Next Article in Journal
The Burden of Being a Muslim Woman in India—The Instrumentalisation of Muslim Women at the Intersection of Gender, Religion, Colonialism, and Secularism
Next Article in Special Issue
The World Is the Road to God: The Encyclical Laudato Si’ and the “Ecological” Vision of Pope Francis
Previous Article in Journal
Reshaping Abraham’s Image in Early Qing China: A Comparative Study of Catholic and Jewish Interpretations
Previous Article in Special Issue
The Nexus of Digital Authoritarianism and Religious Populism
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

The Role of Artificial Intelligence in the Study of the Psychology of Religion

by
Khader I. Alkhouri
Department of Social Theology & the Study of Religion, National and Kapodistrian University of Athens, 10509 Athens, Greece
Religions 2024, 15(3), 290; https://doi.org/10.3390/rel15030290
Submission received: 15 January 2024 / Revised: 21 February 2024 / Accepted: 22 February 2024 / Published: 26 February 2024
(This article belongs to the Special Issue Religion, Society, Politics and Digital Technologies)

Abstract

:
The study of the psychology of religion encompasses various aspects of human experiences and beliefs, including the influence of emerging technologies such as artificial intelligence (AI). This article aims to examine the impact of AI on religious practices and rituals, highlighting its potential to reshape how individuals engage with spirituality. By exploring AI-powered religious applications, virtual communities, and online services, we seek to understand the transformation of traditional religious practices and raise important questions about authenticity, inclusiveness, and the role of technology in the psychology of religious contexts. Moreover, ethical considerations and challenges arising from the integration of AI into religion will be addressed. As researchers delve into this intersection, it is crucial to strike a balance between technological advancements and preserving the fundamental aspects of spirituality, personal growth, and genuine human connection. This article contributes to the existing literature by shedding light on the potential implications of AI in the realm of religious experiences, calling for further exploration of its ethical dimensions and unintended consequences. Ultimately, understanding the influence of AI on the psychology of religion prompts us to reflect on the nature of spirituality, belief formation, and the human experience itself.

1. Introduction

The study of the psychology of religion encompasses various aspects of human experiences and beliefs, including the influence of emerging technologies such as artificial intelligence (AI). These technologies have the potential to reshape how individuals engage with religious and spiritual practices.
Artificial intelligence, with its ability to process vast amounts of data and simulate human-like interactions, presents intriguing possibilities within the realm of religious experiences. It can assist individuals in finding personalized spiritual guidance, provide virtual companionship, or even simulate encounters with divine figures. However, questions arise about the authenticity and ethical implications of AI-driven religious experiences. This excerpt suggests that artificial intelligence (AI) does not inherently inquire about the fundamental essence of spirituality, belief formation, and the human experience. Instead, AI prompts discussions on how it might influence or impact these aspects. While spirituality, belief formation, and the human experience are distinct from one another, they are interconnected with, yet separate from, religion and religious experiences. It challenges us to consider how these technologies can enhance or potentially detract from the depth, authenticity, and transformative power of religious practices. As researchers delve into the influences of AI on the psychology of religion, they must explore the ethical considerations, potential biases, and unintended consequences that may arise. It is crucial to strike a balance between technological advancements and preserving the fundamental aspects of spirituality, personal growth, and genuine human connection.

1.1. Background and Rationale for Studying the Intersection of the Psychology of Religion and Artificial Intelligence

The psychology of religion can now be explored in new ways thanks to these technological advances. A systematic and comprehensive understanding of religious scriptures can be achieved using this computational approach, which sheds light on their cognitive, emotional, and social implications (Citlak 2021).
The study of the intersection of psychology of religion and artificial intelligence (AI) offers a unique opportunity to integrate two distinct fields of study. The psychology of religion explores the cognitive, emotional, and behavioral aspects of religious beliefs, practices, and experiences. On the other hand, AI involves the development of machines or computer systems that can simulate human intelligence and perform tasks that typically require human intelligence (Reed 2021). There are several reasons to explore the intersection of these fields:
1-Understanding religious experiences: Exploring the psychological dimensions of religious experiences with AI can help in understanding the intricate relationship between human cognition, emotions, and religious practices (Vestrucci et al. 2021). By studying AI’s ability to simulate religious experiences, we can gain insights into how individuals perceive and interpret religious phenomena (Umbrello 2023). 2-Simulating religious guidance and counseling: Many individuals seek religious guidance and counseling for various personal and existential issues (Badran and Hejazi 2023). Developing AI systems that can simulate religious leaders or counselors may offer an alternative avenue for individuals who seek such support (Quaquebeke and Gerpott 2023). By studying the intersection of psychology of religion and AI, we can investigate how AI can provide personalized guidance while respecting various religious traditions (Elmahjub 2023). 3-Ethical considerations: As AI becomes more advanced, ethical considerations arise. In the context of religion, ethical dilemmas could emerge in creating AI systems that simulate religious figures or influence individuals’ religious beliefs (Ashraf 2022). Studying the intersection of psychology of religion and AI can help in identifying and addressing potential ethical concerns, ensuring responsible development and utilization of AI technology in religious contexts (Umbrello 2023). 4-Exploring the impact of AI on religious beliefs: AI-driven technologies are increasingly shaping various aspects of human life, including religious practices (Andriansyah 2023). Understanding the impact of AI on individuals’ religious beliefs and practices can help in predicting and responding to potential societal changes (Jungherr 2023). This intersection can provide insights into how AI technology influences religious communities and individuals’ relationships with their faith (Dawson 2023).

1.2. The Article’s Objective and Scope, along with Its Influence on Existing Literature

Examining the impact of artificial intelligence on religious practices and rituals (Ashraf 2022). By examining AI-powered religious applications, virtual communities, and online services, this article explores the transformation of traditional religious practices and raises important questions about authenticity, inclusiveness, and the role of technology in psychology of religious contexts (Orlandi et al. 2022). Addressing ethical considerations and challenges arising from the integration of AI into religion (Elmahjub 2023).

2. The Cognitive Foundations of Religious Belief

2.1. Cognitive Theories and Models Explaining the Development and Maintenance of Religious Beliefs

The study of cognitive theories and models is necessary to investigate the cognitive processes underlying the development and maintenance of religious beliefs (Xygalatas 2014). This section examines prominent cognitive theories and models that shed light on the intricate mechanisms involved in the formation, reinforcement, and persistence of religious belief systems (Hermans 2015). Examining these theories and models can give us deep insights into the cognitive mechanisms that contribute to the development and persistence of religious beliefs.
  • Two different cognitive systems are thought to be involved in belief formation: the intuitive system and the analytical system, according to dual-process theory (Seitz and Angel 2020). Heuristics, emotions, and automatic associations are used by the intuitive system to operate both automatically and unconsciously (Korteling et al. 2018). The analytical system, on the other hand, is deliberate, reflective, and logical (Krishna and Strack 2017). In the context of religious belief, this theory suggests that intuitive processes, such as intuitive thinking, pattern recognition, and emotional experiences, play a pivotal role in the perception of supernatural power and meaning in the world (Leeuwen and Elk 2019).
  • Cognitive-experiential theory emphasizes the role of cognitive processes and personal experiences in the formation of religious beliefs (Epstein 1985). This theory suggests that religious beliefs are not only based on rational and logical thinking but are also strongly influenced by subjective experiences and emotions (Bankston 2002). It argues that religious experiences characterized by awe, transcendence and mystical encounters contribute significantly to the formation of religious beliefs by providing individuals with a sense of meaning, connection and spiritual significance (Evans 2003).
  • Schema theory assumes that people have cognitive structures or mental frameworks, known as schemas, which help to organize and interpret information. Schemas are cognitive frameworks that guide an individual’s interpretation of the world, events, and experiences related to religious belief (Flannery and Walles 2003). Individuals’ expectations, perceptions, and memories of religious information are shaped by these schemas, which reinforce and maintain their religious beliefs over time (Leo et al. 2021). Schemas influence how individuals process and interpret religious texts, rituals, and symbols, and provide a cognitive framework for religious belief systems (Miltiadis et al. 2017).
  • Attribution theory focuses on the cognitive processes that play a role in the causal attribution of events and experiences. Religious belief assumes that individuals attribute supernatural causes to events that they perceive as meaningful, significant, or beyond their control (Spilka et al. 1985). The formation and maintenance of religious beliefs is highly dependent on the attribution of a supernatural cause (Leeuwen and Elk 2019). In addition, attribution theory examines how individuals attribute their own religious experiences to either internal factors, such as personal faith, or external factors, such as divine intervention, thereby influencing their belief in a higher power (DeBono et al. 2020).
  • Cognitive developmental approaches, based on Jean Piaget’s theory of cognitive development, assume that religious beliefs develop as cognitive abilities and understanding of the world’s progress (Rochat 2023). According to these approaches, children’s religious beliefs often exhibit concrete, literal thinking that gradually transitions into more abstract and complex understandings as cognitive maturity increases (Kéri 2023). These approaches emphasize the importance of cognitive development and socialization processes in the formation of an individual’s religious beliefs and the gradual incorporation of religious concepts into the cognitive framework (Long and Hadden 1983).

