When social work emerged as a profession in the first decades of the 20th century, it was strongly influenced by emancipatory motives introduced by various sociocultural and religious movements, and at the same time devoted itself to the construction and maintenance of a powerful welfare and nation state. Transnational agents and social movements promoted these processes and played a crucial role in establishing and developing national welfare systems and relevant professional discourses. This article examines the gendered construction of the social (...) work profession through the transnational history of early social work between Germany and the Jewish community in Palestine in the first half of the 20th century. By adopting a biographical approach to the specific paths of Jewish women practitioners who had been educated in German-speaking countries, immigrated to mandatory Palestine, and engaged themselves in the emerging field of social work, we will trace the construction of the profession as deeply embedded in social power relations. At the same time, we will trace its (re)construction as led mainly by female pioneers, who were concerned with emancipation, discrimination and migration. (shrink)

Reasoning About Knowledge is the first book to provide a general discussion of approaches to reasoning about knowledge and its applications to distributed ...

We present statements equivalent to some fragments of the principle of non-deterministic inductive definitions (NID) by van den Berg (2013), working in a weak subsystem of constructive set theory CZF. We show that several statements in constructive topology which were initially proved using NID are equivalent to the elementary and finitary NIDs. We also show that the finitary NID is equivalent to its binary fragment and that the elementary NID is equivalent to a variant of NID based on the notion (...) of biclosed subset. Our result suggests that proving these statements in constructive topology requires genuine extensions of CZF with the elementary or finitary NID. (shrink)

The question of whether knowledge is definable in terms of belief, which has played an important role in epistemology for the last 50 years, is studied here in the framework of epistemic and doxastic logics. Three notions of definability are considered: explicit definability, implicit definability, and reducibility, where explicit definability is equivalent to the combination of implicit definability and reducibility. It is shown that if knowledge satisfies any set of axioms contained in S5, then it cannot be explicitly defined in (...) terms of belief. S5 knowledge can be implicitly defined by belief, but not reduced to it. On the other hand, S4.4 knowledge and weaker notions of knowledge cannot be implicitly defined by belief, but can be reduced to it by defining knowledge as true belief. It is also shown that S5 knowledge cannot be reduced to belief and justification, provided that there are no axioms that involve both belief and justification. (shrink)

After revelations of participation by psychiatrists and psychologists in interrogation of prisoners at Guantánamo Bay and Central Intelligence Agency secret detention centers, the American Psychiatric Association and the American Psychological Association adopted Position Statements absolutely prohibiting their members from participating in torture under any and all circumstances, and, to a limited degree, forbidding involvement in interrogations. Some interrogations utilize very aggressive techniques determined to be torture by many nations and organizations throughout the world. This paper explains why psychiatrists and psychologists (...) involved in coercive interrogations violate the Geneva Conventions and the laws of the United States. Whether done with ignorance of professional ethical obligations or not, these psychiatrists and psychologists have crossed an ethical barrier that may best be averted from re-occurring by teaching medical students and residents in all medical specialties about the ethics principles stemming from the 1946–1947 Nuremberg trials and the Geneva Conventions, together with the Ethics Codes of the World Medical Association and the American Medical Association; and, with regard to psychiatric residents and psychological trainees, by the teaching about The Principles of Medical Ethics With Annotations Especially Applicable to Psychiatry and the Ethical Principles of Psychologists and Code of Conduct, respectively. In this way, all physicians and psychologists will clearly understand that they have an absolute moral obligation to "First, do no harm" to the human beings they professionally encounter. (shrink)

While much of the social and political attention surrounding the nationwide opioid epidemic has focused on the dramatic increase in overdose deaths among white, middle-class, suburban and rural users, the impact of the epidemic in Black communities has largely been unrecognized. Though rates of opioid use at the national scale are higher for whites than they are for Blacks, rates of increase in opioid deaths have been rising more steeply among Blacks than whites over the last five years. Moreover, the (...) rate of opioid overdose deaths among Blacks already exceeds that of whites in several states. The lack of discussion of Black overdose deaths in the national opioid discourse further marginalizes Black people, and is highly consistent with a history of framing the addictions of people of color as deserving of criminal punishment, rather than worthy of medical treatment. This article argues that, because racial inequalities are embedded in American popular and political cultures as well as in medicine, the federal and state governments should develop more culturally targeted programs to benefit Black communities in the opioid crisis. Such programs include the use of faith-based organizations to deliver substance use prevention and treatment services, the inclusion of racial impact assessments in the implementation of drug policy proposals, and the formal consideration of Black people's interaction with the criminal justice system in designing treatment options. (shrink)

We propose new definitions of explanation, using structural equations to model counterfactuals. The definition is based on the notion of actual cause, as defined and motivated in a companion article. Essentially, an explanation is a fact that is not known for certain but, if found to be true, would constitute an actual cause of the fact to be explained, regardless of the agent’s initial uncertainty. We show that the definition handles well a number of problematic examples from the literature.

