Hasil untuk "Philosophy of religion. Psychology of religion. Religion in relation to other subjects"

Huiyao Chen, Ruimeng Liu, Yan Luo et al.

The intersection of artificial intelligence and psychological science has experienced remarkable growth, with annual publications expanding from 859 papers in 2000 to 29,979 by 2025. However, this rapid evolution has created methodological fragmentation where similar computational techniques are independently developed across isolated psychological domains. This survey introduces the first systematic taxonomy that organizes AI-driven psychology tasks by computational processing patterns rather than application domains, categorizing them into four fundamental types: classification, regression, structured relational, and generative interactive tasks. Through analysis of over 300 representative works spanning the pre-trained model era and large language model era, we examine how computational approaches evolved from task-specific feature engineering to transfer learning and few-shot adaptation. We provide systematic coverage of datasets, evaluation metrics, and benchmarks while addressing fundamental challenges including interpretability, label uncertainty, privacy constraints, and cross-cultural validity. This computational perspective reveals transferable methodological patterns previously obscured by domain-centric organization, enabling systematic knowledge transfer and accelerated progress in computational psychology.

Endah Setyowati, Hendra Sigalingging

Abstrak Penelitian ini bertujuan untuk menganalisis peran Bias Konfirmasi dalam menentukan sikap dan perilaku intoleransi beragama menurut dosen universitas agama di Yogyakarta. Konsep Bias Konfirmasi merupakan salah satu pendekatan kontribusi Neuroscience yang dapat digunakan untuk memahami fenomena sosial seperti sikap dan perilaku intoleransi dalam konteks masyarakat dengan keberagaman agama. Melalui survei yang dilanjutkan dengan wawancara mendalam kepada informan, penelitian ini memberikan gambaran mengenai pandangan para informan dalam menciptakan sikap intoleransi beragama. Sikap penerimaan terhadap keberadaan agama yang berbeda menghilangkan bias konfirmasi terhadap berita konflik yang menggunakan identitas agama. Namun pada situasi tekanan kelompok, bias konfirmasi berkaitan dengan sesuatu yang tidak pernah ada dalam ingatan berpotensi menimbulkan sikap atau perilaku intoleran. Abstract This study aims to analyze the role of Confirmation Bias in determining the attitude and behavior of religious intolerance according to the lecturers of religiously affiliated universities in Yogyakarta. The concept of Confirmation Bias is one of the approaches contributed by Neuroscience that can be used to understand social phenomena such as intolerant attitudes and behavior in the context of societies with religious diversity. Through a survey followed by in-depth interviews, this research provides an overview of the informants’ views on creating attitudes of religious intolerance. An attitude of acceptance towards the existence of different religions eliminates confirmation bias towards conflict news that uses religious identities. However, in situations of group pressure, confirmation bias is related to something that has never been in memory which has the potential to give rise to intolerant attitudes or behavior.

Mehran Rezaee, Eisa Mohammadinia, Mahdi Emami Jome

Axioms are crucial to epistemic frameworks, as several schools of the history of science have recognized. The issue of the current research is that in the validation of axioms, what defects does the intuitive approach entail, and how can the intersubjective approach (based on the ideas of Islamic philosophers) be explained as an alternative, less-known system? The former is dedicated to clarifying and criticizing what is called the intuitive approach to validating axioms: this approach is attributed to classical philosophers and consists of assuming that axioms are propositions whose truth is immediately evident upon taking into account the terms they are based on. The latter focuses on clarifying the alternative approach, called the intersubjective approach of validating axioms (IAVA): this approach is attributed to a specific Islamic tradition, developed by Avicenna and Mullā Ṣadrā, and consists of assuming that axioms are propositions that cannot be rationally proved, denied, or doubted, without being already assumed. In this article, we present the intersubjective approach from a historical point of view.

Xiangrui Liu, Man Luo, Agneet Chatterjee et al.