2.2. Examination of Cognitive Biases, Heuristics, and Social Cognition in Shaping Religious Belief Systems

The formation and interpretation of religious beliefs can be influenced by cognitive biases inherent in human thought (Willard and Norenzayan 2013). Confirmation bias can lead people to seek and interpret information that confirms their pre-existing beliefs, which could potentially reinforce religious beliefs (Peters 2022). People may place greater importance on religious experiences or anecdotes that are readily available due to availability biases, which may influence their religious beliefs. Understanding these biases helps to understand the cognitive mechanisms underlying the development and maintenance of religious beliefs (Willard and Norenzayan 2013).
Mental shortcuts that allow individuals to make quick decisions and judgements are referred to as heuristics. Heuristics can have a significant impact on belief formation in religion (Raue and Scholl 2018). For example, the representativeness heuristic can lead individuals to judge the truthfulness of religious claims based on how well they fit their preconceived notions or stereotypes (Bodenhausen 1990). Individuals’ judgements of the plausibility or credibility of religious concepts based on initial anchor points may be influenced by the anchoring and fitting heuristics (Epley and Gilovich 2006). By exploring these heuristics, one can gain valuable insight into the cognitive processes that shape religious beliefs (Carone and Barone 2001).
Social cognition refers to how individuals perceive, interpret, and interact with others (Frith 2008). Through social learning, social influence, and social identity, social cognition influences the adoption and maintenance of religious beliefs in the religion (Ozorak 1989). Religious beliefs are often acquired by individuals through socialization processes in which they learn from and imitate religious authorities, family members, and peer groups (Taggart et al. 2018). Social influences such as conformity and persuasion can affect religious beliefs by aligning individuals with prevailing religious norms or leading them to accept certain religious teachings (Thiruchselvam et al. 2017). Social identity processes help to maintain religious beliefs by fostering a sense of belonging and group cohesion within religious communities (Ysseldyk et al. 2010).
The psychology of religion can be enriched as AI technologies advance and become more integrated into religious contexts. While we cannot definitively state that it will be enriched, there is a likelihood that it may happen based on current trends and developments. intelligence (Ashraf 2022). AI technologies such as chatbots and virtual religious experiences can influence religious beliefs by interacting with individuals’ cognitive biases, heuristics, and social cognition (Lukyanenko et al. 2022). AI chatbots programmed to provide religious advice or spiritual experiences can confirm an individual’s existing beliefs (Ashraf 2022). AI-generated content based on popular religious narratives or teachings can exploit availability biases and influence individuals’ perceptions of religious truth. In addition, AI technologies can help facilitate social interaction and create virtual religious communities, which could impact social cognition processes in the formation and maintenance of religious beliefs (Puzio 2023).

2.3. The Role of Religious Experiences and Their Psychological Underpinnings in Religious Belief Formation

Religious experiences and their psychological underpinnings play a crucial role in the formation of religious beliefs (Zhong et al. 2017). Religious experiences are a collection of subjective encounters that people perceive as transcendent or divine. The formation, development, and consolidation of religious beliefs is strongly influenced by these experiences (Dein 2020). By examining the psychological aspects of religious experiences, we can better understand how these experiences contribute to the construction of religious belief systems (Głaz 2021).
  • Meaning making and existential significance: Religious experiences provide individuals with a sense of meaning and existential significance (Krokcorresponding 2015). Individuals have a framework to interpret the world and find meaning in their lives through it (Schippers 2019). These experiences form the basis of religious belief by providing answers to existential questions and evoking a sense of connection to a higher power or divine presence (Głaz 2021).
  • Emotions and affective responses play a crucial role in religious experiences. Intense emotions such as awe, joy, reverence and transcendence are often evoked during these encounters (Van 2017). The emotional impact of religious experiences can lead to increased meaning and memory, which can influence the formation and strength of religious beliefs (Watts 2004). Existing beliefs can be strengthened by positive emotional experiences, while negative emotional experiences can cause individuals to question or re-evaluate their beliefs (Rovenpor and Isbell 2018).
  • The interpretation and meaning attributed to religious experiences are highly influenced by cognitive processes. Individuals’ cognitive frameworks, beliefs, and cultural contexts influence their way of attending to, perceiving, remembering, and reflecting on these encounters (Henderson et al. 2022). Religious experiences are interpreted through cognitive processes and integrated into individual belief systems (Mulukom and Lang 2021).
  • Social influence and validation: Social factors exert a significant influence on the interpretation and meaning of religious experiences (Krause 2007). Individuals can share and validate their religious encounters in religious communities and social networks (Brubaker and Haigh 2017). Religious beliefs can be solidified and maintained through social validation and reinforcement by religious peers and authorities, which strengthens belief in the authenticity and meaning of these experiences (Lewandowsky et al. 2012).
  • Advances in neuroscience have shed light on the neurobiological correlates of religious experiences (Kime and Snarey 2018). Neuroimaging studies have shown that these encounters activate specific brain regions involved in reward processing, emotion regulation, and self-referential processing (Guendelman et al. 2017). According to these findings, neurobiological mechanisms are responsible for the subjective aspects of religious experiences that contribute to the formation and maintenance of religious beliefs (Grafman et al. 2020).

3. Computational Approaches to Understanding Religious Beliefs

3.1. Application of Computational Models and Artificial Intelligence Techniques to Study Religious Beliefs and Practices

The use of computational models and artificial intelligence (AI) techniques has become a promising method for investigating religious beliefs and practices (Reed 2021). Through the use of computational methods, researchers can gain valuable insights into various aspects of religion, such as belief formation, social dynamics, and religious experiences (Campbell 2012, Understanding the Relationship between Religion Online and Offline in a Networked Society). The computational models and AI techniques in the study of religious beliefs and practices (Lane and Shults 2021).
  • Modelling belief formation: Computational models provide a quantitative means of simulating and exploring the cognitive processes that underlie belief formation in religious contexts (Nielbo et al. 2012). These models can simulate the acquisition, interpretation, and revision of religious beliefs by integrating principles from cognitive science, psychology, and AI (Vestrucci et al. 2021). Cognitive biases, social influences, and belief revision algorithms will be integrated into computer models to provide a systematic framework for understanding the complex dynamics of religious belief formation (Dixon et al. 2013).
  • Analysis of Textual Data AI techniques such as natural language processing (NLP) and machine learning enable researchers to analyze large-scale textual data related to religious texts, sermons, religious literature and online discussions (Mah et al. 2022). By applying these techniques, researchers can uncover patterns, themes, and semantic relationships within religious texts, allowing for a deeper understanding of the conceptual frameworks and theological foundations of religious beliefs and practices (Kapogiannis et al. 2009). The historical, cultural, and sociological dimensions of religious traditions can be illuminated through this analysis (Lizardo 2023).
  • The development of predictive models that forecast religious behaviors, trends, and societal impacts is possible through the integration of computational models and AI techniques (Dwivedi et al. 2023a). Historical data, demographic factors, and cultural variables can be used by researchers to predict models that predict religious affiliation, adherence, and changes in religious practices over time (Leite et al. 2023). A comprehensive understanding of the dynamics of religious belief systems and their implications for society can be achieved using these predictive models (Sosis 2020).
  • Virtual reality (VR) and immersive technologies provide researchers with controlled environments to study religious experiences (Zhao et al. 2023). The psychological, emotional, and cognitive effects of these experiences on individuals can be investigated through the creation of virtual religious spaces or simulating religious rituals. The exploration of the impact of religious imagery, symbols, and rituals on belief formation and religious practices is made possible by virtual environments, which provide unique insights into the phenomenology of religious encounters (Hobson et al. 2018).
  • Social network analysis, particularly computational techniques, offers a valuable tool for examining social dynamics within religious communities (Park et al. 2019). Researchers can examine the influence of information flows, social influence, and community structures on religious beliefs and practices by analyzing online interactions, social media data, and offline networks (Campbell 2012, Understanding the Relationship between Religion Online and Offline in a Networked Society). A deeper understanding of the mechanisms of religious diffusion, the formation of religious communities, and the dissemination of religious ideas within society is facilitated by these insights (Koehrsen 2021).

