Technoscientific ambitions for perfecting human-like machines, by advancing state-of-the-art neuromorphic architectures and cognitive computing, may end in ironic regret without pondering the humanness of fallible artificial non-normative personalities. Self-organizing artificial personalities individualize machine performance and identity through fuzzy conscientiousness, emotionality, extraversion/introversion, and other traits, rendering insights into technology-assisted human evolution, robot ethology/pedagogy, and best practices against unwanted autonomous machine behavior.

Emerging cybertechnologies, such as social digibots, bend epistemological conventions of life and culture already complicated by human and animal relationships. Virtually-augmented niches of machines and organic life promise new free-energy-governed selection of intelligent digital life. These provocative eco-evolutionary contexts demand a theory of (natural and artificial) minds to characterize and validate the immersive social phenomena universally-shaping cultural affordances.

Communication barriers long-associated with ideographs, including combinatorial grapholinguistic complexity, computational encoding–decoding complexity, and technological rendering and deployment, become trivialized through advancements in interoperable smart mobile digital devices. Such technologies impart unprecedented extended-reality user hazards only mitigated by unprecedented colloquial and bureaucratic societal norms. Digital age norms thus influence natural ideographic language origins and evolution in ways novel to human history.

Some neurotropic enteroviruses hijack Trojan horse/raft commensal gut bacteria to render devastating biomimicking cryptic attacks on human/animal hosts. Such virus-microbe interactions manipulate hosts’ gut-brain axes with accompanying infection-cycle-optimizing central nervous system disturbances, including severe neurodevelopmental, neuromotor, and neuropsychiatric conditions. Co-opted bacteria thus indirectly influence host health, development, behavior, and mind as possible “fair-weather-friend” symbionts, switching from commensal to context-dependent pathogen-like strategies benefiting gut-bacteria fitness.

Microbes perfect social interactions with intuitive logics and goal-directed reciprocity. These multilevel, cognition-resembling adaptations in Dictyostelid cellular molds enable individual-to-group viability through public/private bacterial farming and dynamic marketspaces. Like humans and animals, Dictyostelid livestock-ownership depends on environmental sensing, cooperation, and competition. Moreover, social-norm policing of cosmopolitan colonies coordinates farmer decisions, phenotypes, and ownership identities with bacteria herding, privatization, and consumption.

Graphical AbstractScience and technology consortia provide a viable solution for the recent unsustainable academic growth in biomedical research.

Mounting ambitions and capabilities for public and private, non-government sector crewed space exploration bring with them an increasingly diverse set of space travelers, raising new and nontrivial ethical, legal, and medical policy and practice concerns which are still relatively underexplored. In this piece, we lay out several pressing issues related to ethical considerations for selecting space travelers and conducting human subject research on them, especially in the context of non-governmental and commercial/private space operations.

Disputes between those holding differing political views are ubiquitous and deep-seated, and they often follow common, recognizable lines. The supporters of tradition and stability, sometimes referred to as conservatives, do battle with the supporters of innovation and reform, sometimes referred to as liberals. Understanding the correlates of those distinct political orientations is probably a prerequisite for managing political disputes, which are a source of social conflict that can lead to frustration and even bloodshed. A rapidly growing body of empirical evidence (...) documents a multitude of ways in which liberals and conservatives differ from each other in purviews of life with little direct connection to politics, from tastes in art to desire for closure and from disgust sensitivity to the tendency to pursue new information, but the central theme of the differences is a matter of debate. In this article, we argue that one organizing element of the many differences between liberals and conservatives is the nature of their physiological and psychological responses to features of the environment that are negative. Compared with liberals, conservatives tend to register greater physiological responses to such stimuli and also to devote more psychological resources to them. Operating from this point of departure, we suggest approaches for refining understanding of the broad relationship between political views and response to the negative. We conclude with a discussion of normative implications, stressing that identifying differences across ideological groups is not tantamount to declaring one ideology superior to another. (shrink)

The naturalistic fallacy is mentionedfrequently by evolutionary psychologists as anerroneous way of thinking about the ethicalimplications of evolved behaviors. However,evolutionary psychologists are themselvesconfused about the naturalistic fallacy and useit inappropriately to forestall legitimateethical discussion. We briefly review what thenaturalistic fallacy is and why it is misusedby evolutionary psychologists. Then we attemptto show how the ethical implications of evolvedbehaviors can be discussed constructivelywithout impeding evolutionary psychologicalresearch. A key is to show how ethicalbehaviors, in addition to unethical behaviors,can evolve by natural selection.

