The free-energy principle states that all systems that minimize their free energy resist a tendency to physical disintegration. Originally proposed to account for perception, learning, and action, the free-energy principle has been applied to the evolution, development, morphology, anatomy and function of the brain, and has been called a postulate, an unfalsifiable principle, a natural law, and an imperative. While it might afford a theoretical foundation for understanding the relationship between environment, life, and mind, its epistemic status is unclear. Also (...) unclear is how the free-energy principle relates to prominent theoretical approaches to life science phenomena, such as organicism and mechanism. This paper clarifies both issues, and identifies limits and prospects for the free-energy principle as a first principle in the life sciences. (shrink)

In this volume, a range of high-profile researchers in philosophy of mind, philosophy of cognitive science, and empirical cognitive science, critically engage with Clark's work across the themes of: Extended, Embodied, Embedded, Enactive, and Affective Minds; Natural Born Cyborgs; and Perception, Action, and Prediction. Daniel Dennett provides a foreword on the significance of Clark's work, and Clark replies to each section of the book, thus advancing current literature with original contributions that will form the basis for new discussions, debates and (...) directions in the discipline. (shrink)

It is often claimed that the greatest value of the Bayesian framework in cognitive science consists in its unifying power. Several Bayesian cognitive scientists assume that unification is obviously linked to explanatory power. But this link is not obvious, as unification in science is a heterogeneous notion, which may have little to do with explanation. While a crucial feature of most adequate explanations in cognitive science is that they reveal aspects of the causal mechanism that produces the phenomenon to be (...) explained, the kind of unification afforded by the Bayesian framework to cognitive science does not necessarily reveal aspects of a mechanism. Bayesian unification, nonetheless, can place fruitful constraints on causal–mechanical explanation. 1 Introduction2 What a Great Many Phenomena Bayesian Decision Theory Can Model3 The Case of Information Integration4 How Do Bayesian Models Unify?5 Bayesian Unification: What Constraints Are There on Mechanistic Explanation?5.1 Unification constrains mechanism discovery5.2 Unification constrains the identification of relevant mechanistic factors5.3 Unification constrains confirmation of competitive mechanistic models6 ConclusionAppendix. (shrink)

Bazzocchi disposes the text of the Tractatus in a user-friendly manner, exactly as Wittgenstein's decimals advise. This discloses the logical form of the book by distinct reading units, linked into a fashioned hierarchical tree. The text becomes much clearer and every reader can enjoy, finally, its formal and literary qualities.

Following the September 2001 terrorist attacks on the United States, much support for torture interrogation of terrorists has emerged in the public forum, largely based on the “ticking bomb” scenario. Although deontological and virtue ethics provide incisive arguments against torture, they do not speak directly to scientists and government officials responsible for national security in a utilitarian framework. Drawing from criminology, organizational theory, social psychology, the historical record, and my interviews with military professionals, I assess the potential of an official (...) U.S. program of torture interrogation from a practical perspective. The central element of program design is a sound causal model relating input to output. I explore three principal models of how torture interrogation leads to truth: the animal instinct model, the cognitive failure model, and the data processing model. These models show why torture interrogation fails overall as a counterterrorist tactic. They also expose the processes that lead from a precision torture interrogation program to breakdowns in key institutions—health care, biomedical research, police, judiciary, and military. The breakdowns evolve from institutional dynamics that are independent of the original moral rationale. The counterargument, of course, is that in a society destroyed by terrorism there will be nothing to repair. That is why the actual causal mechanism of torture interrogation in curtailing terrorism must be elucidated by utilitarians rather than presumed. (shrink)