3.2. Integration of Cognitive Models and Computational Simulations to Understand the Psychological Mechanisms Underlying Religious Belief

Exploring the complex psychological mechanisms that underlie religious belief has become possible through the integration of cognitive models and computational simulations, which is a sophisticated and rigorous approach (L. F. Shults 2019). By combining insights from cognitive science, psychology, and computational modeling, this interdisciplinary approach offers a systematic framework for understanding the intricate cognitive processes involved in the formation, maintenance, and expression of religious beliefs (McClelland 2009). The application of cognitive models and computational simulations to unravel the psychological mechanisms behind religious belief.
  • Cognitive Modeling of Religious Belief Cognitive models are theoretical frameworks that provide insights into how individuals acquire, process, and represent religious beliefs (Tolly 2023). These models provide a comprehensive understanding of the cognitive processes that lead to belief formation, such as perception, memory, attention, reasoning, and decision-making (Connors and Halligan 2022). Sophisticated models that capture the dynamics of religious belief systems can be developed by researchers by integrating cognitive theories with computational simulations, which enables simulations of belief development and evolution over time (Galesic et al. 2021).
  • Belief formation and change processes within religious contexts can be investigated using computational simulations, which are a valuable tool (Seitz and Angel 2020). These simulations incorporate cognitive biases, social influences, and belief revision algorithms to examine how individuals’ religious beliefs are shaped by factors such as personal experiences, social interactions, and exposure to new information. Simulating these dynamics can provide researchers with insight into the mechanisms that drive belief stability, conversion, and the emergence of religious diversity within populations. Indeed, “change processes” are a crucial aspect of religious experience to analyze. The study of how individuals undergo personal transformations, shifts in beliefs, or spiritual growth within a religious context can provide valuable insights into the dynamics of human behavior and the impact of religion on individuals and societies. Analyzing change processes in religious experiences can help researchers understand how and why individuals adopt new beliefs, practices, or worldviews. It can also shed light on the psychological, emotional, and social factors that contribute to religious conversion, de-conversion, or shifts in religious identity. By examining change processes in religious experiences, researchers can explore questions related to personal growth, identity formation, community dynamics, and the role of religious beliefs in shaping individuals’ lives. Understanding how these processes unfold can deepen our knowledge of the complexity and diversity of religious experiences and their implications for individual well-being and societal development (Ecker et al. 2022).
  • Exploring Religious Experience and Ritual: The integration of cognitive models and computational simulations facilitates the exploration of the cognitive processes underlying religious experiences and rituals (Taves and Asprem 2017). Researchers can examine how attentional focus, emotional arousal, and sensory integration affect individuals’ engagement with religious practices by simulating religious rituals (Hobson et al. 2018). Understanding the cognitive processes underlying religious experiences, such as mystical encounters, prayer, and transcendence, can be achieved through computer simulations (Umbrello 2023).
  • Examining Cognitive Biases and Religious Beliefs (Willard and Norenzayan 2013). Cognitive biases play a pivotal role in shaping religious beliefs and experiences (Gagliardi 2023). Integrating cognitive models and computational simulations allows researchers to examine the influence of cognitive biases, such as confirmation bias, availability bias, and attribution bias, on the formation and maintenance of religious beliefs (Gagliardi 2023). A deeper understanding of how cognitive biases interact with other cognitive processes is possible through these simulations, which contribute to the structure and resilience, or susceptibility, of religious belief systems (Williams et al. 2022).
  • By integrating cognitive models and computational simulations with neuroscience research, a multi-faceted exploration of religious belief can be exploration (Sugiura et al. 2015). Establishing connections between cognitive processes and neural mechanisms allows researchers to investigate how the brain networks and neural activity underlie religious cognition (Yen et al. 2023). The neurocognitive foundation of religious experiences, the impact of religious practices on brain function, and the neural correlates of belief formation and change are discussed in this interdisciplinary approach (Harris et al. 2009).

4. Artificial Intelligence and the Simulation of Religious Experiences

4.1. Exploration of How AI Technologies Can Simulate or Enhance Religious Experiences

The exploration of how artificial intelligence (AI) technologies can simulate or enhance religious experiences represents a fascinating and intellectually demanding area of investigation (Umbrello 2023). The potential of artificial intelligence in simulating or augmenting various aspects of religious experiences is being explored by researchers (Puzio 2023).
  • AI technologies allow for the simulation of religious rituals and practices, resulting in virtual or augmented reality experiences (Mann 2019). AI can create immersive environments that allow individuals to engage in religious practices remotely by replicating the sensory elements associated with religious ceremonies (Umbrello 2023). Through AI-powered simulations, individuals can engage in virtual religious rituals and ceremonies, fostering a deep sense of connection and belonging, regardless of their physical location (Campbell 2011, Introducation).
  • AI-powered chatbots and virtual assistants have the potential to offer personalized religious guidance tailored to address individuals’ religious or existential inquiries. While they may excel in providing religious guidance, the realm of spiritual guidance presents a different challenge. Spiritual transformation often stems from inner reflection and discernment rather than external influence or cognitive processes. Hence, while AI can support individuals in their religious quests, the deeply personal and introspective nature of spiritual change may not align as seamlessly with the capabilities of AI technology. To provide personalized guidance and support, these conversational agents use extensive religious texts, theological principles, and philosophical frameworks. Through user input analysis and adaptive responses, AI can replicate interactions like those with spiritual leaders, giving individuals a personalized spiritual experience (Dingler et al. 2021).
  • AI technologies can enable individuals to embark on religious journeys without the need for physical travel by recreating sacred spaces and facilitating virtual pilgrimages (Rähme 2021). Virtual reality or augmented reality platforms can be used by individuals to explore and experience significant religious sites, historical landmarks, and sacred architecture (Scavarelli et al. 2021). The deepening of individuals’ understanding of religious heritage and the furtherment of a profound sense of spiritual connectedness can be achieved through these immersive encounters (Abdulla 2018).
  • The analysis and interpretation of religious texts and scriptures can be assisted by AI algorithms (Macagno and Salvato 2023). Artificial intelligence can help with comprehensive textual analysis, identify patterns, and extract semantic insights from religious texts by using natural language processing and machine learning techniques (Wagner et al. 2022). This helps scholars and theologians to explore the complexities of religious doctrines, historical contexts, and theological interpretations (Cormie 2020).
  • The exploration of AI technologies for simulating and enhancing religious experiences necessitates careful consideration of the ethical implications and challenges (Dorobantu 2022). The authenticity and integrity of religious practices, the possibility of commercializing or trivializing sacred traditions, and the impact on social and cultural dimensions within religious communities are among these concerns (Meintel 2021). Researchers and developers must approach this field with utmost sensitivity, respect for religious beliefs, and ensure the ethical and responsible use of AI technologies (Chubb 2022).
Intriguing possibilities for individuals seeking to engage with their faith and spirituality are presented by the exploration of AI technologies for simulating and enhancing religious experiences (Cheong 2021, Bounded Religious Automation at Work: Communicating Human Authority in Artificial Intelligence Networks). AI’s contribution to religion studies and practices can be significantly enhanced by simulating rituals, providing personalized guidance, creating virtual sacred spaces, aiding scriptural analysis, and addressing ethical considerations (Reed 2021). However, it is crucial to approach this field with meticulousness, ensuring that AI technologies are developed and deployed in a manner that respects the diverse beliefs, values, and traditions of religious communities (Huang et al. 2023).

4.2. Examination of Virtual Reality, Chatbots, and Other AI Applications in Providing Immersive Spiritual Experiences

The study of virtual reality (VR), chatbots, and other artificial intelligence (AI) applications in delivering immersive spiritual experiences (Moriuchi et al. 2021). Scholars have investigated the potential of these technologies to create immersive environments and interactions that enhance spiritual engagement by harnessing them (Mann 2019).
  • Virtual Reality technology enables individuals to experience significant religious sites and landmarks remotely by recreating sacred spaces and facilitating virtual pilgrimages (Chatzopoulou 2022). Users can experience detailed reconstructions of temples, churches, mosques, and other sacred locations through VR platforms that are both highly realistic and interactive. Individuals can engage in virtual pilgrimages thanks to this technological advancement, which fosters a profound sense of presence and deepens their spiritual connection to these revered spaces (Pietroni and Ferdani 2021).
  • Chatbots for Personalized Spiritual Guidance: AI-powered chatbots have emerged as a valuable tool for offering personalized spiritual guidance and support. To have meaningful conversations about religious beliefs, practices, and existential inquiries, these conversational agents use advanced natural language processing and machine learning algorithms (Reed 2021). Chatbots provide tailored insights, advice, and resources by simulated interactions with spiritual mentors or guides, which facilitate spiritual exploration and guidance in a flexible and accessible manner (Bhuiyan 2023).
  • AI applications, including machine learning and virtual agents, can be utilized to simulate religious rituals and practices (Puzio 2023). Historical data and cultural patterns can be analyzed by AI algorithms to create highly realistic simulations of religious ceremonies, capturing the intricate details of rituals, chants, and symbolic gestures (Chen and Ibrahim 2023). These simulations provide individuals with the opportunity to virtually engage in religious practices, fostering a sense of active participation and enabling them to learn and experience rituals from different religious traditions (Umbrello 2023).
  • Augmented reality (AR) technologies have the potential to enhance individuals’ spiritual experiences by overlaying digital content onto the physical world (Bryant and Hemsley 2022). Contextual information, visual representations, or audio guidance can be offered by AR applications when visiting religious sites or engaging in spiritual practices. AR is instrumental in advancing immersive spiritual encounters by enriching individuals’ understanding, deepening their connection to spiritual teachings, and facilitating a more immersive and interactive experience (Allal-Chérif 2022).
  • Ethical considerations and challenges: The examination of VR, chatbots, and other AI applications in providing immersive spiritual experiences necessitates careful consideration of the ethical implications and challenges (Siapka 2018). These concerns include authenticity, the possibility of commercializing or trivializing sacred traditions, privacy and data security concerns, and the impact on human-to-human spiritual interactions (Raquib et al. 2022). Scholars and practitioners must navigate these ethical challenges with utmost care, ensuring that the development and utilization of these technologies align with the values, beliefs, and cultural sensitivities of individuals seeking immersive spiritual encounters (Akguncorresponding and Greenhow 2022).
However, it is paramount to approach the development and implementation of these technologies with a meticulous consideration of ethical dimensions, ensuring that they are deployed responsibly and with due respect for the diverse beliefs and cultural contexts of individuals seeking immersive spiritual encounters (Ashraf 2022).