Hallucination is a long-standing problem that has been actively investigated in Vision-Language Models (VLMs). Existing research commonly attributes hallucinations to technical limitations or sycophancy bias, where the latter means the models tend to generate incorrect answers to align with user expectations. However, these explanations primarily focus on technical or externally driven factors, and may have neglected the possibility that hallucination behaviours might mirror cognitive biases observed in human psychology. In this work, we introduce a psychological taxonomy, categorizing VLMs' cognitive biases that lead to hallucinations, including sycophancy, logical inconsistency, and a newly identified VLMs behaviour: appeal to authority. To systematically analyze these behaviours, we design AIpsych, a scalable benchmark that reveals psychological tendencies in model response patterns. Leveraging this benchmark, we investigate how variations in model architecture and parameter size influence model behaviour when responding to strategically manipulated questions. Our experiments reveal that as model size increases, VLMs exhibit stronger sycophantic tendencies but reduced authority bias, suggesting increasing competence but a potential erosion of response integrity. A human subject study further validates our hypotheses and highlights key behavioural differences between VLMs and human respondents. This work suggests a new perspective for understanding hallucination in VLMs and highlights the importance of integrating psychological principles into model evaluation.

Yohana Esti Tambunan

Arushi Jain, Shubham Paliwal, Monika Sharma et al.

Creative story illustration requires a consistent interplay of multiple characters or objects. However, conventional text-to-image models face significant challenges while producing images featuring multiple personalized subjects. For example, they distort the subject rendering, or the text descriptions fail to render coherent subject interactions. We present Multi-Subject Personalization (MSP) to alleviate some of these challenges. We implement MSP using Stable Diffusion and assess our approach against other text-to-image models, showcasing its consistent generation of good-quality images representing intended subjects and interactions.

Aditi Verma

This paper describes the underlying philosophy, design, and implementation of a course on "Nuclear Technology, Policy, and Society" taught in the Department of Nuclear Engineering and Radiological Sciences at the University of Michigan. The course explores some of nuclear technology's most pressing challenges or its 'wicked problems'. Through this course students explore the origins of these problems be they social or technical and, they are offered tools, both conceptual and methodological to make sense of these problems, and guided through a semester-long exploration of how scientists engineers can work towards their resolution, and to what degree these problems can be solved through institutional transformation or a transformation in our own practices and norms as a field. The underlying pedagogical philosophy, implementation, and response to the course are described here for other instructors who might wish to create a similar course, or for non-academic nuclear scientists and engineers, who might perhaps, in these pages, find a vocabulary for articulating and reflecting on the nature of these problems as encountered in their praxis.

Edoardo Sebastiano De Duro, Enrique Taietta, Riccardo Improta et al.

Machine psychology aims to reconstruct the mindset of Large Language Models (LLMs), i.e. how these artificial intelligences perceive and associate ideas. This work introduces PhDGPT, a prompting framework and synthetic dataset that encapsulates the machine psychology of PhD researchers and professors as perceived by OpenAI's GPT-3.5. The dataset consists of 756,000 datapoints, counting 300 iterations repeated across 15 academic events, 2 biological genders, 2 career levels and 42 unique item responses of the Depression, Anxiety, and Stress Scale (DASS-42). PhDGPT integrates these psychometric scores with their explanations in plain language. This synergy of scores and texts offers a dual, comprehensive perspective on the emotional well-being of simulated academics, e.g. male/female PhD students or professors. By combining network psychometrics and psycholinguistic dimensions, this study identifies several similarities and distinctions between human and LLM data. The psychometric networks of simulated male professors do not differ between physical and emotional anxiety subscales, unlike humans. Other LLMs' personification can reconstruct human DASS factors with a purity up to 80%. Furthemore, LLM-generated personifications across different scenarios are found to elicit explanations lower in concreteness and imageability in items coding for anxiety, in agreement with past studies about human psychology. Our findings indicate an advanced yet incomplete ability for LLMs to reproduce the complexity of human psychometric data, unveiling convenient advantages and limitations in using LLMs to replace human participants. PhDGPT also intriguingly capture the ability for LLMs to adapt and change language patterns according to prompted mental distress contextual features, opening new quantitative opportunities for assessing the machine psychology of these artificial intelligences.