In 1978, as the protests against the Shah of Iran reached their zenith, philosopher Michel Foucault was working as a special correspondent for _Corriere della Sera_ and _le Nouvel Observateur_. During his little-known stint as a journalist, Foucault traveled to Iran, met with leaders like Ayatollah Khomeini, and wrote a series of articles on the revolution. _Foucault and the Iranian Revolution _is the first book-length analysis of these essays on Iran, the majority of which have never before appeared in English. (...) Accompanying the analysis are annotated translations of the Iran writings in their entirety and the at times blistering responses from such contemporaneous critics as Middle East scholar Maxime Rodinson as well as comments on the revolution by feminist philosopher Simone de Beauvoir. In this important and controversial account, Janet Afary and Kevin B. Anderson illuminate Foucault's support of the Islamist movement. They also show how Foucault's experiences in Iran contributed to a turning point in his thought, influencing his ideas on the Enlightenment, homosexuality, and his search for political spirituality. _Foucault and the Iranian Revolution_ informs current discussion on the divisions that have reemerged among Western intellectuals over the response to radical Islamism after September 11. Foucault's provocative writings are thus essential for understanding the history and the future of the West's relationship with Iran and, more generally, to political Islam. In their examination of these journalistic pieces, Afary and Anderson offer a surprising glimpse into the mind of a celebrated thinker. (shrink)

Marx concentrated on Western Europe and North America in his core writings, but discussions of Asia, the Middle East, Africa, Eastern Europe, and Latin America are scattered throughout his work. In the Communist Manifesto (1848) and his writings for the New York Tribune Marx posited a universal theory of historical and economic development in which non-Western societies represented backwardness, but could progress into modernity with the external impetus of the world market. Later, especially in the Grundrisse (1857-58) and the recently (...) available Ethnological Notebooks of 1879-82, Marx gradually altered this implicitly unilinear model, replacing it with a more multilinear one in which non-Western societies (in which he included Russia) might be able to embark upon an alternate form of modernity that would offer a new challenge to capitalist modernity. The basis of this alternate form was economic, in the “communal” property forms that he saw as underlying many Asian societies, as opposed to Western-style private property. (shrink)

The Lottery Paradox has been thought to provide a reductio argument against probabilistic accounts of inductive inference. As a result, much work in artificial intelligence has concentrated on qualitative methods of inference, including default logics, which are intended to model some varieties of inductive inference. It has recently been shown that the paradox can be generated within qualitative default logics. However, John Pollock's qualitative system of defeasible inference, does avoid the Lottery Paradox by incorporating a rule designed specifically for that (...) purpose. I shall argue that Pollock's system instead succumbs to a worse disease: it fails to allow for induction at all. (shrink)

Carter and Leslie's Doomsday Argument maintains that reflection upon the number of humans born thus far, when that number is viewed as having been uniformly randomly selected from amongst all humans, past, present and future, leads to a dramatic rise in the probability of an early end to the human experiment. We examine the Bayesian structure of the Argument and find that the drama is largely due to its oversimplification.

I consider three aspects in which machine learning and philosophy of science can illuminate each other: methodology, inductive simplicity and theoretical terms. I examine the relations between the two subjects and conclude by claiming these relations to be very close.

The promises of precision medicine are often heralded in the medical and lay literature, but routine integration of genomics in clinical practice is still limited. While the “last mile” infrastructure to bring genomics to the bedside has been demonstrated in some healthcare settings, a number of challenges remain — both in the receptivity of today's health system and in its technical and educational readiness to respond to this evolution in care. To improve the impact of genomics on health and disease (...) management, we will need to integrate both new knowledge and new care processes into existing workflows. This change will be onerous and time-consuming, but hopefully valuable to the provision of high quality, economically feasible care worldwide. (shrink)