4.3. Ethical Considerations and Implications of Using AI to Simulate Religious Experiences

The use of artificial intelligence (AI) to simulate religious experiences presents a complex array of ethical considerations and implications that necessitate thorough academic investigation (Geraci 2008). It is necessary to critically analyze the ethical dimensions involved in simulating religious experiences through AI, even though AI technologies have the potential to enhance individuals’ engagement with spirituality (Raghav and Gulia 2023).
  • Simulating religious experiences through AI raises concerns regarding authenticity and integrity (Salvadore 2023). To faithfully replicate religious rituals, practices, and sacred spaces, it is necessary to pay careful attention to cultural context, respect religious traditions, and accurately portray the intricate nuances of religious experiences (Puzio 2023). Ethical considerations arise when AI simulations risk diluting or trivializing the profound significance of these experiences, potentially compromising the authenticity and integrity of religious practices (Singler 2020).
  • Commercialization and appropriation of AI simulations of religious experiences can present ethical challenges (Johns 2021). The development and marketing of AI technologies for profit is a risk of exploiting individuals’ spiritual needs and modifying sacred traditions (Elmahjub 2023). Cultural appropriation can happen when AI simulations of religious experiences are created without sufficient understanding or respect for the specific cultural and religious contexts, they represent (Dorobantu 2022). Establishing ethical guidelines is necessary to prevent undue commercialization and appropriation of religious practices (Pozzo 2020).
  • The use of AI to simulate religious experiences often involves the collection and analysis of personal data (J. E. Lane 2021). Concerns about privacy and data security are raised by this. AI-powered platforms can be used by individuals to disclose sensitive information about their religious beliefs, practices, and existential inquiries (Ashraf 2022). It is crucial to ensure robust data protection measures, informed consent, and transparent data handling practices to safeguard individuals’ privacy and prevent any unauthorized use or access to their personal information (Humerick 2018).
  • The introduction of AI simulations of religious experiences may have implications for human-to-human interactions within religious communities (H. A. Stahl 2022). The role of human spiritual leaders, mentors, or community interactions should not be replaced or diminished by AI technologies, although they can provide personalized spiritual guidance and support (Yin and Mahrous 2022). Ethical considerations demand that AI simulations of religious experiences complement rather than replace human-to-human connections, acknowledging the unique value of personal relationships and communal support within religious contexts (Findlay and Wong 2021).
  • Cultural sensitivity and respect for diverse religious beliefs and practices are necessary for the development and deployment of AI simulations of religious experiences (Olsher 2015). Extensive research, consultation, and collaboration with religious communities are essential to ensure that AI technologies are developed and utilized in a manner that aligns with their values, beliefs, and cultural sensitivities (Gabriel 2020). Establishing ethical guidelines is necessary to promote inclusivity, diversity, and respect for religious diversity in the design and implementation of AI simulations (Shults and Wildman 2020).
  • Responsible development and deployment of AI simulations of religious experiences necessitate adherence to ethical principles throughout the process (Truby 2020). This includes transparency in AI algorithms and decision-making processes, ensuring accountability for the outcomes of AI and simulations, and ongoing monitoring and evaluation to mitigate potential biases or unintended consequences (Busuioc 2021). Establishing ethical guidelines and regulatory frameworks is necessary to guide the responsible development and deployment of AI technologies in the realm of religious experiences (Stahl et al. 2022).
Scholars, practitioners, and developers must engage in critical discussions and ethical reflections as the use of AI to simulate religious experiences progresses (Graves 2023, What Does it Mean to Consider AI a Person?). By addressing the considerations outlined above, researchers can contribute to the responsible and ethical use of AI technologies, ensuring that they respect religious beliefs, foster cultural sensitivity, and enhance individuals’ spiritual experiences without compromising authenticity, integrity, privacy, or human-to-human interactions (Ashraf 2022).

5. AI-Assisted Analysis of Religious Texts

5.1. Analysis of Large-Scale Religious Text Corpora Using Natural Language Processing and Machine Learning Algorithms

The analysis of large-scale religious text corpora through the application of natural language processing (NLP) and machine learning algorithms represents a significant advancement in the study of religious texts (Adel et al. 2022). By harnessing computational methods, researchers can delve into the linguistic, semantic, and thematic aspects of religious texts, thereby facilitating a profound understanding of religious beliefs, practices, and traditions (Nowell et al. 2017).
  • Corpus preprocessing NLP techniques play a crucial role in preprocessing and cleaning large religious text corpora, rendering them amenable to analysis (Uysal and Gunal 2014). Tasks such as tokenization, sentence segmentation, part-of-speech tagging, and lemmatization aid in extracting the fundamental linguistic units and structural information from the texts (Khurana et al. 2023, Natural language processing: state of the art, current trends and challenges). This preprocessing step ensures a standardized representation of the corpus, facilitating subsequent analyses (Berenguer et al. 2023).
  • Semantic analysis NLP algorithms, including topic modeling and word embedding techniques, offer robust methods for discerning the semantic structure and latent topics within religious texts (Koehler et al. 2020). Topic modeling algorithms, such as Latent Dirichlet Allocation (LDA), enable the identification of key themes and topics present in the corpus (Chauhan and Shah 2021). Word embedding models, such as Word2Vec and GloVe, provide vector representations of words, capturing their semantic relationships and contextual information (Asudani et al. 2023). These techniques enable researchers to uncover the underlying meanings and conceptual frameworks embedded within religious texts (Collins and Stockton 2018).
  • Sentiment analysis algorithms empower researchers to assess the emotional tone and sentiment conveyed within religious texts (Wang and Wang 2023). By automatically classifying text segments as positive, negative, or neutral, sentiment analysis sheds light on the affective dimensions of religious texts (Yusof et al. 2015). This analysis aids in understanding the emotional nuances, attitudes, and expressions manifested by religious authors, thereby enriching our comprehension of religious beliefs and practices (Héliot et al. 2019).
  • Named entity recognition (NER) algorithms facilitate the identification and classification of named entities, such as people, locations, and organizations, within religious texts (Goyal et al. 2018). This technique assists in identifying important figures, significant places, and religious institutions mentioned in the texts (Nowell et al. 2017). NER enhances the study of historical figures, religious leaders, and their pivotal roles in shaping religious beliefs and practices (Dowd 2015).
  • Text classification and prediction machine learning algorithms, including support vector machines, decision trees, or deep learning models, enable text classification and prediction tasks within religious text corpora (Hassan et al. 2022). Researchers can train models to classify texts into predefined categories, such as religious genres, theological concepts, or historical periods. These models can also be utilized for predictive tasks, such as predicting the authorship or dating of religious texts, thereby yielding valuable insights into the historical and literary dimensions of religious traditions (Gattal et al. 2023).

5.2. Computational Methods for Analyzing and Interpreting Religious Texts, including Semantic Analysis and Sentiment Analysis

Religious texts have traditionally been interpreted and analyzed using subjective human expertise (Andriansyah 2023). Objective and data-driven approaches to the study of these texts have been introduced by recent advances in computational methods. Semantic analysis and sentiment analysis are two significant computational methods used in the analysis and interpretation of religious texts (Taherdoost and Madanchian 2023).
  • Semantic analysis involves the examination of the meaning and relationships between words and phrases within a text (Khurana et al. 2023, Natural language processing: state of the art, current trends and challenges). The goal of semantic analysis of religious texts is to uncover the underlying themes, concepts, and connections present in the text (Verma 2017). The use of natural language processing algorithms and linguistic resources is utilized in this method to extract and analyze the semantic structures that are inherent in religious texts (Torregrosa et al. 2023). Theological, philosophical, and moral dimensions of religious texts by utilizing AI tools to identify key terms, categorize concepts, and map semantic networks. By applying natural language processing algorithms and machine learning techniques, researchers can uncover underlying themes, relationships between concepts, and the evolution of ideas within religious scriptures. This analytical approach allows for a deeper understanding of the intricate theological, philosophical, and ethical teachings embedded in these texts, enabling scholars to explore the nuances and complexities of religious thought in a more systematic and comprehensive manner (Graves 2021, Emergent Models for Moral AI Spirituality).
Semantic analysis techniques, such as named entity recognition, entity linking, and topic modeling, assist in identifying specific entities (e.g., deities, places, or events), linking them to external knowledge bases, and uncovering latent topics within religious texts (Goyal et al. 2018). Scholars can use these techniques to explore the connections between different religious ideas, trace the evolution of concepts across texts, and identify differences or similarities between different religious traditions (Nieminen et al. 2020).
2.
Sentiment analysis of religious texts aims to determine the emotional tone, attitude, or sentiment conveyed in a text (Nandwani and Verma 2021). The emotional and affective dimensions of religious expressions can be unearthed through sentiment analysis in religious texts. Machine learning algorithms are typically used in this method to categorize text passages as either positive, negative, or neutral based on the sentiment expressed (Hewitt 2012).
Analyzing sentiment in religious texts can provide researchers with insights into the emotional experiences, beliefs, and values of religious communities. Sentiment analysis enables the identification of passages that express praise, gratitude, or spiritual longing, as well as those that indicate doubt, fear, or moral conflict (Bowie et al. 2022). The deeper understanding of the emotional and affective aspects of religious texts and their role in shaping religious experiences and practices is enhanced by these findings (Sameera and Khadijah 2023).
3.
Religious texts can be analyzed using both semantic analysis and sentiment analysis, with different applications and limitations (Birjali et al. 2021). Researchers can uncover hidden patterns, explore theological concepts, trace the development of ideas, and gain a complete understanding of religious texts across different traditions using these methods (Nath et al. 2023). Comparative studies can be facilitated, textual variations can be identified, and complex religious doctrines can be interpreted with their help.
Acknowledging the limitations of these computational methods is crucial. Metaphorical or symbolic language is often used in religious texts, which may not be adequately captured by semantic or sentiment analysis alone (Jackson et al. 2022). The cultural and historical contexts in which religious texts were produced pose challenges to accurate analysis, as computational methods may not fully capture the nuances and subtleties of religious language and interpretation (Nishant et al. 2023). Combining computational approaches with human expertise and critical hermeneutics is crucial for achieving a comprehensive and nuanced understanding of religious texts (Gill et al. 2017).

