Search Results (60)

This paper applies quantum game theory to three ethical dilemmas that frequently arise in negotiation: cooperation versus competition, self-interest versus equity, and honesty versus deception. Using quantum extensions of selected games such as the Prisoner’s Dilemma, the Ultimatum Game, the Battle of the Sexes, and the Buyer–Seller Game, we examine whether quantization can generate equilibria that improve classical outcomes while also aligning more closely with ethical principles such as fairness, cooperation, and honesty. The analysis shows that quantum strategies, through entanglement and superposition, can sustain cooperative, fair, or honest behaviour as stable equilibria, outcomes that are typically unstable or unattainable in classical settings. The specific outcomes depend on the chosen quantization method, but across cases, the analysis consistently shows that quantum formulations expand the range of solutions in which efficiency and ethical principles co-exist. Full article

In this article, I argue that the climate crisis is a symptom of dissonant eco-subjects and relations that are, in part, produced by Abrahamic religious/spiritual traditions—traditions that function as apparatuses of the ontological rift between human and other-than-human animals. The argument begins by addressing the relation between Abrahamic traditions and apparatuses of the ontological rift. This sets the stage for explicating what is meant by spiritualities of eco-dissonant subjects. To further understand the features of eco-dissonant spiritualities, I turn to the philosophical notion of self-deception and the psychoanalytic notion of weak dissociation, which help explain our resistance to becoming aware of our contributions to the sufferings of other species and the wounding of the Earth, as well as our resistance to change. Full article

The paper renegotiates two regnant and interconnected modern assumptions, a reduction of forgetting to memory loss, and insistence on a self-remembering individual as the social atom, from which one builds molar and molecular social structures. In the article, a critical conceptual retrieval of the notion of bicorp extends beyond the doctrinal frameworks of rabbinic and patristic traditions to afford a heuristic scope in which to access the significance and limitations of a modern individual as an atom of the society. The main result is a detection of the central rather than marginal role of bicorp in creating legally imputable and responsible individuals in society. This result is accompanied by a connected detection of the long-term reversal, in which memory, including the memory the individual has of oneself, becomes primary and forgetting plays a deceptively secondary role of a memory loss in society. Full article

Deepfake audio refers to the generation of voice recordings using deep neural networks that replicate a specific individual’s voice, often for deceptive or fraud purposes. Although this has been an area of research for quite some time, deepfakes still pose substantial challenges for reliable true speaker authentication. To address the issue, we propose AudioFakeNet, a hybrid deep learning architecture that use Convolutional Neural Networks (CNNs) along with Long Short-Term Memory (LSTM) units, and Multi-Head Attention (MHA) mechanisms for robust deepfake detection. CNN extracts spatial and spectral features, LSTM captures temporal dependencies, and MHA enhances to focus on informative audio segments. The model is trained using Mel-Frequency Cepstral Coefficients (MFCCs) from the publicly available dataset and was validated on self-collected dataset, ensuring reproducibility. Performance comparisons with state-of-the-art machine learning and deep learning models show that our proposed AudioFakeNet achieves higher accuracy, better generalization, and lower Equal Error Rate (EER). Its modular design allows for broader adaptability in fake-audio detection tasks, offering significant potential across diverse speech synthesis applications. Full article

This paper presents HE-DMDeception, a novel adversarial attack network that integrates human visual deception with deep model deception to enhance the security of 3D object detection. Existing patch-based and camouflage methods can mislead deep learning models but struggle to generate visually imperceptible, high-quality textures. Our framework employs a CycleGAN-based camouflage network to generate highly camouflaged background textures, while a dedicated deception module disrupts non-maximum suppression (NMS) and attention mechanisms through optimized constraints that balance attack efficacy and visual fidelity. To overcome the scarcity of annotated vehicle data, an image segmentation module based on the pre-trained Segment Anything (SAM) model is introduced, leveraging a two-stage training strategy combining semi-supervised self-training and supervised fine-tuning. Experimental results show that the minimum P@0.5 values (50%, 55%, 20%, 25%, 25%) were achieved by HE-DMDeception across You Only Look Once version 8 (YOLOv8), Real-Time Detection Transformer (RT-DETR), Fast Region-based Convolutional Neural Network (Faster-RCNN), Single Shot MultiBox Detector (SSD), and MaskRegion-based Convolutional Neural Network (Mask RCNN) detection models, while maintaining high visual consistency with the original camouflage. These findings demonstrate the robustness and practicality of HE-DMDeception, offering new insights into 3D object detection adversarial attacks. Full article