We examine the role of the American Psychological Association (APA) in the weaponization of American psychology post-9/11. In 2004, psychologists’ involvement in the detention and interrogation of terrorist suspects generated controversy over psychological ethics in national security (PENS). Two signal events inflamed the controversy. The 2005 APA PENS Report legitimized clinical psychology consultation in support of military/intelligence operations with detained terrorist suspects. An independent review, the 2015 Hoffman Report, found APA collusion with the US Department of Defense in producing the (...) APA PENS Report and subsequent policies. Ongoing activities within APA to weaponize psychology sharpened the controversy. The authors—two psychologists and four former military/intelligence professionals—bring a military/intelligence operational perspective to detail two neglected areas of collateral damage. The first is the toll on psychology as a scientific enterprise. The second is covert influence on professional associations for incompatible security-sector objectives. We establish epistemic, historical, institutional, legal, and operational foundations for evaluation of these damages, as well as implications for APA and related professional associations in the ongoing Global War on Terror. (shrink)

O’Donohue et al. sought to derive, from classical ethical theories, the ethical obligation of psychologists to assist “enhanced interrogations and torture” in national defense scenarios under strict EIT criteria. They asked the American Psychological Association to adopt an ethics code obligating psychologists to assist such EIT and to uphold the reputation of EIT psychologists. We contest the authors’ ethical analyses as supports for psychologists’ forays into torture interrogation when the EIT criteria obtain. We also contend that the authors’ application of (...) these ethical analyses violates the Geneva Conventions, contravenes military doctrine and operations, and undermines psychology as a profession. We conclude that “good” public reputation is not owed to, or expected by, “good” intelligence professionals, and collaborating operational psychologists must share their providence. (shrink)

abstract Much of the literature on torture in recent years takes the position of denouncing the barbarity of torture, while allowing for exceptions to this veto in extreme circumstances. The ticking‐bomb argument, where a terrorist is tortured in order to extract information of a primed bomb located in a civilian area, is often invoked as one of those extreme circumstances where torture becomes justified. As the War on Terrorism intensifies, the ticking‐bomb argument has become the dominant line of reasoning used (...) by both academics and policy advisers to justify a legalized, state‐sponsored program of torture. This paper argues for the unconditional refutation of any attempt to justify torture, without exceptions. We argue against the consequentialist reasoning of the ticking‐bomb argument not from a deontological position, but on consequentialist grounds. Empirical evidence suggests that the institutionalization of torture practices creates serious problems. Torture interrogation fails to fulfil its initial purpose as a low‐cost life saver, while its long‐term potential is the devastation of democratic institutions. (shrink)

This article further elaborates on the “pre-crime society” thesis as developed and examined by Arrigo and Sellers. Specifically, the article focuses on the ultramodern era of digital inter-connectivity and argues that productive psychic desire is held clinically captive. Ultra-modernity is populated by cyber-forms of human relating and of economic exchange that nurture hyper-securitization. We discuss how the maintenance of hyper-securitization supports a pre-crime society, and how hyper-securitization’s object of desire consists of sign-optics. We argue that the co-constitutive forces of (...) this desire represent the sign-exchange values of post-criminology. Post-criminology’s signifiers include, among others, “predictive policing”, “crime mapping”, and “actuarial penology.” Post-criminology’s signifieds produce captivity-generating bio-digital “laws” of human relatedness. Among others, these laws sanction the neurosis of de-vitalization and certify the psychosis of finalization. We explain how the unchecked excess neutralizations of de-vitalization and finalization cultivate clinical captivity. Clinical captivity is a social anxiety in which reciprocal consciousness, inter-subjectivity, and mutual power are limited in existence or are denied an existence. (shrink)

The continuous growth of the pharmaceutical industry is expected to require a considerable output of new drugs, with speedy development and approval processes. This profit-driven expansion of the drug market may broaden the already established erosion of the role of academia in favor of commercial clinical research organizations. Less and less control on the clinical trial design, its conduct and the resulting publication[s] is the likely consequence. Academic medicine and governments should find means to sustain the development of independent clinical (...) research. (shrink)