5.3. The Role of AI in Uncovering Patterns, Themes, and Symbolism in Religious Scriptures

The use of artificial intelligence (AI) technologies has great potential for the analysis of religious scriptures, as they facilitate the discovery of patterns, themes, and symbolism embedded within these texts (Santos et al. 2023). AI can help scholars and researchers uncover hidden insights and improve their comprehension of religious scriptures by using advanced computational algorithms (Reed 2021). In this section, we will explore how AI can uncover patterns, themes, and symbolism in religious scriptures (Geraci 2008).
  • The identification and extraction of recurring patterns within religious scriptures can be achieved through AI techniques such as pattern recognition and text mining (Hassani et al. 2020). By analyzing a vast amount of textual data, AI algorithms can automatically detect and analyze repeated words, phrases, or syntactical structures. The identification of textual patterns, such as parallelisms, charms, or other rhetorical devices commonly employed in religious literature, is made easier by this (Redondo and Sandoval 2016).
AI can help identify textual variations, such as different versions or translations of religious scriptures, by using pattern recognition. This enables scholars to trace the evolution and transmission of religious texts, thereby discerning changes or adaptations over time (Umbrello 2023). By uncovering these patterns with AI, one can gain a deeper understanding of the textual structure and linguistic characteristics of religious scriptures (Andriansyah 2023).
2.
AI-powered techniques, such as topic modeling and clustering algorithms, can assist in extracting and analyzing themes present in religious scriptures (Albalawi et al. 2020). Researchers can identify overarching themes and sub-themes within the texts by automatically grouping similar passages based on their content using these algorithms (Hitch 2023).
Using AI, scholars can gain insights into the dominant theological, moral, or philosophical themes addressed in religious scriptures (Barbour 2004). This not only makes it easier to comprehend the religious doctrines and teachings embedded in the scriptures, but it also allows for comparative studies across different religious traditions (Geraci 2008). The underlying conceptual frameworks are revealed in the AI-driven analysis of themes, which serves as a basis for further exploration and interpretation (Gerlich 2023).
3.
Symbolism and metaphor detection can be assisted by AI technologies in the detection and interpretation of symbolism and metaphorical expressions found in religious scriptures (Geraci 2008). Religious literature often uses symbolism and metaphors to convey deeper meanings and spiritual truths (Susanto et al. 2023). AI algorithms can identify metaphorical language and symbolic references within the texts by utilizing natural language processing techniques (Kang et al. 2020).
The AI-driven analysis assists in uncovering the rich symbolic tapestry that is woven into religious texts, revealing the metaphorical language used to convey spiritual truths and insights (Umbrello 2023).
4.
Ethical considerations and human interpretation. While AI technologies offer valuable capabilities for uncovering patterns, themes, and symbolism in religious scriptures, it is crucial to recognize the importance of human interpretation and critical analysis (Blanchard and Taddeo 2023). AI algorithms are powerful, but they do not have the nuanced understanding and contextual knowledge that human scholars possess (Jarrahi 2018). The analysis of religious texts requires human expertise to provide the necessary interpretation, contextualization, and cultural understanding (J. Wang 2021).
Moreover, ethical considerations must guide the use of AI in the religious scripture analysis. It is important to address sensitiveness to diverse religious beliefs and the potential for misinterpretation or misrepresentation of sacred texts with care (Gretchen 2022).

5.4. Challenges and Limitations in Applying AI to Religious Text Analysis, Such as Cultural Context and Linguistic Nuances

The utilization of artificial intelligence (AI) for the analysis of religious texts presents several challenges and limitations, primarily in relation to the cultural context and linguistic nuances inherent in such texts (Spennemann 2023). The application of AI techniques in this domain requires careful consideration of these factors (Grassini 2023). This section provides an exploration of the challenges and limitations associated with the application of AI to religious text analysis, with a specific focus on cultural context and linguistic nuances.
  • Religious texts are deeply embedded within specific cultural contexts, and it is possible that AI will have access to a more extensive historical record than any individual scholar or group of scholars in the field. However, when it comes to interpreting religious texts, it is crucial to consider that these texts are deeply intertwined with specific cultural contexts. A comprehensive grasp of these contexts is vital for accurate interpretation (Elster 2003). While AI algorithms may have the capacity to process vast amounts of data, they may struggle to fully comprehend the intricate cultural nuances and historical backgrounds associated with religious scriptures (Reed 2021). Consequently, there is a potential for misinterpretation or oversimplification of the texts when relying solely on AI, as AI lacks the contextual knowledge and cultural understanding that human scholars bring to the table (Brown 2020).
The cultural context encompasses a broad array of elements, including societal norms, historical events, religious practices, and cultural symbolism (Abdulla 2018). The meaning and interpretation of religious texts are greatly influenced by these factors, and any omission or misinterpretation by AI models can result in incomplete or distorted analyses. Therefore, it is imperative to complement an AI-driven approach with human expertise to ensure a comprehensive understanding of the cultural context surrounding religious texts (Umbrello 2023).
2.
Linguistic nuances: Religious texts often employ intricate linguistic structures, metaphorical language, and symbolic expressions that pose challenges for AI algorithms. AI techniques have a reputation for processing and analyzing large volumes of text, but they may not be able to capture the subtleties and nuances of religious language and interpretation (Reed 2021).
Religious texts have linguistic nuances that include metaphorical or allegorical language, poetic devices, and specific terminologies with layered meanings (Harrison 2007). These nuances require a deep understanding of the religious traditions, theological concepts, and historical developments associated with the texts. AI algorithms, lacking contextual understanding, may provide incomplete or inaccurate interpretations of the linguistic nuances present in religious scriptures (Umbrello 2023).
Furthermore, the variety of languages used in religious texts further complicates AI analysis (Bhuiyan 2023). AI models may face obstacles in accurately processing and comprehending multiple languages, especially those with complex grammatical structures or limited training data (Kaddour et al. 2023). This language barrier hinders the application of AI across a wide range of religious texts and traditions (Gibney 2022).
3.
AI algorithms are trained on extensive datasets, which may contain biases and preconceptions inherent in the data itself. When applied to the religious text analysis, these biases can influence the interpretation and analysis of the texts. Stereotypes can be reinforced, marginalized perspectives can be overlooked, or the intended meanings within religious scriptures can be misrepresented due to biased results. For example, some researchers are exploring the use of apophatic strategies in mystical texts and T2I models to highlight the mutual benefit of theorizing AI with the help of religious theory and concepts (Z. Chen 2023).
Addressing biases requires a meticulous curating and preprocessing of training data, ensuring diversity and representation of different religious traditions, perspectives, and cultural contexts (Reed 2021). Regularly evaluating and refining AI models can aid in identifying and rectifying biases that may arise during the analysis of religious texts (Dorobantu 2022).
4.
Interpretive complexity: Religious texts are subject to diverse interpretive approaches and hermeneutical methods (Johnston 2022). Different scholars and religious communities may have different interpretations of the same text, leading to a multitude of meanings and understandings (Josselson 2004). The nature of AI algorithms, which are deterministic, may make it difficult to navigate this interpretive complexity, often offering a single, rigid interpretation that ignores the diversity of diverse perspectives (Li et al. 2022).
AI can aid in identifying patterns and themes, but it is crucial to acknowledge that understanding religious texts necessitates human insight, critical thinking, and cultural sensitivity (Dwivedi et al. 2023b). AI should be seen as a tool to aid and complement human interpretation rather than as a substitute for it (Sezgin 2023).