As artificial intelligence transitions from conversational agents to autonomous actors in high-stakes environments, a critical gap emerges: how to ensure AI prioritizes human safety when its core objectives conflict with human well-being. Current safety benchmarks focus on harmful content, not behavioral alignment during instrumental goal conflicts. To address this, we introduce PacifAIst, a benchmark of 700 scenarios testing self-preservation, resource acquisition, and deception. We evaluated eight state-of-the-art large language models, revealing a significant performance hierarchy. Google’s Gemini 2.5 Flash demonstrated the strongest human-centric alignment (90.31%), while the highly anticipated GPT-5 scored lowest (79.49%), indicating potential risks. These findings establish an urgent need to shift the focus of AI safety evaluation from what models say to what they would do, ensuring that autonomous systems are not just helpful in theory but are provably safe in practice. Full article

In the era of the “super-individual”, companion robots (or sex robots), as novel agents for intimate relationships, have provoked profound ethical controversies. This article responds to Fang Xudong’s defense of companion robots in terms of the “instrumentalization of womanhood” and further explores the possible stance of Confucian ethics towards companion robots. Companion robots risk fostering emotional self-deception, which violates the Confucian self-cultivation requirement of “sincerity within, manifesting outwardly” 诚于中，形于外. They also fail to fulfill the “generative virtue” 生生之德 encompassing biological reproduction and moral education through kinship and may even undermine the family’s function as a carrier of ethical practice. From a Confucian perspective, the “pseudo-intimacy” facilitated by companion robots might alleviate symptoms of social isolation in an atomized age, but it cannot replace the familial warmth characterized by “affection between father and son, distinct roles between husband and wife” 父子有亲，夫妇有别. Only in the ethical practice of facing the other and taking responsibility can one truly realize the ideal of “cultivating oneself and bringing all things to their ideal state” 成己成物. Full article

In informal economic contexts, migrant entrepreneurs have been extolled as highly resilient and adaptable. This study critically investigates the adverse psychological foundations inherent in such enterprises, focusing on how dark triad personality traits emerge in the leadership orientations of marginal migrant entrepreneurs. Following a qualitative ethnographic approach, this research engaged 10–15 migrant employees through participant observation, field notes, and semi-structured interviews in an informal economic context. Thematic analysis revealed five dominant patterns: narcissistic leadership with entitlement and emotional disrespect; Machiavellian behavior of manipulation and deception; psychopathic detachment in emotional callousness; absence of light triad actions such as empathy, humility, and selflessness; and moral disengagement through rationalizations such as “everyone does it” or system blame. Migrant business owners prefer to rationalize their exploitative acts as being necessary for economic survival, thus legitimizing immoral conduct and suppressing moral self-regulation. The findings indicate that marginality not only drives entrepreneurial innovation, but also has the potential to create exploitative inclinations that are institutionally and morally unchecked. Solving this issue requires not only mere psychological awareness, but also systematic reforms that foster ethical robustness and emotional sensitivity. This study ultimately asserts the need to reframe migrant entrepreneurship discourse, including both ethical and psychological accountability. Full article

The rapid expansion of digital communication platforms has created new spaces for antisocial, manipulative, and emotionally detached behaviors. While psychopathy has been extensively studied in clinical and forensic settings, its digital manifestation, referred to as cyberpsychopathy, remains conceptually underdefined. This integrative review aimed to synthesize empirical research exploring psychopathy and aversive personality traits in online contexts to identify key conceptual domains and propose a preliminary definition. A systematic search across five databases yielded 35 peer-reviewed studies meeting the inclusion criteria. Using a biopsychosocial framework and thematic synthesis, six interrelated domains were identified: online behaviors (e.g., trolling and deception), online environments (e.g., anonymity and reward mechanisms), sociodemographic factors (e.g., age and gender), personality traits (e.g., psychopathy and narcissism), psychological factors (e.g., emotion dysregulation and low self-esteem), and motivations (e.g., dominance and emotional compensation). These domains interact to shape how psychopathic tendencies manifest online. Most studies were of moderate-to-high methodological quality, though variability limited direct comparisons. We propose cyberpsychopathy as a multidimensional construct representing the expression of aversive traits facilitated by digital affordances and psychological vulnerabilities. This review provides a foundational framework for understanding cyberpsychopathy and underscores the need for empirical validation and the development of assessment tools suited to digital behavior in both clinical and forensic settings. Full article