Three notions of definability in multimodal logic are considered. Two are analogous to the notions of explicit definability and implicit definability introduced by Beth in the context of first-order logic. However, while by Beth’s theorem the two types of definability are equivalent for first-order logic, such an equivalence does not hold for multimodal logics. A third notion of definability, reducibility, is introduced; it is shown that in multimodal logics, explicit definability is equivalent to the combination of implicit definability and reducibility. (...) The three notions of definability are characterized semantically using algebras. The use of algebras, rather than frames, is shown to be necessary for these characterizations. (shrink)

Good scientific research depends on critical thinking at least as much as factual knowledge; psychology is no exception to this rule. And yet, despite the importance of critical thinking, psychology students are rarely taught how to think critically about the theories, methods, and concepts they must use. This book shows students and researchers how to think critically about key topics such as experimental research, statistical inference, case studies, logical fallacies, and ethical judgments. Using updated research findings and new insights, this (...) volume provides a comprehensive overview of what critical thinking is and how to teach it in psychology. Written by leading experts in critical thinking in psychology, each chapter contains useful pedagogical features, such as critical-thinking questions, brief summaries, and definitions of key terms. It also supplies descriptions of each chapter author's critical-thinking experience, which evidences how critical thinking has made a difference to facilitating career development. (shrink)

What are the limits of the use of artificial intelligence (AI) in the relational aspects of medical and nursing care? There has been a lot of recent work and applications showing the promise and efficiency of AI in clinical medicine, both at the research and treatment levels. Many of the obstacles discussed in the literature are technical in character, regarding how to improve and optimize current practices in clinical medicine and also how to develop better data bases for optimal parameter (...) adjustments and predictive algorithms. This paper argues that there are also in principle obstacles to the application of AI in clinical medicine and care where empathy is important, and that these problems cannot be solved with any of the technical and theoretical approaches that shape the current application of AI in specific areas of clinical medicine in which care for patients is fundamental. This is important, because it generates specific risks that may be overlooked otherwise, and it justifies the necessity of human monitoring and emotional intervention in clinical medicine. Consequently, difficult issues concerning moral and legal responsibility may ensue if these in principle problems are ignored. (shrink)

Using formal systems to represent and reason about uncertainty.

A new approach for defining causality and such related notions as degree of responsibility, degrees of blame, and causal explanation. Causality plays a central role in the way people structure the world; we constantly seek causal explanations for our observations. But what does it even mean that an event C "actually caused" event E? The problem of defining actual causation goes beyond mere philosophical speculation. For example, in many legal arguments, it is precisely what needs to be established in order (...) to determine responsibility. The philosophy literature has been struggling with the problem of defining causality since Hume. In this book, Joseph Halpern explores actual causality, and such related notions as degree of responsibility, degree of blame, and causal explanation. The goal is to arrive at a definition of causality that matches our natural language usage and is helpful, for example, to a jury deciding a legal case, a programmer looking for the line of code that cause some software to fail, or an economist trying to determine whether austerity caused a subsequent depression. Halpern applies and expands an approach to causality that he and Judea Pearl developed, based on structural equations. He carefully formulates a definition of causality, and building on this, defines degree of responsibility, degree of blame, and causal explanation. He concludes by discussing how these ideas can be applied to such practical problems as accountability and program verification. Technical details are generally confined to the final section of each chapter and can be skipped by non-mathematical readers. (shrink)

Professor Judea Pearl won the 2011 Turing Award "for fundamental contributions to artificial intelligence through the development of a calculus for probabilistic and causal reasoning." This book contains the original articles that led to the award, as well as other seminal works, divided into four parts: heuristic search, probabilistic reasoning, causality, first period (1988-2001), and causality, recent period (2002-2020). Each of these parts starts with an introduction written by Judea Pearl. The volume also contains original, contributed articles by leading researchers (...) that analyze, extend, or assess the influence of Pearl's work in different fields: from AI, Machine Learning, and Statistics to Cognitive Science, Philosophy, and the Social Sciences. The first part of the volume includes a biography, a transcript of his Turing Award Lecture, two interviews, and a selected bibliography annotated by him. (shrink)