5.5. Exploration of How AI Technologies Are Transforming Traditional Religious Practices and Rituals

The integration of artificial intelligence (AI) technologies has the potential to bring about significant changes in traditional religious practices and rituals (Furst 2021). This part examines the ways in which AI technologies are influencing and shaping these practices, while also exploring the associated opportunities and challenges.
  • AI technologies that enhance accessibility and outreach are making religious teachings, scriptures, and rituals more accessible (Ashraf 2022). Online platforms and mobile applications powered by AI algorithms make it convenient for individuals to access religious texts, sermons, and educational resources (Berger and Golan 2023). Individuals can engage with their faith traditions regardless of their physical location thanks to this increased accessibility that transcends geographical and logistical boundaries. AI-powered language translation tools enable multilingual access to religious content, which promotes inclusivity and global engagement (Andriansyah 2023).
Additionally, chatbots, and virtual assistants driven by AI provide personalized guidance and support, dealing with queries and concerns related to religious practices. Individuals can seek spiritual guidance at their convenience with the help of these virtual companions who provide round-the-clock availability. Consequently, religious communities can expand their outreach, connect with diverse audiences, and provide support and resources to individuals worldwide (Vishwanatha et al. 2023).
2.
Language interpretation and translation play a crucial role in religious practices, particularly in contexts where religious texts or rituals are conducted in unfamiliar languages (Gunawan 2022). AI-driven language processing systems, like natural language processing and machine translation, are transforming communication and understanding across language barriers (McLoughlin and Indurkhya 2023).
Real-time translation of religious sermons, ceremonies, or discussions can be performed using AI technologies, which allows participants to comprehend and engage with the content in their native language (Cheong 2020, Religion, Robots and Rectitude: Communicative Affordances for Spiritual Knowledge and Community). Cross-cultural dialogue within religious communities is facilitated through this fosters inclusivity. In addition, AI-driven transcription services automatically transcribe and translate religious speeches or lectures, making them accessible to individuals with hearing impairments or language challenges (Shadiev et al. 2018).
3.
AI technologies offer the potential for automation and assistance in various aspects of religious rituals (Puzio 2023). Robotic automation, for instance, can streamline the production of religious artifacts, such as candles, incense sticks, or prayer beads, ensuring consistent quality while meeting the demands of ritual objects more efficiently (Balle and Ess 2020).
AI-powered devices and applications are capable of guiding individuals through religious rituals by giving them step-by-step instructions or recitations. Digital assistants make it easier to perform rituals accurately, particularly for complex ceremonies or prayers with specific sequences (Maedche et al. 2019). AI technologies can be used to provide reminders for important religious events, fasting periods, or prayer timings, as the phone apps 1-ImamAI: Ask the Quran! 2-Prayer Times Azan Reminder App ensuring religious obligations are met (Koubaa et al. 2020).
4.
Religious communities can use AI technologies to analyze and interpret vast amounts of data on religious practices, rituals, and community engagement (Bhuiyan 2023). Religious leaders and organizations can acquire valuable insights into attendance patterns, preferences, and levels of engagement within their communities using data analysis. Decision-making processes can be informed of this information, including optimizing sermon topics, organizing events, and identifying areas for community outreach and support (Furst 2021).
Furthermore, AI algorithms can be utilized to aid in the analysis of religious texts and scriptures, uncovering patterns, themes, and symbolic references (Turini 2023). Scholars and religious leaders gain a deeper understanding of their religious traditions through this analysis, which supports interpretation and teaching (Andriansyah 2023). The scholarly exploration of religious texts is enhanced by AI-driven data analysis and leads to insights into the historical, cultural, and theological dimensions of religious practices (Reed 2021).
5.
Ethical considerations and adaptation must be addressed while AI technologies present new opportunities for religious communities (Ryan and Stahl 2020). Navigating the potential risks of relying too much on AI is crucial, as it ensures that human connections, empathy, and personal engagement are still central to religious experiences. It is crucial to consider the preservation of cultural authenticity and the avoidance of cultural appropriation when using AI technologies (Stahl et al. 2023, Ethics of Artificial Intelligence Case Studies and Options for Addressing Ethical Challenges).
Religious leaders, scholars, and practitioners must constantly engage in dialogue and reflection to adjust AI technologies to match their religious values and practices. Establishing guidelines and frameworks that promote responsible and ethical integration of AI in religious contexts can be achieved through collaboration with AI experts and ethicists (Rodríguez et al. 2023).

5.6. Examination of AI-Powered Religious Apps, Virtual Religious Communities, and Online Religious Services

Artificial intelligence (AI) technologies have led to the development of various applications, platforms, and services that enhance religious experiences and foster virtual religious communities. AI-powered religious apps utilize machine learning algorithms and natural language processing to offer an array of features and functionalities that enhance religious engagement. The following elements are commonly included in these apps:
  • AI algorithms facilitate the digitization and organization of religious texts, providing users with convenient access to sacred scriptures. Personalized study and reflection can be achieved by users by searching, bookmarking, and annotating these texts. AI-powered chatbots or virtual assistants provide personalized guidance to address common queries related to religious practices, beliefs, and rituals. On-demand support is provided by these virtual companions, which help users navigate their spiritual journeys (Bhuiyan 2023).
Prayer reminders: AI-driven apps use notifications to remind individuals of prayer timings, fasting periods, or significant religious events. This feature aids users in fulfilling their religious obligations and upholding their spiritual routines (Karataş and Cutright 2023). AI technologies enable real-time translation of religious content, overcoming language barriers and allowing users to engage with religious teachings in their native language. This language inclusivity fosters accessibility and understanding (Zaid and Bennoudi 2023).
AI-powered apps often include features that facilitate community building, like forums, discussion boards, or integration with social media platforms. The religious community’s sense of belonging and connection is strengthened by these features that encourage interaction and collaboration among users (André 2023).
2.
Virtual religious communities encompass online platforms that bring together individuals who share common religious beliefs and practices. AI technologies significantly contribute to the creation and maintenance of these communities (Dein 2020).
Individuals can participate in religious services, ceremonies, or events remotely through online congregations. The feeling of physical presence in a religious setting can be enhanced by immersive technologies, such as AI-powered video streaming, virtual reality, or augmented reality (Partarakis and Zabulis 2024).
Virtual communities offer platforms for collaboration, resource sharing, and support. Matching individuals with similar interests, fostering connections, and facilitating the exchange of ideas and experiences related to their faith are all made possible by AI algorithms (Kim et al. 2022).
3.
Online religious services encompass a range of religious practices and rituals conducted in virtual spaces. AI technologies contribute to the effectiveness and accessibility of these services (Singler 2020).
Individuals can participate in virtual religious services, such as sermons, prayers, or religious lectures, using AI-powered platforms. The inclusion of interactive features in these platforms often leads to users being able to engage and respond in real-time, creating a sense of collective worship (Lazzarino 2023). AI technologies guide individuals through religious rituals by providing step-by-step instructions or recitations (Tan 2020). This feature proves particularly valuable for those who are unfamiliar with certain rituals or unable to attend physical, religious gatherings, ensuring proper adherence to established practices (Furst 2021).
The role of human connection: Virtual experiences should complement, rather than replace, physical, religious practices and human connections. To ensure the preservation of meaningful religious experiences, it is crucial to balance technology-mediated interactions and in-person religious engagement. Access to AI-powered religious apps and online services may be hindered by factors such as internet availability, technological literacy, or socioeconomic disparities. To ensure equitable access to these technologies within religious communities, it is important to make efforts to bridge the digital divide (Ashraf 2022).

5.7. Ethical Considerations and Potential Consequences of AI Integration in Religious Practices

  • Autonomy and Human Agency: The integration of AI into religious practices raises concerns about the potential erosion of individual autonomy and human agency (Laitinen and Sahlgren 2021). Personal interpretation and decision-making could be compromised by AI providing personalized recommendations and dictating religious rituals, potentially undermining the individual’s role in shaping their religious experiences (Steyvers and Kumar 2023).
  • Algorithmic bias and discrimination: AI algorithms can inadvertently perpetuate bias and discrimination (Varona and Suárez 2022). This raises concerns about reinforcing existing prejudices or discriminatory outcomes in religious practices. The development of AI systems requires an awareness of potential biases, rigorous testing, and measures to minimize discriminatory effects (Varsha 2023).
  • Privacy and data security: The collection and analysis of personal data in AI-powered religious practices raises concerns about privacy and data security (Aldoseri et al. 2023). Religious organizations and developers must ensure the protection of sensitive information by implementing robust data protection measures, obtaining informed consent, and adhering to privacy regulations (Buttarelli 2016).
  • While AI-powered apps and services improve accessibility, there are concerns about the authenticity and genuineness of spiritual experiences (Umbrello 2023). Preserving the spiritual integrity and meaningfulness of rituals requires striking a balance between technology-mediated experiences and traditional religious practices (Claisse and Durrant 2023).
  • Theological implications and doctrinal interpretation: Integrating AI into religious practices raises theological questions and challenges (Dorobantu 2022). The interpretations of sacred texts, rituals, and doctrines within religious traditions may not match those generated by AI (Geraci 2008). Careful consideration is needed to ensure that AI aligns with religious teachings and to address the implications for religious authority, interpretation, and knowledge transmission (J. E. Lane 2021).
  • The adoption of AI in religious practices may exacerbate existing inequalities in access to technology and digital resources. To avoid excluding or disadvantaging certain individuals or communities, efforts should be made to ensure equitable distribution, taking into account socioeconomic disparities, technological literacy, and internet access (Rodrigues 2020).
  • Maintaining transparency and accountability is essential in religious practices powered by AI. It is important for users to be informed about the limitations, potential biases, and decision-making processes of AI usage (Rodríguez et al. 2023). Building trust and enabling individuals to make informed decisions about their religious engagement can be achieved through open and clear communication (Robinson 2020).
  • Ethical governance and regulation are necessary given the potential consequences. A collaboration between religious leaders, technologists, ethicists, and policymakers is crucial to establish guidelines, ethical frameworks, and regulatory mechanisms to ensure responsible and accountable use of AI in religious contexts (B. C. Stahl 2022, Organisational responses to the ethical issues of artificial intelligence).