Michael Pichat

What is the "nature" of the cognitive processes and contents of an artificial neural network? In other words, how does an artificial intelligence fundamentally "think," and in what form does its knowledge reside? The psychology of artificial intelligence, as predicted by Asimov (1950), aims to study this AI probing and explainability-sensitive matter. This study requires a neuronal level of cognitive granularity, so as not to be limited solely to the secondary macro-cognitive results (such as cognitive and cultural biases) of synthetic neural cognition. A prerequisite for examining the latter is to clarify some epistemological milestones regarding the cognitive status we can attribute to its phenomenology.

Şəms Ağazadə

Müasir psixologiya tarixinin formalaşmasında bir sıra cərəyan olub ki, bunlardan biri də humanistik psixologiyadır. Abraham Maslov və Rocers – bu iki şəxsiyyət birlikdə humanistik psixologiyanın banilərindən hesab olunurlar. Onların birgə əməyi sayəsində humanistik psixologiya sistemli vəziyyətə gəlmişdir. Rocers Mənlik nəzəriyyəsini şəxsiyyətin quruluşu­nun mühüm tərkib hissəsi hesab edirdi. Rocers üçün əsas olan “şəxsiyyət nəzəriyyəsi” mənlik və ya “mənlik” anlayışıdır. Bu, “özü haqqında mütəşəkkil, ardıcıl qavrayışlar və inanclar toplusu" kimi də müəyyən edi­lir. “Mən” – bir insan olaraq həqiqətdə kim olduğumuzu ifadə edən huma­nist termindir. Mənlik – daxili şəxsiyyətimizdir; onu ruha və ya Freydin psixikasına bənzətmək mümkündür. Mən – insanın həyatında keçirdiyi təcrübələrdən və bu praktikaların şərhlərindən təsirlənir. Mənlik anlayışı­mıza təsir edən iki əsas mənbə – uşaqlıq təcrübələri və başqaları tərəfindən qiymətləndirmədir. Rocersə görə, biz – öz imicimizə uyğun olan və necə olmaq istəyimiz, ideal mənliyimizi əks etdirən tərzi duymaq, təcrübə etmək və davranmaq arzumuzdur. Özümüz haqqında təsəvvürümüz və ideal mənliyimiz bir-birinə nə qədər yaxındırsa, bir o qədər ardıcılıq, uyğun gəlirik və özümüzə dəyərvermə duyğumuz da bir o qədər yüksəkdir. Rocersə görə, özümüz haqqında necə düşünməyimiz, özümüzə dəyərvermə duyğumuz – həm psixoloji sağlamlıq, həm də həyatda məqsəd və ambisiyalarımıza nail olmaq, özünüreallaşdırabilmə ehtimalımız üçün əsas əhəmiyyət kəsb edir. Özünədəyər çox yüksəkdən-çox aşağıyadək bir davamlılıq kimi görünə bilər. Karl Rocers üçün yüksək özünəinamlı, yəni özünəinamı və müsbət hissləri olan, həyatda çətinliklərlə üzləşən, uğursuzluqları və bədbəxtlikləri bəzən qəbul edən, insanlara açıq olan şəxsdir.

Anoop Kadan, Deepak P., Sahely Bhadra et al.

Groundbreaking inventions and highly significant performance improvements in deep learning based Natural Language Processing are witnessed through the development of transformer based large Pre-trained Language Models (PLMs). The wide availability of unlabeled data within human generated data deluge along with self-supervised learning strategy helps to accelerate the success of large PLMs in language generation, language understanding, etc. But at the same time, latent historical bias/unfairness in human minds towards a particular gender, race, etc., encoded unintentionally/intentionally into the corpora harms and questions the utility and efficacy of large PLMs in many real-world applications, particularly for the protected groups. In this paper, we present an extensive investigation towards understanding the existence of "Affective Bias" in large PLMs to unveil any biased association of emotions such as anger, fear, joy, etc., towards a particular gender, race or religion with respect to the downstream task of textual emotion detection. We conduct our exploration of affective bias from the very initial stage of corpus level affective bias analysis by searching for imbalanced distribution of affective words within a domain, in large scale corpora that are used to pre-train and fine-tune PLMs. Later, to quantify affective bias in model predictions, we perform an extensive set of class-based and intensity-based evaluations using various bias evaluation corpora. Our results show the existence of statistically significant affective bias in the PLM based emotion detection systems, indicating biased association of certain emotions towards a particular gender, race, and religion.