The success of deep brain stimulation (DBS) for movement disorders and the improved understanding of the neurobiologic and neuroanatomic bases of psychiatric diseases have led to proposals to expand current DBS applications. Recent preclinical and clinical work with Alzheimer's disease and obsessive-compulsive disorder, for example, supports the safety of stimulating regions in the hypothalamus and nucleus accumbens in humans. These regions are known to be involved in addiction and overeating associated with obesity. However, the use of DBS targeting these areas (...) as a treatment modality raises common ethical considerations, which include informed consent, coercion, enhancement, threat to personhood, and manipulation of the reward center. Pilot studies for both of these conditions are currently investigational. If these studies show promise, then there is a need to address the ethical concerns related to the initiation of clinical trials including the reliability of preclinical evidence, patient selection, study design, compensation for participation and injury, cost-effectiveness, and the need for long-term follow-up. Multidisciplinary teams are necessary for the ethical execution of such studies. In addition to establishing safety and efficacy, the consideration of these ethical issues is vital to the adoption of DBS as a treatment for these conditions. We offer suggestions about the pursuit of future clinical trials of DBS for the treatment of addiction and overeating associated with obesity and provide a framework for addressing ethical concerns related to treatment. (shrink)

Recent work in psychology and experimental philosophy has shown that judgments of actual causation are often influenced by consideration of defaults, typicality, and normality. A number of philosophers and computer scientists have also suggested that an appeal to such factors can help deal with problems facing existing accounts of actual causation. This article develops a flexible formal framework for incorporating defaults, typicality, and normality into an account of actual causation. The resulting account takes actual causation to be both graded and (...) comparative. We then show how our account would handle a number of standard cases. 1 Introduction2 Causal Models3 The HP Definition of Actual Causation4 The Problem of Isomorphism5 Defaults, Typicality, and Normality6 Extended Causal Models7 Examples7.1 Omissions7.2 Knobe effects7.3 Causes versus background conditions7.4 Bogus prevention7.5 Causal chains7.6 Legal doctrines of intervening causes7.7 Pre-emption and short circuits8 Conclusion. (shrink)

We propose a new definition of actual causes, using structural equations to model counterfactuals. We show that the definition yields a plausible and elegant account of causation that handles well examples which have caused problems for other definitions and resolves major difficulties in the traditional account.

Despite some principal similarities, there is no systematic comparison between the different types of synesthesia . This comprehensive review compares the three principal types of synesthesia and focuses on their phenomenological features and their relation to different etiological models. Implications of this comparison for the validity of the different etiological models are discussed.Comparison of the three forms of synesthesia show many more differences than similarities. This is in contrast to their representation in the literature, where they are discussed in many (...) respects as being virtually similar. Noteworthy is the much broader spectrum and intensity with the typical drug-induced synesthesias compared to genuine and acquired synesthesias. A major implication of the phenomenological comparison in regard to the etiological models is that genuine and acquired synesthesias point to morphological substrates, while drug-induced synesthesia appears to be based on functional changes of brain activity. (shrink)

the recent announcement of the claimed births of CRISPR-edited babies has prompted both widespread condemnation and calls by leading scientists for a moratorium on any further germline genome editing for reproductive purposes. Concurrently, national and international bodies are calling for the development of robust guidelines and requirements that will identify permissible conditions under which such GGE efforts may proceed. As detailed recommendations to navigate this unique terrain are under development, we suggest an approach that begins with identifying serious concerns about (...) social exclusion and social justice that arise... (shrink)

This book offers an in-depth analysis of the cognitive and ethical role of emotion, particularly empathy, in medical practice. The author explains how doctors can use empathy in diagnosing and treating patients without jeopardizing their objectivity or projecting their own values on to patients.

The Covid‐19 crisis has accelerated a trend toward burnout in health care workers, making starkly clear that burnout is especially likely when providing health care is not only stressful and sad but emotionally alienating; in such situations, there is no mental space for clinicians to experience authentic clinical empathy. Engaged curiosity toward each patient is a source of meaning and connection for health care providers, and it protects against sympathetic distress and burnout. In a prolonged crisis like Covid‐19, clinicians provide (...) care out of a sense of duty, especially the duty of nonabandonment. We argue that when duty alone is relied on too heavily, with fear and frustration continually suppressed, the risk of burnout is dramatically increased. Even before Covid‐19, clinicians often worked under dehumanizing and unjust conditions, and rates of burnout were 50 percent for physicians and 33 percent for nurses. The Covid‐19 intensification of burnout can serve as a wake‐up call that the structure of health care needs to be improved if we are to prevent the loss of a whole generation of empathic clinicians. (shrink)