6. Ethical and Societal Implications of AI in Religion

6.1. Examination of Ethical Considerations Arising from the Intersection of AI and Religion

  • The incorporation of AI in religious contexts raises significant concerns regarding individual autonomy and human agency (Elmahjub 2023). Relying on AI-generated recommendations and rituals may decrease personal interpretation and decision-making, potentially undermining the individual’s ability to shape their religious experiences (Jackson et al. 2023).
  • Algorithmic biases: The inherent biases within AI algorithms, stemming from their training on existing data, can inadvertently perpetuate the biases and discrimination (D. Dwivedi 2023). Within religious practices, this raise concerns surrounding the reinforcement of existing prejudices or the propagation of discriminatory outcomes (Vang et al. 2019). It is imperative to develop and deploy AI systems that possess a robust awareness of potential biases, undergo rigorous testing, and are subject to ongoing auditing to mitigate the adverse effects of algorithmic bias (Fu et al. 2020).
  • The use of AI-powered platforms in religious practices introduces profound questions regarding the authenticity and genuineness of religious experiences. Although these platforms provide enhanced accessibility and convenience, they may not be capable of capturing the depth and richness of in-person religious engagement (Umbrello 2023). Preserving the spiritual integrity and meaningfulness of religious rituals requires a delicate balance between technology-mediated experiences and the authenticity of traditional religious practices.

6.2. The Role of Religious Leaders, Scholars, and Policymakers in Addressing These Ethical Challenges

  • Religious leaders play a pivotal role in addressing the ethical challenges associated with AI in religion. Guidance and interpretation can be provided to ensure that AI technologies align with religious teachings, values, and traditions. Engaging in dialogue with their communities can help religious leaders develop critical thinking, ethical awareness, and responsible AI usage. They also have the responsibility to address concerns related to the authenticity, spirituality, and the meaningfulness of religious experiences mediated by AI (Abramov 2020).
  • Scholars of religion play a vital role in examining the ethical implications of AI in religious contexts. They can critically analyze the impact of AI on religious traditions, practices, and beliefs because of their expertise in theology, ethics, and religious studies (Umbrello 2023). Conducting research and publishing scholarly work can help them develop guidelines, ethical frameworks, and best practices for integrating AI in religious settings. Religious scholars are responsible for educating and raising awareness among religious communities about the potential ethical challenges and opportunities presented by AI (Puzio 2023).
  • Policymakers have a significant role to play in addressing the societal implications of AI in religion (Larsson 2019). In the context of AI-mediated religious practices, they can create regulatory frameworks that guarantee transparency, accountability, and the protection of individuals’ rights (Novelli 2023). It is important for policymakers to collaborate with religious leaders, scholars, and technology experts to create policies that reduce algorithmic bias, safeguard privacy, promote inclusivity, and address access disparities. Fostering interdisciplinary dialogue and establishing mechanisms for ongoing monitoring and evaluation of AI technologies used in religious contexts is necessary (Vinichenko et al. 2020).
  • Collaboration and dialogue among religious leaders, scholars, and policymakers are essential to effectively address the ethical challenges and societal implications of AI in religion (Trotta 2023). Fostering interdisciplinary partnerships can help these stakeholders exchange knowledge, perspectives, and experiences. The development of comprehensive guidelines, ethical frameworks, and policies that incorporate diverse viewpoints and considerations can be achieved through this collaboration (Furst 2021).

7. Research Results

-
In these recent studies we highlighted highlight the growing significance of artificial intelligence (AI) in exploring the psychology of religion. AI technologies such as natural language processing and machine learning algorithms are being used to analyze large datasets of religious texts, beliefs, and practices. These tools enable researchers to identify patterns, trends, and correlations within religious data that were previously difficult to uncover through traditional methods. AI-driven sentiment analysis helps researchers understand the emotional tone and sentiment associated with religious texts and how they influence individuals’ beliefs and behaviors. Additionally, AI is employed to simulate religious experiences and rituals, providing insights into the psychological mechanisms underlying religious practices. The integration of AI in the study of the psychology of religion offers new perspectives and methodologies that contribute to a deeper understanding of how individuals perceive, interpret, and engage with religious beliefs and experiences. Ultimately, exploring the influence of AI on the psychology of religion prompts reflection on the essence of spirituality, belief formation, and the human experience at large.
-
Implications and Recommendations: 1-Responsible Development: The responsible development and deployment of AI technologies in the psychology of religion require careful consideration of ethical implications to ensure alignment with religious teachings and respect for diverse beliefs. 2-Stakeholder Collaboration: Collaboration among religious leaders, scholars, policymakers, and technology experts is crucial for developing guidelines and policies that address societal implications of AI in religion, ensuring transparency, accountability, and ethical integration.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