Some naturalistic philosophers of mind subscribing to the predictive processing theory of mind have adopted a realist attitude towards the results of Bayesian cognitive science. In this paper, we argue that this realist attitude is unwarranted. The Bayesian research program in cognitive science does not possess special epistemic virtues over alternative approaches for explaining mental phenomena involving uncertainty. In particular, the Bayesian approach is not simpler, more unifying, or more rational than alternatives. It is also contentious that the Bayesian approach (...) is overall better supported by the empirical evidence. So, to develop philosophical theories of mind on the basis of a realist interpretation of results from Bayesian cognitive science is unwarranted. Naturalistic philosophers of mind should instead adopt an anti-realist attitude towards these results and remain agnostic as to whether Bayesian models are true. For continuing on with an exclusive focus and praise of Bayes within debates about the predictive processing theory will impede progress in philosophical understanding of scientific practice in computational cognitive science as well as of the architecture of the mind. (shrink)

Computational approaches dominate contemporary cognitive science, promising a unified, scientific explanation of how the mind works. However, computational approaches raise major philosophical and scientific questions. In what sense is the mind computational? How do computational approaches explain perception, learning, and decision making? What kinds of challenges should computational approaches overcome to advance our understanding of mind, brain, and behaviour? The Routledge Handbook of the Computational Mind is an outstanding overview and exploration of these issues and the first philosophical collection of (...) its kind. Comprising thirty-five chapters by an international team of contributors from different disciplines, the Handbook is organised into four parts: History and future prospects of computational approaches Types of computational approach Foundations and challenges of computational approaches Applications to specific parts of psychology. Essential reading for students and researchers in philosophy of mind, philosophy of psychology, and philosophy of science, The Routledge Handbook of the Computational Mind will also be of interest to those studying computational models in related subjects such as psychology, neuroscience, and computer science. (shrink)

A widely shared view in the cognitive sciences is that discovering and assessing explanations of cognitive phenomena whose production involves uncertainty should be done in a Bayesian framework. One assumption supporting this modelling choice is that Bayes provides the best approach for representing uncertainty. However, it is unclear that Bayes possesses special epistemic virtues over alternative modelling frameworks, since a systematic comparison has yet to be attempted. Currently, it is then premature to assert that cognitive phenomena involving uncertainty are best (...) explained within the Bayesian framework. As a forewarning, progress in cognitive science may be hindered if too many scientists continue to focus their efforts on Bayesian modelling, which risks to monopolize scientific resources that may be better allocated to alternative approaches. (shrink)

According to the free energy principle, life is an “inevitable and emergent property of any random dynamical system at non-equilibrium steady state that possesses a Markov blanket” :20130475, 2013). Formulating a principle for the life sciences in terms of concepts from statistical physics, such as random dynamical system, non-equilibrium steady state and ergodicity, places substantial constraints on the theoretical and empirical study of biological systems. Thus far, however, the physics foundations of the free energy principle have received hardly any attention. (...) Here, we start to fill this gap and analyse some of the challenges raised by applications of statistical physics for modelling biological targets. Based on our analysis, we conclude that model-building grounded in the free energy principle exacerbates a trade-off between generality and realism, because of a fundamental mismatch between its physics assumptions and the properties of actual biological targets. (shrink)

Life-science phenomena are often explained by specifying the mechanisms that bring them about. The new mechanistic philosophers have done much to substantiate this claim and to provide us with a better understanding of what mechanisms are and how they explain. Although there is disagreement among current mechanists on various issues, they share a common core position and a seeming commitment to some form of scientific realism. But is such a commitment necessary? Is it the best way to go about mechanistic (...) explanation? In this article, we propose an alternative antirealist account that also fits explanatory practice in the life sciences. We pay special attention to mechanistic models, i.e. scientific models that involve a mechanism, and to the role of coherence considerations in building such models. To illustrate our points, we consider the mechanism for the action potential. 1 Introduction2 Some Core Features of Mechanistic Explanation3 Scientific Realism and Mechanistic Explanation4 Antirealist Mechanistic Explanation: The Case of the Action Potential5 Some Outstanding Issues for the Antirealist Mechanist6 Two Problems for the Realist Mechanist7 Conclusions. (shrink)