ABSTRACT For changing opinion, represented by an assignment of probabilities to propositions, the criterion proposed is motivated by the requirement that the assignment should have, and maintain, the possibility of matching in some appropriate sense statistical proportions in a population. This ‘tracking’ criterion implies limitations on policies for updating in response to a wide range of types of new input. Satisfying the criterion is shown equivalent to the principle that the prior must be a convex combination of the possible posteriors. (...) Furthermore, this is equivalent to the requirement that prior expected values must fall inside the range spanned by possible posterior expected values. The tracking criterion is liberal; it allows for, but does not require, a policy such as Bayesian conditionalization, and can be offered as a general constraint on policies for managing opinion over time. Examples are given of non-Bayesian policies, both ones that satisfy and ones that violate the criterion. _1_ Introduction _2_ Alternative Updating Policies _3_ Modelling the Situation for Normal Updating _4_ Tracking: A Criterion for Updating Policies _5_ Tracking: Precise Formulation and Relation to Convexity _6_ The Spanning Criterion _7_ Non-Bayesian Policies that Satisfy the Spanning and Tracking Criteria _8_ Policies that Violate the Spanning and Tracking Criteria Appendix Appendix. (shrink)

For changing opinion, represented by an assignment of probabilities to propositions, the criterion proposed is motivated by the requirement that the assignment should have, and maintain, the possibility of matching in some appropriate sense statistical proportions in a population. This ‘tracking’ criterion implies limitations on policies for updating in response to a wide range of types of new input. Satisfying the criterion is shown equivalent to the principle that the prior must be a convex combination of the possible posteriors. Furthermore, (...) this is equivalent to the requirement that prior expected values must fall inside the range spanned by possible posterior expected values. The tracking criterion is liberal; it allows for, but does not require, a policy such as Bayesian conditionalization, and can be offered as a general constraint on policies for managing opinion over time. Examples are given of non-Bayesian policies, both ones that satisfy and ones that violate the criterion. 1 Introduction2 Alternative Updating Policies3 Modelling the Situation for Normal Updating4 Tracking: A Criterion for Updating Policies5 Tracking: Precise Formulation and Relation to Convexity6 The Spanning Criterion7 Non-Bayesian Policies that Satisfy the Spanning and Tracking Criteria8 Policies that Violate the Spanning and Tracking Criteria AppendixAppendix. (shrink)

Causal models have proven extremely useful in offering formal representations of causal relationships between a set of variables. Yet in many situations, there are non-causal relationships among variables. For example, we may want variables LDL, HDL, and TOT that represent the level of low-density lipoprotein cholesterol, the level of lipoprotein high-density lipoprotein cholesterol, and total cholesterol level, with the relation LDL+HDL=TOT. This cannot be done in standard causal models, because we can intervene simultaneously on all three variables. The goal of (...) this paper is to extend standard causal models to allow for constraints on settings of variables. Although the extension is relatively straightforward, to make it useful we have to define a new intervention operation that disconnects a variable from a causal equation. We give examples showing the usefulness of this extension, and provide a sound and complete axiomatization for causal models with constraints. (shrink)

As autonomous systems rapidly become ubiquitous, there is a growing need for a legal and regulatory framework to address when and how such a system harms someone. There have been several attempts within the philosophy literature to define harm, but none of them has proven capable of dealing with with the many examples that have been presented, leading some to suggest that the notion of harm should be abandoned and "replaced by more well-behaved notions". As harm is generally something that (...) is caused, most of these definitions have involved causality at some level. Yet surprisingly, none of them makes use of causal models and the definitions of actual causality that they can express. In this paper we formally define a qualitative notion of harm that uses causal models and is based on a well-known definition of actual causality (Halpern, 2016). The key novelty of our definition is that it is based on contrastive causation and uses a default utility to which the utility of actual outcomes is compared. We show that our definition is able to handle the examples from the literature, and illustrate its importance for reasoning about situations involving autonomous systems. (shrink)

Scientific models describe natural phenomena at different levels of abstraction. Abstract descriptions can provide the basis for interventions on the system and explanation of observed phenomena at a level of granularity that is coarser than the most fundamental account of the system. Beckers and Halpern (2019), building on work of Rubenstein et al. (2017), developed an account of abstraction for causal models that is exact. Here we extend this account to the more realistic case where an abstract causal model (...) offers only an approximation of the underlying system. We show how the resulting account handles the discrepancy that can arise between low- and high-level causal models of the same system, and in the process provide an account of how one causal model approximates another, a topic of independent interest. Finally, we extend the account of approximate abstractions to probabilistic causal models, indicating how and where uncertainty can enter into an approximate abstraction. (shrink)

We consider a sequence of successively more restrictive definitions of abstraction for causal models, starting with a notion introduced by Rubenstein et al. (2017) called exact transformation that applies to probabilistic causal models, moving to a notion of uniform transformation that applies to deterministic causal models and does not allow differences to be hidden by the "right" choice of distribution, and then to abstraction, where the interventions of interest are determined by the map from low-level states to high-level states, and (...) strong abstraction, which takes more seriously all potential interventions in a model, not just the allowed interventions. We show that procedures for combining micro-variables into macro-variables are instances of our notion of strong abstraction, as are all the examples considered by Rubenstein et al. (shrink)