We further develop the mathematical theory of causal interventions, extending earlier results of Korb, Twardy, Handfield, & Oppy, (2005) and Spirtes, Glymour, Scheines (2000). Some of the skepticism surrounding causal discovery has concerned the fact that using only observational data can radically underdetermine the best explanatory causal model, with the true causal model appearing inferior to a simpler, faithful model (cf. Cartwright, (2001). Our results show that experimental data, together with some plausible assumptions, can reduce the space of viable explanatory (...) causal models to one. (shrink)

The common opinion has been that evolution results in the continuing development of more complex forms of life, generally understood as more complex organisms. The arguments supporting that opinion have recently come under scrutiny and been found wanting. Nevertheless, the appearance of increasing complexity remains. So, is there some sense in which evolution does grow complexity? Artificial life simulations have consistently failed to reproduce even the appearance of increasing complexity, which poses a challenge. Simulations, as much as scientific theories, are (...) obligated at least to save the appearances! We suggest a relation between these two problems, understanding biological complexity growth and the failure to model even its appearances. We present a different understanding of that complexity which evolution grows, one that genuinely runs counter to entropy and has thus far eluded proper analysis in information-theoretic terms. This complexity is reflected best in the increase in niches within the biosystem as a whole. Past and current artificial life simulations lack the resources with which to grow niches and so to reproduce evolution’s complexity. We propose a more suitable simulation design integrating environments and organisms, allowing old niches to change and new ones to emerge. (shrink)

Karl Rahner and Hans Urs von Balthasar pushed back in various ways against the tide of historical criticism in the twentieth century. On the one hand Rahner wished to distance theology from biblical revelation in his turn towards the subject. In so doing, he sought to preserve theology from the rising tide of skepticism resulting from contemporary exegesis. His philosophical system left little room for historical revelation because of a fixation on individual revelation. Balthasar, on the other hand, questioned whether (...) the Rahnerian system strips Christianity of the need to bear witness to the world, and relativizes Christ’s Incarnation. Balthasar saw the indestructible unity of the form (gestalt) presented to humanity in the revelation of Old and New Testaments as an antidote to the fragmentation within biblical studies. Because of gestalt, Scripture is more than a mere sum of its parts. For Balthasar, the faith of the exegete is an irreplaceable requisite for accurate hermeneutics. Dispensing with the revelatory character of the Scriptures would also be unscientific; it is an unsuitable approach to a text that calls one to bear witness. Balthasar thus correctly called for a theological hermeneutic whereby the faithful exegete recognizes the unity of the scriptural account. (shrink)

This work provides a conceptual foundation for a Bayesian approach to artificial inference and learning. I argue that Bayesian confirmation theory provides a general normative theory of inductive learning and therefore should have a role in any artificially intelligent system that is to learn inductively about its world. I modify the usual Bayesian theory in three ways directly pertinent to an eventual research program in artificial intelligence. First, I construe Bayesian inference rules as defeasible, allowing them to be overridden in (...) certain contexts and therefore allowing them to play a part in a hybrid system, coexisting with non-Bayesian modes of inference. I take seriously the need to find meaningful prior probabilities for hypotheses, and elaborate means for supplying an artificial intelligence with such. And I address the computational complexity of Bayesian inference by reference to simplifications using causal networks and by allowing the probabilistic acceptance of hypotheses and subsequent qualitative inference to supplement Bayesian reasoning. The result is a Pragmatic Bayesian model of induction. (shrink)

Bayesian networks are computer programs which represent probabilitistic relationships graphically as directed acyclic graphs, and which can use those graphs to reason probabilistically , often at relatively low computational cost. Almost every expert system in the past tried to support probabilistic reasoning, but because of the computational difficulties they took approximating short-cuts, such as those afforded by MYCIN's certainty factors. That all changed with the publication of Judea Pearl's Probabilistic Reasoning in Intelligent Systems, in 1988, which synthesized a decade of (...) research making accurate graphical probabilistic reasoning computationally achievable.Bayesian network technology is now one of the fastest growing fields of research in artificial intelligence. That it has become a publication industry in its own right is shown by a search on Google scholar :This development, together with a parallel related growth in the use of causal discovery algorithms which automate the learning of Bayesian networks from sample data, has generated considerable interest, and controversy, within the philosophy-of-science community.Three central questions bringing together AI researchers and philosophers of science are: Are Bayesian networks Bayesian? What is the relation between probability and causality? Are the assumptions behind causal discovery of Bayesian networks realistic or fantastical?Jon Williamson, as a philosopher of science with a keen interest in the technology, asks and answers these questions in his new book. Although it is self-contained, his book is not very likely as an introduction to the technology , nor is it optimal even as an introduction to the philosophical problems in interpreting Bayesian networks . Rather Williamson's book is an attempt to move the debate forward by solving the central problems of the …. (shrink)