D.I. Ansusa Putra

Religious theological views alter continuously with the context and dynamics of social change. The emergence of digital media and the flow of information has caused a change in the theological views on religious truths and their validation ways. Therefore, this research aimed to explore the theological views and practices of converts in Indonesia who are committed to disseminating validated the Qur'an-Bible relationship in social media as a consequence of their Islamic beliefs. The influence of context and social dynamics on religious theological views was explored by obtaining data through media observations and in-depth interviews with three popular converts on social media, namely Ahmad Kainama, drg. Carissa Grani, and Teressia Pardede. Subsequently, this research concluded that converts to religious theology in Indonesia focus on three basic views, 1) Converts considered Islam as a universal religion and the faith of all prophets and apostles, as Jesus, Moses, and all the bearers of religion in the world are Muslims, 2) Convert judges a historical distortion about Islam and Christianity, 3) Convert claims there is a misinterpretation in understanding Islam and Christianity. This also provided an overview of the impacts that arise due to theological validation in social-religious life by Indonesian converts on social media. This information is expected to contribute to future research as a theoretical-empirical-phenomenological basis about converts and their theological views on social media for the development of relevant investigations.

Peng Ye, Shengji Tang, Baopu Li et al.

Residual networks have shown great success and become indispensable in today's deep models. In this work, we aim to re-investigate the training process of residual networks from a novel social psychology perspective of loafing, and further propose a new training strategy to strengthen the performance of residual networks. As residual networks can be viewed as ensembles of relatively shallow networks (i.e., \textit{unraveled view}) in prior works, we also start from such view and consider that the final performance of a residual network is co-determined by a group of sub-networks. Inspired by the social loafing problem of social psychology, we find that residual networks invariably suffer from similar problem, where sub-networks in a residual network are prone to exert less effort when working as part of the group compared to working alone. We define this previously overlooked problem as \textit{network loafing}. As social loafing will ultimately cause the low individual productivity and the reduced overall performance, network loafing will also hinder the performance of a given residual network and its sub-networks. Referring to the solutions of social psychology, we propose \textit{stimulative training}, which randomly samples a residual sub-network and calculates the KL-divergence loss between the sampled sub-network and the given residual network, to act as extra supervision for sub-networks and make the overall goal consistent. Comprehensive empirical results and theoretical analyses verify that stimulative training can well handle the loafing problem, and improve the performance of a residual network by improving the performance of its sub-networks. The code is available at https://github.com/Sunshine-Ye/NIPS22-ST .

Rohitash Chandra, Mukul Ranjan

A distinct feature of Hindu religious and philosophical text is that they come from a library of texts rather than single source. The Upanishads is known as one of the oldest philosophical texts in the world that forms the foundation of Hindu philosophy. The Bhagavad Gita is core text of Hindu philosophy and is known as a text that summarises the key philosophies of the Upanishads with major focus on the philosophy of karma. These texts have been translated into many languages and there exists studies about themes and topics that are prominent; however, there is not much study of topic modelling using language models which are powered by deep learning. In this paper, we use advanced language produces such as BERT to provide topic modelling of the key texts of the Upanishads and the Bhagavad Gita. We analyse the distinct and overlapping topics amongst the texts and visualise the link of selected texts of the Upanishads with Bhagavad Gita. Our results show a very high similarity between the topics of these two texts with the mean cosine similarity of 73%. We find that out of the fourteen topics extracted from the Bhagavad Gita, nine of them have a cosine similarity of more than 70% with the topics of the Upanishads. We also found that topics generated by the BERT-based models show very high coherence as compared to that of conventional models. Our best performing model gives a coherence score of 73% on the Bhagavad Gita and 69% on The Upanishads. The visualization of the low dimensional embeddings of these texts shows very clear overlapping among their topics adding another level of validation to our results.

