperHypersoft Set and the Double-Framed Treesoft Set as extensions of traditional and advanced soft set frameworks, such as Hypersoft and SuperHypersoft Sets. The chapter explores their relationships with existing concepts, offering new tools to handle complex decision-making scenarios with enhanced structural flexibility. The sixth paper (HyperPlithogenic Cubic Set and SuperHyperPlithogenic Cubic Set) introduces the concepts of the HyperPlithogenic Cubic Set and SuperHyperPlithogenic Cubic Set, which extend the Plithogenic Cubic Set by integrating both interval-valued and single-valued fuzzy memberships. These sets leverage multi-attribute aggregation techniques inherent to plithogenic structures, allowing for nuanced representations of uncertainty. Additionally, related constructs such as the HyperPlithogenic Fuzzy Cubic Set, HyperPlithogenic Intuitionistic Fuzzy Cubic Set, and HyperPlithogenic Neutrosophic Cubic Set are explored, further enriching the theoretical and practical applications of this framework. The seventh chapter (L-Neutrosophic Sets and Nonstationary Neutrosophic Sets) extends the foundational concepts of fuzzy sets by integrating Neutrosophic and Plithogenic frameworks. By introducing L-Neutrosophic Sets and Nonstationary Neutrosophic Sets, the study enhances the representation of uncertainty through independent membership components: truth, indeterminacy, and falsity. These advanced constructs also incorporate multi-dimensional and contradictory attributes, providing a robust means of modeling complex decision-making and uncertain data. Plithogenic and Rough Sets, known for generalizing uncertainty modeling and classification, are extended in the eight chapter (Forest HyperPlithogenic and Forest HyperRough Sets) to Forest HyperPlithogenic Sets, Forest SuperHyperPlithogenic Sets, Forest HyperRough Sets, and Forest SuperHyperRough Sets. These frameworks incorporate hierarchical and recursive structures to advance existing set-theoretic paradigms. The chapter explores their applications in multi-level data analysis and uncertainty classification, demonstrating their adaptability to complex systems. Building on Fuzzy, Neutrosophic, and Plithogenic Sets, the tenth chapter (Symbolic HyperPlithogenic Sets) introduces Symbolic HyperPlithogenic Sets and Symbolic n-SuperHyperPlithogenic Sets. These sets incorporate symbolic components and algebraic coefficients, enabling flexible operations within a defined prevalence order. By extending symbolic representation into hyperplithogenic and superhyperplithogenic domains, the chapter opens new pathways for addressing uncertainty and hierarchical complexity in mathematical modeling. Soft Sets, designed to manage uncertainty and imprecision, have evolved through various extensions like Hypersoft Sets and SuperHypersoft Sets. The eleventh chapter (N-SuperHypersoft and Bijective SuperHypersoft Sets) introduces N-SuperHypersoft Sets, N-Treesoft Sets, Bijective SuperHypersoft Sets, and Bijective Treesoft Sets. These new constructs enhance decision-making frameworks by incorporating advanced hierarchical and bijective relationships, building on existing theories and expanding their applications. Plithogenic Sets, known for integrating multi-valued attributes and contradictions, and Rough Sets, which partition data into definable approximations, are combined in the twelfth chapter (Plithogenic Rough Sets) to form Plithogenic Rough Sets. This fusion provides a powerful framework for addressing uncertainty in dynamic and complex decision-making scenarios, offering a novel approach to uncertainty modeling. Expanding on Neutrosophic Sets, which represent truth, indeterminacy, and falsehood, this chapter introduces Plithogenic Duplets and Plithogenic Triplets. These constructs leverage the Plithogenic framework to incorporate attributes, values, and contradiction measures. The thirteenth chapter (Plithogenic Duplets and Triplets) examines their relationships with Neutrosophic Duplets and Triplets, offering new tools for multi-dimensional data representation and decision-making. Building on foundational concepts like Rough Sets and Vague Sets, the fourteenth chapter (SuperRough and SuperVague Sets) introduces SuperRough Sets and SuperVague Sets. These generalized frameworks extend uncertainty modeling by incorporating hierarchical structures. The study also demonstrates that SuperRough Sets can evolve into SuperHyperRough Sets, providing further generalizations for advanced data classification and analysis. The fifteenth chapter (Neutrosophic TreeSoft Expert and ForestSoft Sets) revisits the Neutrosophic TreeSoft Set, which combines the hierarchical structure of TreeSoft Sets with the Neutrosophic framework for uncertainty representation. Additionally, it introduces the Neutrosophic TreeSoft Expert Set, incorporating expert knowledge into the model. The chapter also explores the ForestSoft Set and its extension, the Neutrosophic ForestSoft Set, to provide multi-level, tree-structured approaches for complex data representation and analysis. (shrink)