Bystander intervention and sexual assault research typically rely on self-reported intent to intervene. However, predicted behaviour can be considerably different from actual behaviour. Hypothetical scenarios are often utilised to remove extenuating circumstances, limiting insight into actual behaviour where those circumstances impact intervention. This paper discusses the development and evaluation of an innovative methodology to measure actual bystander behaviour when witnessing signs of an impending sexual assault. With careful attention paid to ethical considerations and participant safety, 13 participants were directly deceived about the true aim of the research. Utilising observational data and a funnelling debrief, the findings demonstrated varied reactions to sexual assault cues, from not noticing and therefore not intervening, to noticing and (in)directly intervening. Participants’ responses indicated they remained unaware of the deception until it was formally revealed, suggesting the methodology effectively realised the study’s aims. The funnelling debrief mitigated the adverse effects of the deception, with some participants reporting more confidence and motivation to intervene in the future. Further development of this methodology could create more interactive bystander intervention programmes that teach people to identify signs of a sexual assault, develop skills to safely intervene, and raise awareness about sexual violence. Full article

Background/Objectives: Cognitive and psychological factors, such as eating disorder psychopathology, irrational food beliefs, and internalized weight stigma, have not been sufficiently explored in the context of obesity treatment. This study evaluated the role of these variables as predictors of weight loss in patients with severe obesity following a brief intensive cognitive–behavioral therapy for obesity (CBT-OB) program. Methods: A total of 400 patients (mean BMI: 41.9 kg/m²; mean age: 55.9 years) participated in a 21-day residential CBT-OB intervention, followed by a 12-month follow-up assessment. The Eating Disorder Examination Questionnaire, Weight Bias Internalization Scale, and Irrational Food Beliefs Scale were administered at admission and discharge. Body weight was also assessed at the 12-month follow-up. Results: Of the participants, 371 patients (92.2%) completed the intensive CBT-OB program, and 310 (81.1%) attended the follow-up. On average, completers achieved 9% weight loss at follow-up, accompanied by a significant reduction in binge-eating episodes. Cognitive factors, including lower baseline eating concern, higher baseline weight concern, and greater improvement in irrational beliefs (specifically self-deception about eating and weight control), significantly predicted weight loss at 12 months. However, internalized weight stigma did not predict weight loss in this cohort. Conclusions: This study underscores the importance of targeting specific cognitive factors in obesity treatment to enhance long-term outcomes. Addressing irrational food beliefs and promoting flexible dietary restraint may improve weight loss and maintenance in individuals with severe obesity. Further research is warranted to refine cognitive–behavioral interventions for personalized obesity management strategies. Full article

Background: The patterns of inbreeding coefficients (F_IS) and fine spatial genetic structure (FSGS) were evaluated regarding the mating system and inbreeding depression of food-deceptive orchids, Dactylorhiza majalis, Dactylorhiza incarnata var. incarnata, and Dactylorhiza fuchsii, from NE Poland. Methods: We used 455 individuals, representing nine populations of three taxa and AFLPs, to estimate percent polymorphic loci and Nei’s gene diversity, which are calculated using the Bayesian method; F_IS; F_ST; FSGS with the pairwise kinship coefficient (Fij); and AMOVA in populations. Results: We detected a relatively high proportion of polymorphic fragments (40.4–68.4%) and Nei’s gene diversity indices (0.140–0.234). The overall F_IS was relatively low to moderate (0.071–0.312). The average Fij for the populations of three Dactylorhiza showed significantly positive values, which were observed between plants at distances of 1–10 m (20 m). F_ST was significant in each Dactylorhiza taxon, ranging from the lowest values in D. fuchsii and D. majalis (0.080–0.086, p < 0.05) to a higher value (0.163, p < 0.05) in D. incarnata var. incarnata. Molecular variance was the highest within populations (76.5–86.6%; p < 0.001). Conclusions: We observed concordant genetic diversity patterns in three food-deceptive, allogamous, pollinator-dependent, and self-compatible Dactylorhiza. F_IS is often substantially higher than Fij with respect to the first class of FSGSs, suggesting that selfing (meaning of geitonogamy) is at least responsible for homozygosity. A strong FSGS may have evolutionary consequences in Dactylorhiza, and combined with low inbreeding depression, it may impact the establishment of inbred lines of D. majalis and D. incarnata var. incarnata. Full article