Rolls's presentation of emotion as integral to cognition is a welcome counter to a long tradition of treating them as antagonists. His eduction of experimental evidence in support of this view is impressive. However, we find his excursion into the philosophy of consciousness less successful. Rolls gives syntactical manipulation the central role in consciousness (in stark contrast to Searle, for whom “mere” syntax inevitably falls short of consciousness), and leaves us wondering about the roles left for emotion after all.

Louis Dupré’s death marks the passing of a philosopher who made a profound contribution to the study of Marx, Hegel, and the wider tradition, and who needs to be reread today. This memoriam acknowledges his importance through placing him in conversation with the great Marxist humanist Raya Dunayevskaya.

Dual labor market theory, developed as an explanation of underemployment and poverty within the economy, may also be applied to the illicit economy of crime. Criminal careers are differentiated into a primary sector, with occupational stability, low failure rate, and high chances of advancement; and a secondary sector, with instability, high failure rate, and lack of "market" control. The attraction of criminal careers, the likelihood of incarceration, and the effects of law enforcement are best understood in these contexts.

Organizational leaders are increasingly emphasizing a stakeholder perspective in order to address concerns about business ethics. This study examined the choices of 94 groups in the context of a business decision-making simulation to determine how specific actions and communications can facilitate the consideration of different stakeholder perspectives. In particular, we examined whether generally framing the business situation as one involving diverse stakeholders versus a primarily profit-driven operation (referred to as framing), and whether specific suggestions that participants consider the concerns of (...) stakeholders versus stockholders in maximizing the value of the firm (referred to as vision priming), would influence group choices and decision outcomes. We tested four experimental conditions against a control in a 2 × 2 experimental design to determine the effects that group choices had on decision outcomes when groups were exposed to stakeholder versus stockholder decision framing and stakeholder versus stockholder vision priming. The results revealed that the consistent conditions outperformed the control condition and that vision priming has a greater impact on decision outcomes than decision framing. (shrink)

Eight scholars answered the call printed in both issues of volume 19 of The Owl to “bone up for Loyola” by attending a week-long seminar devoted to the study of Hegel’s Science of Logic. The seminar was held at Windy Pine, a summer retreat of the Trent University Canadian Studies Program, on Kushog Lake in Ontario’s Haliburton Highlands. A half dozen rustic cabins lining a rocky, wooded cove provided a delightful setting for the exercise of both mind and body. The (...) best of Hegel, along with more empirical events such as enjoying fine food, swimming, canoeing, fishing, hiking, and long evenings of pleasant conversation left all of the participants wishing that Hegel had written a sequel. (shrink)

The use of artificial intelligence (AI) in hiring entails vast ethical challenges. As such, using an ethical lens to study this phenomenon is to better understand whether and how AI matters in hiring. In this paper, we examine whether ethical perceptions of using AI in the hiring process influence individuals’ trust in the organizations that use it. Building on the organizational trust model and the unified theory of acceptance and use of technology, we explore whether ethical perceptions are shaped by (...) individual differences in performance expectancy and social influence and how they, in turn, impact organizational trust. We collected primary data from over 300 individuals who were either active job seekers or who had recent hiring experience to capture perceptions across the full range of hiring methods. Our findings indicate that performance expectancy, but not social influence, impacts the ethical perceptions of AI in hiring, which in turn influence organizational trust. Additional analyses indicate that these findings vary depending on the type of hiring methods AI is used for, as well as on whether participants are job seekers or individuals with hiring experience. Our study offers theoretical and practical implications for ethics in HRM and informs policy implementation about when and how to use AI in hiring methods, especially as it pertains to acting ethically and trustworthily. (shrink)