Background: The management of challenging behaviours in inpatient with intellectual disability and/or autism spectrum disorders can lead to an escalation of control measures. In these complex situations where patients have an intellectual disability/autism spectrum disorder accompanied by a psychiatric comorbidity, the experiences of caregivers related to the crisis management have rarely been studied. Purpose: This study examined the moral experiences of caregivers related to challenging behaviours’ management and alternatives to control measures. Research design: Using Charles Taylor’s hermeneutic framework, a 2-month (...) focused ethnography with a participatory approach was used. Participants and research context: Sixteen caregivers were interviewed in a Canadian mental health setting for adults with intellectual disability/autism spectrum disorder and psychiatric comorbidity. Ethical considerations: The research was conducted in compliance with the Declaration of Helsinki and local Research Ethics Board approval. Written informed consent was collected systematically from participants. Findings: By accounting for caregivers’ moral experiences, this study sheds light on a neglected dimension of the care relationship: the vulnerability of the caregiver. We highlight the main barriers and facilitators to alternatives to control measures. First, a caregiver’s vulnerability was characterised by the overall impact of challenging behaviours and the moral distress associated with the use of control measures and exclusion mechanisms of intellectual disability/autism spectrum disorder patients. Second, a strong ambiguity between care and control measures and a lack of inclusive approaches were identified as the two main barriers to challenging behaviour management. Third, the involvement, both professional and personal, of caregivers was deemed necessary to implement alternatives to control measures. Discussion: A conflict of values opposes two conceptions of autonomy: a rational autonomy, which is counterproductive to the reduction of control measures, versus a relational autonomy based on shared vulnerability. Conclusion: The recognition of caregiver’s vulnerability is a benchmark to create alternative approaches, which defuse the logic of control and promote an ethics of care within which caregivers’ self-concern can be understood as fostering mutual respect. (shrink)

This chapter concerns the nature of our obligations as individuals when it comes to our emissions-producing activities and climate change. The first half of the chapter argues that the popular ‘expected utility’ approach to this question faces a problematic dilemma: either it gives skeptical verdicts, saying that there are no such obligations, or it yields implausibly strong verdicts. The second half of the chapter diagnoses the problem. It is argued that the dilemma arises from a very general feature of (...) the view, and thus is shared by other views as well. The chapter then discusses what an account of our individual obligations needs to look like if it is to avoid the dilemma. Finally, the discussion is extended beyond climate change to other collective impact contexts. (shrink)

In this article, I will argue in favor of both the ethical and epistemological utility of explanations in artificial intelligence -based medical technology. I will build on the notion of “explicability” due to Floridi, which considers both the intelligibility and accountability of AI systems to be important for truly delivering AI-powered services that strengthen autonomy, beneficence, and fairness. I maintain that explicable algorithms do, in fact, strengthen these ethical principles in medicine, e.g., in terms of direct patient–physician contact, as (...) well as on a longer-term epistemological level by facilitating scientific progress that is informed through practice. With this article, I will therefore attempt to counter arguments against demands for explicable AI in medicine that are based on a notion of “whatever heals is right.” I will elucidate my elaboration on the positive aspects of explicable AI in medicine as well as by pointing out risks of non-explicable AI. (shrink)

