There have been two major lines of research aimed at capturing resource-bounded players in game theory. The first, initiated by Rubinstein (), charges an agent for doing costly computation; the second, initiated by Neyman (), does not charge for computation, but limits the computation that agents can do, typically by modeling agents as finite automata. We review recent work on applying both approaches in the context of decision theory. For the first approach, we take the objects of choice in a (...) decision problem to be Turing machines, and charge players for the “complexity” of the Turing machine chosen (e.g., its running time). This approach can be used to explain well-known phenomena like first-impression-matters biases (i.e., people tend to put more weight on evidence they hear early on) and belief polarization (two people with different prior beliefs, hearing the same evidence, can end up with diametrically opposed conclusions) as the outcomes of quite rational decisions. For the second approach, we model people as finite automata, and provide a simple algorithm that, on a problem that captures a number of settings of interest, provably performs optimally as the number of states in the automaton increases. (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)

The eminent political scientist Manfred Halpern viewed politics as belonging to each of us, as part of the nature of being human. In A Comprehensive Philosophy of Transformation, his magnum opus, Halpern elucidates the interconnected “four faces of our being”: the political, personal, historical, and sacred. This momentous volume identifies several modes of political activity, warns against the dangers of leaving politics to professional politicians, and urges us to build networks of compassion that include everyone in a just (...) society. Overall, Halpern calls for a transformative politics achieved through enhanced participation and understanding. (shrink)

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)

When the fuzzy indeterminacy of quantum mechanics overthrew the orderly world of Isaac Newton, Albert Einstein and Erwin Schrödinger were at the forefront of the revolution. Neither man was ever satisfied with the standard interpretation of quantum mechanics, however, and both rebelled against what they considered the most preposterous aspect of quantum mechanics: its randomness. Einstein famously quipped that God does not play dice with the universe, and Schrödinger constructed his famous fable of a cat that was neither alive nor (...) dead not to explain quantum mechanics but to highlight the apparent absurdity of a theory gone wrong. But these two giants did more than just criticize: they fought back, seeking a Theory of Everything that would make the universe seem sensible again. In Einstein’s Dice and Schrödinger’s Cat, physicist Paul Halpern tells the little-known story of how Einstein and Schrödinger searched, first as collaborators and then as competitors, for a theory that transcended quantum weirdness. This story of their quest—which ultimately failed—provides readers with new insights into the history of physics and the lives and work of two scientists whose obsessions drove its progress. Today, much of modern physics remains focused on the search for a Theory of Everything. As Halpern explains, the recent discovery of the Higgs Boson makes the Standard Model—the closest thing we have to a unified theory— nearly complete. And while Einstein and Schrödinger failed in their attempt to explain everything in the cosmos through pure geometry, the development of string theory has, in its own quantum way, brought this idea back into vogue. As in so many things, even when they were wrong, Einstein and Schrödinger couldn’t help but get a great deal right. (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 consider a setting where a decision maker’s uncertainty is represented by a set of probability measures, rather than a single measure. Measure-by-measure updating of such a set of measures upon acquiring new information is well known to suffer from problems. To deal with these problems, we propose using weighted sets of probabilities: a representation where each measure is associated with a weight, which denotes its significance. We describe a natural approach to updating in such a situation and a natural (...) approach to determining the weights. We then show how this representation can be used in decision making, by modifying a standard approach to decision making—minimizing expected regret—to obtain minimax weighted expected regret. We provide an axiomatization that characterizes preferences induced by MWER both in the static and dynamic case. (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)

I show how thinking in terms of the protocol used can help clarify problems related to anthropic reasoning and self-location, such as the Doomsday Argument and the Sleeping Beauty Problem.

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)

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)

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)

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.

Using formal systems to represent and reason about uncertainty.

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)

Unrealistic therapeutic beliefs are very common—the majority of patient-subjects enrol in phase 1 trials seeking and expecting significant medical benefit, even though the likelihood of such benefit has historically proven very low. The high prevalence of therapeutic misestimation and unrealistic optimism in particular has stimulated debate about whether unrealistic therapeutic beliefs in early-phase clinical trials preclude adequate informed consent. We seek here to help resolve this controversy by showing that a crucial determination of when such therapeutic beliefs are ethically problematic (...) turns on whether they are causally linked and instrumental to the motivation to participate in the trial. Thus, in practice, it is ethically incumbent on researchers to determine which understanding and beliefs lead to the participant’s primary motivation for enrolling, not to simply assess understanding, beliefs and motivations independently. We further contend that assessing patient-subjects’ appreciation as a component of informed consent—it is already an established component of decision-making capacity assessments—can help elucidate the link between understanding-beliefs and motivation; appreciation refers to an individual’s understanding of the personal significance of both the medical facts and the experience of trial participation. Therefore, we recommend that: in addition to the usual question, ‘Why do you want to participate in this trial?’, all potential participants should be asked the question: ‘What are you giving up by participating in this trial?’ and researchers should consider the settings in which it may be possible and practical to obtain ‘two-point consent’. (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.

Popular and technical usages yield unequivocal definitions of "myth"' and "ideology," terms which imply distinct meanings of "history" as both accumulated symbolic product and dynamic symbolic production. "Culture," the historical symbolic realm, is analyzable objectively as accumulation in terms of art, law, etc., or subjectively as dynamic process through mythology and ideology-the former dealing with beliefs originating in historical experience, value integration, and establishment of consensus, the latter with beliefs originating in competitive social situations and their communication and segregation. Irrational (...) mythologies spark historical dynamism, rational ideologies extend it. Sorel, Mannheim, and other writers here examined use these distinctions systematically in historical interpretation. (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.

The field of science communication is plagued by challenges. Communicators face the difficulty of responding to unjustified public skepticism over issues like climate change and COVID-19 while also acknowledging the fallibility and limitations of scientific knowledge. Our goal in this paper is to suggest a new model for science communication that can help foster more productive, respectful relationships among all those involved in science communication. Inspired by the pragmatist philosophy of John Dewey, we develop an experience model, according to which (...) science communication consists in people’s experiences with science and the meanings they develop from those experiences. Three principles are central to the model: experience is cumulative, context matters, and audiences have agency. We argue that this model has significant implications both for communication research and practice, which we illustrate by applying it to the phenomenon of vaccine hesitancy. We show how science communicators can help to identify and alleviate structural factors that contribute to skepticism as well as fostering opportunities for meaning making around shared experiences. (shrink)

Judea Pearl (2000) was the first to propose a definition of actual causation using causal models. A number of authors have suggested that an adequate account of actual causation must appeal not only to causal structure but also to considerations of normality. In Halpern and Hitchcock (2011), we offer a definition of actual causation using extended causal models, which include information about both causal structure and normality. Extended causal models are potentially very complex. In this study, we show how (...) it is possible to achieve a compact representation of extended causal models. (shrink)

The current research investigates how religiosity can influence unethicality in a consumption context. In particular, considering the link between extrinsic religious orientations and unethicality, this research clarifies why and when extrinsic religiosity leads to unethical decisions. Across two studies, findings show that ethnocentrism is both a mediator and a moderator of the effects of extrinsic religiosity on consumers’ ethical judgments. This is because extrinsic religiosity leads to ethnocentrism, and in-group loyalty manifested through ethnocentrism increases support for unethical consumer actions, thus (...) establishing ethnocentrism as a mediator. At the same time, different levels of ethnocentrism can also influence how extrinsic religiosity leads to supporting unethical consumption via self-righteousness, thus establishing ethnocentrism as a moderator. The findings from this research have significant implications for diverse stakeholders who have an interest in religiosity and consumer behavior. (shrink)