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Resignation syndrome (RS) designates a long-standing disorder predominately affecting psychologically traumatized children and adolescents in the midst of a strenuous and lengthy migration process. Typically a depressive onset is followed by gradual withdrawal progressing via stupor into a state that prompts tube feeding and is characterized by failure to respond even to painful stimuli. The patient is seemingly unconscious. Recovery ensues within months to years and is claimed to be dependent on the restoration of hope to the family. Descriptions of disorders resembling RS can be found in the literature and the condition is unlikely novel. Nevertheless, the magnitude and geographical distribution stand out. Several hundred cases have been reported exclusively in Sweden in the past decade prompting the Swedish National Board of Health and Welfare to recognize RS as a separate diagnostic entity. The currently prevailing stress hypothesis fails to account for the regional distribution and contributes little to treatment. Consequently, a re-evaluation of diagnostics and treatment is required. Psychogenic catatonia is proposed to supply the best fit with the clinical presentation. Treatment response, altered brain metabolism or preserved awareness would support this hypothesis. Epidemiological data suggests culture-bound beliefs and expectations to generate and direct symptom expression and we argue that culture-bound psychogenesis can accommodate the endemic distribution. Last, we review recent models of predictive coding indicating how expectation processes are crucially involved in the placebo and nocebo effect, delusions and conversion disorders. Building on this theoretical framework we propose a neurobiological model of RS in which the impact of overwhelming negative expectations are directly causative of the down-regulation of higher order and lower order behavioral systems in particularly vulnerable individuals.

AI research is growing rapidly raising various ethical issues related to safety, risks, and other effects widely discussed in the literature. We believe that in order to adequately address those issues and engage in a productive normative discussion it is necessary to examine key concepts and categories. One such category is anthropomorphism. It is a well-known fact that AI's functionalities and innovations are often anthropomorphized (i.e., described and conceived as characterized by human traits). The general public's anthropomorphic attitudes and some of their ethical consequences (particularly in the context of social robots and their interaction with humans) have been widely discussed in the literature. However, how anthropomorphism permeates AI research itself (i.e., in the very language of computer scientists, designers, and programmers), and what the epistemological and ethical consequences of this might be have received less attention. In this paper we explore this issue. We first set the methodological/theoretical stage, making a distinction between a normative and a conceptual approach to the issues. Next, after a brief analysis of anthropomorphism and its manifestations in the public, we explore its presence within AI research with a particular focus on brain-inspired AI. Finally, on the basis of our analysis, we identify some potential epistemological and ethical consequences of the use of anthropomorphic language and discourse within the AI research community, thus reinforcing the need of complementing the practical with a conceptual analysis.

In the past decade, the perception of a bioterrorist threat has increased and created a demand on life scientists to consider the potential security implications of dual use research. This article examines a selection of proposed moral obligations for life scientists that have emerged to meet these concerns and the extent to which they can be considered reasonable. It also describes the underlying reasons for the concerns, how they are managed, and their implications for scientific values. Five criteria for what constitutes preventable harm are suggested and a number of proposed obligations for life scientists are considered against these criteria, namely, the obligations to prevent bioterrorism; to engage in response activities; to consider negative implications of research; not to publish or share sensitive information; to oversee and limit access to dangerous material; and to report activities of concern. Although bioterrorism might be perceived as an imminent threat, the analysis illustrates that this is beyond the responsibility of life scientists either to prevent or to respond to. Among the more reasonable obligations are duties to consider potential negative implications of one's research, protect access to sensitive material, technology and knowledge, and report activities of concern. Responsibility, therefore, includes obligations concerned with preventing foreseeable and highly probable harm. A central conclusion is that several of the proposed obligations are reasonable, although not unconditionally.

In today’s society, it becomes increasingly important to assess which non-human and non-verbal beings possess consciousness. This review article aims to delineate criteria for consciousness especially in animals, while also taking into account intelligent artifacts. First, we circumscribe what we mean with “consciousness” and describe key features of subjective experience: qualitative richness, situatedness, intentionality and interpretation, integration and the combination of dynamic and stabilizing properties. We argue that consciousness has a biological function, which is to present the subject with a multimodal, situational survey of the surrounding world and body, subserving complex decision-making and goal-directed behavior. This survey reflects the brain’s capacity for internal modeling of external events underlying changes in sensory state. Next, we follow an inside-out approach: how can the features of conscious experience, correlating to mechanisms inside the brain, be logically coupled to externally observable (“outside”) properties? Instead of proposing criteria that would each define a “hard” threshold for consciousness, we outline six indicators: (i) goal-directed behavior and model-based learning; (ii) anatomic and physiological substrates for generating integrative multimodal representations; (iii) psychometrics and meta-cognition; (iv) episodic memory; (v) susceptibility to illusions and multistable perception; and (vi) specific visuospatial behaviors. Rather than emphasizing a particular indicator as being decisive, we propose that the consistency amongst these indicators can serve to assess consciousness in particular species. The integration of scores on the various indicators yields an overall, graded criterion for consciousness, somewhat comparable to the Glasgow Coma Scale for unresponsive patients. When considering theoretically derived measures of consciousness, it is argued that their validity should not be assessed on the basis of a single quantifiable measure, but requires cross-examination across multiple pieces of evidence, including the indicators proposed here. Current intelligent machines, including deep learning neural networks (DLNNs) and agile robots, are not indicated to be conscious yet. Instead of assessing machine consciousness by a brief Turing-type of test, evidence for it may gradually accumulate when we study machines ethologically and across time, considering multiple behaviors that require flexibility, improvisation, spontaneous problem-solving and the situational conspectus typically associated with conscious experience.

Several studies have identified associations between poverty and development of self-regulation during childhood, which is broadly defined as those skills involved in cognitive, emotional, and stress self-regulation. These skills are influenced by different individual and contextual factors at multiple levels of analysis (i.e., individual, family, social, and cultural). Available evidence suggests that the influences of those biological, psychosocial, and sociocultural factors on emotional and cognitive development can vary according to the type, number, accumulation of risks, and co-occurrence of adverse circumstances that are related to poverty, the time in which these factors exert their influences, and the individual susceptibility to them. Complementary, during the past three decades, several experimental interventions that were aimed at optimizing development of self-regulation of children who live in poverty have been designed, implemented, and evaluated. Their results suggest that it is possible to optimize different aspects of cognitive performance and that it would be possible to transfer some aspects of these gains to other cognitive domains and academic achievement. We suggest that it is an important task for ethics, notably but not exclusively neuroethics, to engage in this interdisciplinary research domain to contribute analyses of key concepts, arguments, and interpretations. The specific evidence that neuroscience brings to the analyses of poverty and its implications needs to be spelled out in detail and clarified conceptually, notably in terms of causes of and attitudes toward poverty, implications of poverty for brain development, and for the possibilities to reduce and reverse these effects.

Recognizing that its research may raise various ethical, social, and philosophical issues, the HBP has made the identification, examination, and management of those issues a top priority. The Ethics and Society subproject is part of the core research project.