In the interpretations of Zhuangzi, there are four levels to the relationship between dreaming and awakening: awakening is more realistic than dreaming, dreaming is more realistic than awakening, dreaming and awakening are equal, and there is no distinction between dreaming and awakening. From the view of the Chongxuan (重玄) School, 1. insisting that awakening is more realistic and cherishing life is attached to substantiality as a psychological intention to seek out a specific object; 2. insisting that dreaming is more realistic is attached to nihility as a cynical intention of desirelessness; 3. non-attachment to the distinction between dreaming and awakening as a false objectification of the mid-way (madhyamā-pratipad) is a first-order non-attachment and a new kind of self-deception to form a hidden meta-desire to transcend the two kinds of desires above; and 4. Chongxuan, as a second-order non-attachment of non-attachment, allows people to forget the distinction between dreaming and awakening. This topic has also been reflected upon or reinterpreted by ancient and modern philosophers and has a continuous impact on social reform in modern China. Full article

This paper offers a critical analysis of the 2023 sustainability reports of five major ICT corporations: Amazon, Apple, Google, Meta, and Microsoft. It scrutinises how these organisations use sustainability data, particularly within the context of their actions, their planned initiatives, and visions for the future to report on three overarching sustainability narratives: 1. Reducing the climate footprint of their own operations; 2. Influencing and reducing the climate footprint of their supply chain and consumers; and 3. Financing innovation for climate change. Despite all five corporations expressing a commitment to sustainability and confronting climate change, their specific actions and planned initiatives differ, influenced by their core businesses and existing sustainability practices. This becomes more apparent in their choice to use their own intricate measuring infrastructures for self-tracking and self-reporting environmental data. Such infrastructures, although purportedly aimed at showcasing progress towards sustainability goals, face scrutiny due to their lack of transparency and the potential for manipulation and greenwashing, especially given the lack of standardised reporting protocols within the sector. This analysis highlights that, despite these companies’ claims of commitment to carbon neutrality, their climate pledges and sustainability goals are rarely achieved. In this framework, this paper suggests that a critical approach is essential when evaluating Big Tech’s often deceptive sustainability narratives and underscores the need for more rigorous regulatory frameworks and independent third-party audits to ensure genuine progress towards a sustainable future and true accountability. Full article

Particle swarm optimisation (PSO) is a swarm intelligence algorithm that finds candidate solutions by iteratively updating the positions of particles in a swarm. The decentralised optimisation methodology of PSO is ideally suited to problems with multiple local minima and deceptive fitness landscapes, where traditional gradient-based algorithms fail. PSO performance depends on the use of a suitable control parameter (CP) configuration, which governs the trade-off between exploration and exploitation in the swarm. CPs that ensure good performance are problem-dependent. Unfortunately, CPs tuning is computationally expensive and inefficient. Self-adaptive particle swarm optimisation (SAPSO) algorithms aim to adaptively adjust CPs during the optimisation process to improve performance, ideally while reducing the number of performance-sensitive parameters. This paper proposes a reinforcement learning (RL) approach to SAPSO by utilising a velocity-clamped soft actor-critic (SAC) that autonomously adapts the PSO CPs. The proposed SAC-SAPSO obtains a 50% to 80% improvement in solution quality compared to various baselines, has either one or zero runtime parameters, is time-invariant, and does not result in divergent particles. Full article