According to a growing trend in theoretical neuroscience, the human perceptual system is akin to a Bayesian machine. The aim of this article is to clearly articulate the claims that perception can be considered Bayesian inference and that the brain can be considered a Bayesian machine, some of the epistemological challenges to these claims; and some of the implications of these claims. We address two questions: (i) How are Bayesian models used in theoretical neuroscience? (ii) From the use of Bayesian (...) models in theoretical neuroscience, have we learned or can we hope to learn that perception is Bayesian inference or that the brain is a Bayesian machine? From actual practice in theoretical neuroscience, we argue for three claims. First, currently Bayesian models do not provide mechanistic explanations; instead they are useful devices for predicting and systematizing observational statements about people's performances in a variety of perceptual tasks. That is, currently we should have an instrumentalist attitude towards Bayesian models in neuroscience. Second, the inference typically drawn from Bayesian behavioural performance in a variety of perceptual tasks to underlying Bayesian mechanisms should be understood within the three-level framework laid out by David Marr ( [1982] ). Third, we can hope to learn that perception is Bayesian inference or that the brain is a Bayesian machine to the extent that Bayesian models will prove successful in yielding secure and informative predictions of both subjects' perceptual performance and features of the underlying neural mechanisms. (shrink)

The finding that intuitions about the reference of proper names vary cross-culturally was one of the early milestones in experimental philosophy. Many follow-up studies investigated the scope and magnitude of such cross-cultural effects, but our paper provides the first systematic meta-analysis of studies replicating. In the light of our results, we assess the existence and significance of cross-cultural effects for intuitions about the reference of proper names.

Climate change, nutrition, poverty and medical drugs are widely discussed and pressing issues in science, policy and society. Despite these issues being of great importance for the quality of our lives it remains unclear how well people understand them. Specifically, do particular demographic and socioeconomic factors explain variation in public understanding of these four concepts? To what extent are people’s changes in understanding associated with changes in their behaviour? Do people judge scientific practices relying on the more descriptive concepts of (...) climate change and effective medical drugs to be more objective (less controversial) than practices relying on the more value-laden concepts of poverty and healthy nutrition? To address these questions, an experimental survey and regression analyses are conducted using data collected from about one thousand participants across different continents. The study finds that public understanding of science is generally low. A smaller proportion of people were able to correctly identify the common explanation accepted internationally among the scientific community for climate change and effectiveness of medical drugs (42% and 43% of participants in the study, respectively) than for poverty and healthy nutrition (61% and 65% of participants, respectively). Older age and political non-conservativeness were the strongest predictors of correctly understanding these four concepts. Greater levels of education and political non-conservativeness were in turn the strongest predictors of people’s reported changes in their behaviour based on their improved understanding of these concepts. Because climate change is among the least understood scientific concepts but is arguably the greatest challenge of our time, better efforts are needed to improve how media, awareness campaigns and education systems mediate information on the topic in order to tackle the large knowledge deficits that constrain behavioural change. (shrink)

This highly original book develops a systematic zero-net-profit comparative statics theory of the firm that challenges many widely held views in microeconomics. It builds a bridge between the marginalist long-run theory of the firm and Sraffian theory to create a unified theoretical framework that explains how firms react to exogenous shocks resulting in new equilibrium positions of the whole economy. The central message of the book is that too often economists expect more from the microeconomic laws of input demand and (...) output supply than they can really give. The authors show that the zero-net-profit condition requires a more articulated analysis that sometimes yields qualitative results contrary to those of familiar economic laws. Written for academic researchers and graduate students, the book will be of particular interest to those working on the microeconomics of industry equilibrium, comparative statics and Sraffian economics. (shrink)