We give two social aggregation theorems under conditions of risk, one for constant population cases, the other an extension to variable populations. Intra and interpersonal welfare comparisons are encoded in a single ‘individual preorder’. The theorems give axioms that uniquely determine a social preorder in terms of this individual preorder. The social preorders described by these theorems have features that may be considered characteristic of Harsanyi-style utilitarianism, such as indifference to ex ante and ex post equality. However, the theorems are (...) also consistent with the rejection of all of the expected utility axioms, completeness, continuity, and independence, at both the individual and social levels. In that sense, expected utility is inessential to Harsanyi-style utilitarianism. In fact, the variable population theorem imposes only a mild constraint on the individual preorder, while the constant population theorem imposes no constraint at all. We then derive further results under the assumption of our basic axioms. First, the individual preorder satisfies the main expected utility axiom of strong independence if and only if the social preorder has a vector-valued expected total utility representation, covering Harsanyi’s utilitarian theorem as a special case. Second, stronger utilitarian-friendly assumptions, like Pareto or strong separability, are essentially equivalent to strong independence. Third, if the individual preorder satisfies a ‘local expected utility’ condition popular in non-expected utility theory, then the social preorder has a ‘local expected total utility’ representation. Fourth, a wide range of non-expected utility theories nevertheless lead to social preorders of outcomes that have been seen as canonically egalitarian, such as rank-dependent social preorders. Although our aggregation theorems are stated under conditions of risk, they are valid in more general frameworks for representing uncertainty or ambiguity. (shrink)

Accordingly, the task of the present book is to consider the role of idealization in cognitive matters and to establish its utility in this realm.

It is a truth universally known but not oft discussed that a journal article is often a fragment of a larger series of thoughts, or a longer piece of work. In entering into dialogue with Gaab and Bamboulis and Bortolotti, I will briefly describe the context of this paper, in the hopes that it will clarify my commitments and wider thinking on this area.This paper isolates one thread of my doctoral dissertation evaluating what I take to be two central theoretical (...) claims of CBT: first, that mental illness is related to patterns of thought with epistemic issues and secondly, that CBT works through rectifying these epistemic issues. In the broader work I argue that over time, because psychotherapy has... (shrink)

Utilitarianism is one of the most famous ethical doctrines, based on the ideal of maximizing pleasure and minimizing pain. But Utilitarians and their opponents lack a clear scientific and philosophical understanding of its foundations, the measurement and aggregation of utility. This is what The Pursuit of Happiness now offers.

An agent whose preferences violate the Independence Axiom or for some other reason are not representable by an expected utility function, can avoid 'dynamic inconsistency' either by foresight ('sophisticated choice') or by subsequent adjustment of preferences to the chosen plan of action ('resolute choice'). Contrary to McClennen and Machina, among others, it is argued these two seemingly conflicting approaches to 'dynamic rationality' need not be incompatible. 'Wise choice' reconciles foresight with a possibility of preference adjustment by rejecting the two (...) assumptions that create the conflict: Separability of Preferences in the case of sophisticated choice and Reduction to Normal form in the case of resolute choice.. (shrink)

The term “therapeutic misconception” was coined in 1982 by Paul Appelbaum, Loren Roth, and Charles Lidz. Appelbaum and his colleagues interviewed participants in several psychiatric studies, including a drug trial with a placebo control arm. Appelbaum's group found that many people were unaware of the differences between participating in a study and receiving treatment in the clinical setting. Rather than understanding these differences, study participants tended to believe that therapy and research were governed by the same primary goal: to advance (...) the individual patient's best interests. Appelbaum's group labeled this mistaken belief the therapeutic misconception. (shrink)

It is better when people get what they deserve. So we need an axiology according to which the intrinsic value of a possible world is a function of both how well-off and how deserving the people in that world are. But how should these ?desert-adjusted? values of possible worlds be calculated? It is easy to come up with some qualitative ideas. But these qualitative ideas leave us with an embarrassment of riches: too many quantitative functions that implement those qualitative ideas. (...) In this paper I will select one of these quantitative functions and defend its superiority. (shrink)

According to the ideal of tolerance, the state is supposed to be neutral or evenhanded in its dealings with religious sects and doctrines. The tolerant state does not pursue policies aimed at favoring one sect over another.

We use a theorem from M. J. Schervish to explore the relationship between accuracy and practical success. If an agent is pragmatically rational, she will quantify the expected loss of her credence with a strictly proper scoring rule. Which scoring rule is right for her will depend on the sorts of decisions she expects to face. We relate this pragmatic conception of inaccuracy to the purely epistemic one popular among epistemic utility theorists.

This article analyses how normative decision theory is understood by economists. The paradigmatic example of normative decision theory, discussed in the article, is the expected utility theory. It...