Abdul Pirol, Aswan Aswan

This research discusses the politics of identity that are increasingly strengthening in the public sphere. This phenomenon grows through the religious sentiment circulated massively on social media and is also evident in dress and daily behavior. This article wants to see: (1) the extent to which the identity of female students that wearing niqab influences the national insight, (2) how their perspectives and attitudes in national and state life. As a result, the sentiment of niqab female students' identity grew more vital in the public sphere. It is directly proportional to their low acceptance of government leaders of different religions. The government role is also considered lacking in helping them to overcome the life problems they face. Interestingly, the position of the Pancasila in the group gaining acceptance is relatively high. The primary data of this study through a questionnaire with the techniques of purposive sampling of 30 female students that wearing the niqab from various religious organisations spread across many campuses in the City of Palopo.

Michael te Vrugt

Explaining the emergence of stochastic irreversible macroscopic dynamics from time-reversible deterministic microscopic dynamics is one of the key problems in philosophy of physics. The Mori-Zwanzig projection operator formalism, which is one of the most important methods of modern nonequilibrium statistical mechanics, allows for a systematic derivation of irreversible transport equations from reversible microdynamics and thus provides a useful framework for understanding this issue. However, discussions of the Mori-Zwanzig formalism in philosophy of physics tend to focus on simple variants rather than on the more sophisticated ones used in modern physical research. In this work, I will close this gap by studying the problems of probability and irreversibility using the example of Grabert's time-dependent projection operator formalism. This allows to give a more solid mathematical foundation to various concepts from the philosophical literature, in particular Wallace's simple dynamical conjecture and Robertson's theory of autonomous macrodynamics. Moreover, I will explain how the Mori-Zwanzig formalism allows to resolve the tension between epistemic and ontic approaches to probability in statistical mechanics. Finally, I argue that the debate which interventionists and coarse-grainers should really be having is related not to the question why there is equilibration at all, but why it has the quantitative form it is found to have in experiments.

Dorian Peters

While human beings have a right to digital experiences that support, rather than diminish, their psychological wellbeing, technology designers lack research-based practices for ensuring psychological needs are met. To help address this gap, we draw on findings from over 30 years of research in psychology (specifically, self-determination theory) that has identified contextual factors shown to support psychological wellbeing. We translate these findings into a list of 15 heuristics and 30 design strategies to provide technology makers with theoretically grounded, research-based, and actionable ways to support wellbeing in user experience.

Robert E. Carter

Religion in Japan is multi‐faceted and draws from two primary sources: Shintō and Buddhism. Japan's early indigenous cults together with Buddhist sources became Shintō, and while it eschews theory and intellectualization, it serves as a major stream of culture and its practices. Buddhism already flourishing in China before coming to Japan became the other major cultural influence.In addition to Shintō, the work of Nishida Kitarō, Tanabe Hajime of the Pure Land Buddhist tradition, Keiji Nishitani's Zen‐inspired religious philosophy, and the dramatic “spiritual atheism” of Hisamatsu Shin'ichi are considered in some detail. What emerges from all of these traditions is that they considered direct experience and not belief to be paramount. Religious experience and not theory or belief is the heart of religion in Japan.

Yi-Cai Zhang

In this work, a Josephson relation is generalized to a multi-component fermion superfluid. Superfluid density is expressed through a two-particle Green function for pairing channels. When the system has only one gapless collective excitation mode, the Josephson relation is simplified, which is given in terms of the order parameters and the trace of two-particle Green functions. In the presence of inversion symmetry, the superfluid density is directly related to the inverse of pairing fluctuation matrix. The results of the superfluid density in Haldane model show that the generalized Josephson relation can be also applied into a multi-band fermion superfluid in lattice.

Tadeusz Gacia

Tłumaczenie poezji Alkuina z Yorku