No new data were created or analyzed in this study. Data sharing is not applicable to this article.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Abdulla, M. R. 2018. Culture, Religion, and Freedom of Religion or Belief. The Review of Faith & International Affairs 16: 102–15. [Google Scholar]
  2. Abramov, A. A. 2020. Religious and Ethical Issues of Artificial Intelligence: Expert Assessments and the Vatican Position. Koнцeпт: φилocoφия, peлигия, кyльтypa 4: 68–82. [Google Scholar] [CrossRef]
  3. Adel, B., M. C. Meftah, A. Laouid, and M. Hammoudeh. 2022. Machine Learning to Classify Religious Communities and Detect Extremism on Social Networks: ML to CRCs and DE Through Text Tweets on SNs. International Journal of Organizational and Collective Intelligence (IJOCI) 12: 1–19. [Google Scholar] [CrossRef]
  4. Akguncorresponding, S., and C. Greenhow. 2022. Artificial intelligence in education: Addressing ethical challenges in K-12 settings. AI Ethics 2: 431–40. [Google Scholar]
  5. Albalawi, R., T. H. Yeap, and M. Benyoucef. 2020. Using Topic Modeling Methods for Short-Text Data: A Comparative Analysis. Methods 3: 14. [Google Scholar] [CrossRef] [PubMed]
  6. Aldoseri, A., K. N. Al-Khalifa, and A. M. Hamouda. 2023. Re-Thinking Data Strategy and Integration for Artificial Intelligence: Concepts, Opportunities, and Challenges. Applied Sciences 13: 7082. [Google Scholar] [CrossRef]
  7. Allal-Chérif, O. 2022. Intelligent cathedrals: Using augmented reality, virtual reality, and artificial intelligence to provide an intense cultural, historical, and religious visitor experience. Technological Forecasting and Social Change 178: 121604. [Google Scholar] [CrossRef]
  8. André, F. 2023. A New AI App Lets Users ‘Text’ with Jesus. Some Call It Blasphemy. The Washington Post. August 12. Available online: https://www.washingtonpost.com/religion/2023/08/12/text-with-jesus-chatgpt-ai/ (accessed on 12 August 2023).
  9. Andriansyah, Y. 2023. The Current Rise of Artificial Intelligence and Religious Studies: Some Reflections Based on ChatGPT. Journal of Religious Studies 22: 9–18. [Google Scholar] [CrossRef]
  10. Ashraf, C. 2022. Exploring the impacts of artificial intelligence on freedom of religion or belief online. The International Journal of Human Rights 26: 757–91. [Google Scholar] [CrossRef]
  11. Asudani, D. S., N. K. Nagwani, and P. Singh. 2023. Impact of word embedding models on text analytics in deep learning environment: A review. Artificial Intelligence Review 56: 10345–425. [Google Scholar] [CrossRef]
  12. Badran, L., and A. Hejazi. 2023. Muslim social workers’ recommendation of parents with mental illness or intellectual disability disorders in vignettes of simulated religious court cases of custody, marriage, and divorce. Journal of Religion & Spirituality in Social Work: Social Thought 42: 302–22. [Google Scholar]
  13. Balle, S., and C. Ess. 2020. Robots in Religious Contexts. IOS Press Ebooks 335: 585–91. [Google Scholar]
  14. Bankston, C. L. 2002. Rationality, Choice and the Religious Economy: The Problem of Belief. Review of Religious Research 43: 311–25. [Google Scholar]
  15. Barbour, I. G. 2004. Neuroscience, Artificial Intelligence, and Human Nature: Theological and Philosophical Reflections. Journal of Religion & Science 34: 361–98. [Google Scholar]
  16. Berenguer, A., J.-N. Mazón, and D. Tomás. 2023. Word embeddings for retrieving tabular data from research publications. Machine Learning, 1–22. [Google Scholar] [CrossRef]
  17. Berger, A., and O. Golan. 2023. Online religious learning: Digital epistemic authority and self-socialization in religious communities. Learning, Media and Technology, 1–16. [Google Scholar] [CrossRef]
  18. Bhuiyan, J. 2023. Are Chatbots Changing the Face of Religion? Three Faith Leaders on Grappling with AI. The Guardian. April 7. Available online: https://www.theguardian.com/technology/2023/apr/07/chatgpt-artificial-intelligence-religion-faith-leaders (accessed on 12 August 2023).
  19. Birjali, M., M. Kasri, and A. Beni-Hssane. 2021. A comprehensive survey on sentiment analysis: Approaches, challenges and trends. Knowledge-Based Systems 226: 107134. [Google Scholar] [CrossRef]
  20. Blanchard, A., and M. Taddeo. 2023. The Ethics of Artificial Intelligence for Intelligence Analysis: A Review of the Key Challenges with Recommendations. Digital Society 2: 2–12. [Google Scholar] [CrossRef] [PubMed]
  21. Bodenhausen, G. V. 1990. Stereotypes as Judgmental Heuristics: Evidence of Circadian Variations in Discrimination. Psychological Science 1: 319–22. [Google Scholar] [CrossRef]
  22. Bowie, R. A., F. Panjwani, and K. Clemmey. 2022. A meta approach to texts in religious education: Researching teachers’ engagement with sacred text scholarship in English secondary schools. British Journal of Religious Education 44: 271–80. [Google Scholar] [CrossRef]
  23. Brown, R. D. 2020. Property ownership and the legal personhood of artificial intelligence. Information & Communications Technology Law 30: 208–34. [Google Scholar]
  24. Brubaker, P. J., and M. M. Haigh. 2017. Individuals can share and validate their religious encounters in religious communities and social networks. Social Media + Society 3: 2056305117703723. [Google Scholar]
  25. Bryant, L., and B. Hemsley. 2022. Augmented reality: A view to future visual supports for people with disability. Disability and Rehabilitation: Assistive Technology, 1–14. [Google Scholar]
  26. Busuioc, M. 2021. Accountable Artificial Intelligence: Holding Algorithms to Account. Public Administration Review 81: 825–36. [Google Scholar] [CrossRef]
  27. Buttarelli, G. 2016. Personal Data Protection in Churches and Religious Organisation. European Data Protection Supervisor. February 25. Available online: https://edps.europa.eu/sites/edp/files/publication/16-02-25_personal_data_protection_church_warsaw_en.pdf (accessed on 12 August 2023).
  28. Campbell, H. A. 2011. Introducation. Information, Communication & Society 14: 1083–96. [Google Scholar]
  29. Campbell, H. A. 2012. Understanding the Relationship between Religion Online and Offline in a Networked Society. Journal of the American Academy of Religion 80: 64–93. [Google Scholar] [CrossRef]
  30. Carone, D. J., and D. Barone. 2001. A social cognitive perspective on religious beliefs: Their functions and impact on coping and psychotherapy. Clinical Psychology Review 21: 989–1003. [Google Scholar] [CrossRef]
  31. Chatzopoulou, I. 2022. Virtual Τourism/Virtual Reality and Technology Use: Applications and Implications for Religious and Pilgrimage Tourism. The Case of Greece. In Transcending Borders in Tourism Through Innovation and Cultural Heritage. Edited by V. Katsoni and A. Claudia. Berlin and Heidelberg: Springer, pp. 1021–36. [Google Scholar]
  32. Chauhan, U., and A. Shah. 2021. Topic Modeling Using Latent Dirichlet allocation: A Survey. ACM Computing Surveys 54: 1–35. [Google Scholar] [CrossRef]
  33. Chen, X., and Z. Ibrahim. 2023. A Comprehensive Study of Emotional Responses in AI-Enhanced Interactive Installation Art. Sustainability 15: 15830. [Google Scholar] [CrossRef]
  34. Chen, Z. 2023. Ethics and discrimination in artificial intelligence-enabled recruitment practices. Humanities and Social Sciences Communications 10: 567. [Google Scholar] [CrossRef]
  35. Cheong, P. H. 2020. Religion, Robots and Rectitude: Communicative Affordances for Spiritual Knowledge and Community. Applied Artificial Intelligence 34: 412–31. [Google Scholar] [CrossRef]
  36. Cheong, P. H. 2021. Bounded Religious Automation at Work: Communicating Human Authority in Artificial Intelligence Networks. Journal of Communication Inquiry 45: 5–23. [Google Scholar] [CrossRef]
  37. Chubb, J. 2022. Speeding up to keep up: Exploring the use of AI in the research process. AI & Society 37: 1439–57. [Google Scholar]
  38. Citlak, A. 2021. Psychology of religion in the theories and research of the Lvov-Warsaw School (basic achievements and developments). Archive for the Psychology of Religion 43: 95–116. [Google Scholar] [CrossRef]
  39. Claisse, C., and A. C. Durrant. 2023. ‘Keeping our Faith Alive’: Investigating Buddhism Practice during COVID-19 to Inform Design for the Online Community Practice of Faith. In Paper presented at the CHI ‘23: Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, Hamburg, Germany, April 23–28; pp. 1–19. [Google Scholar]
  40. Collins, C. S., and C. M. Stockton. 2018. The Central Role of Theory in Qualitative Research. International Journal of Qualitative Methods 17: 1609406918797475. [Google Scholar] [CrossRef]
  41. Connors, M. H., and P. W. Halligan. 2022. Revealing the Cognitive Neuroscience of Belief. Frontiers in Behavioral Neuroscience 16: 926742. [Google Scholar] [CrossRef] [PubMed]
  42. Cormie, L. F. 2020. Artificial Intelligence: Challenges and Possibilities for Theology and Ethics. Toronto Journal of Theology 36: 75–77. [Google Scholar] [CrossRef]
  43. Dawson, C. L. 2023. The Intersection of Technology and Faith: Exploring AI through a Biblical Lens. Linkedin. July 15. Available online: https://www.linkedin.com/pulse/intersection-technology-faith-exploring-ai-through-biblical-givens/ (accessed on 12 August 2023).
  44. DeBono, A., D. Poepsel, and N. Corley. 2020. Thank God for My Successes (Not My Failures): Feeling God’s Presence Explains a God Attribution Bias. Psychological Reports 123: 1663–87. [Google Scholar] [CrossRef]
  45. Dein, S. 2020. Transcendence, religion and social bonding. Archive for the Psychology of Religion 42: 77–88. [Google Scholar] [CrossRef]
  46. Dingler, T., D. Kwasnicka, J. Wei, E. Gong, and B. Oldenburg. 2021. The Use and Promise of Conversational Agents in Digital Health. Yearbook of Medical Informatics 30: 191–99. [Google Scholar] [CrossRef]
  47. Dixon, T. H., J. L. Maynard, M. Mildenberger, M. Milkoreit, S. J. Mock, S. Quilley, Tobias Schröder, and P. Thagard. 2013. A Complex Systems Approach to the Study of Ideology: Cognitive-Affective Structures and the Dynamics of Belief Systems. Journal of Social and Political Psychology 1: 337–63. [Google Scholar]
  48. Dorobantu, M. 2022. Artificial Intelligence As a Testing Ground for Key Theological Questions. Journal of Religion & Science 57: 984–99. [Google Scholar]
  49. Dowd, R. A. 2015. The Role of Religious Leaders. In Christianity, Islam, and Liberal Democracy: Lessons from Sub-Saharan Africa Christianity, Islam, and Liberal Democracy: Lessons from Sub-Saharan Africa. Oxford: Oxford University Press, pp. 49–79. [Google Scholar]
  50. Dwivedi, D. 2023. Algorithmic Bias: A Challenge for Ethical Artificial Intelligence (AI). In Immersive Technology and Experiences. Edited by G. S. Heggde. Berlin and Heidelberg: Springer Nature, pp. 65–82. [Google Scholar]
  51. Dwivedi, Y. K., A. Sharma, N. P. Rana, M. Giannakis, P. Goel, and V. Dutot. 2023a. Evolution of artificial intelligence research in Technological Forecasting and Social Change: Research topics, trends, and future directions. Technological Forecasting and Social Change 192: 122579. [Google Scholar] [CrossRef]
  52. Dwivedi, Y. K., N. Kshetri, L. Hughes, E. L. Slade, A. K. Kar, A. M. Baabdullah, Alex Koohang, Vishnupriya Raghavan, Manju Ahuja, Hanaa Albanna, and et al. 2023b. Opinion Paper: “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management 71: 102642. [Google Scholar] [CrossRef]
  53. Ecker, U. K., S. Lewandowsky, J. Cook, P. Schmid, L. K. Fazio, N. Brashier, Panayiota Kendeou, Emily K. Vraga, and M. A. Amazeen. 2022. The psychological drivers of misinformation belief and its resistance to correction. Nature Reviews Psychology 1: 13–29. [Google Scholar] [CrossRef]
  54. Elmahjub, E. 2023. Artificial Intelligence (AI) in Islamic Ethics: Towards Pluralist Ethical Benchmarking for AI. Philosophy & Technology 36: 73. [Google Scholar]
  55. Elster, C. A. 2003. Authority, Performance, and Interpretation in Religious Reading: Critical Issues of Intercultural Communication and Multiple Literacies. Journal of Literacy Research 35: 663–92. [Google Scholar] [CrossRef]
  56. Epley, N., and T. Gilovich. 2006. The Anchoring-and-Adjustment Heuristic: Why the Adjustments Are Insufficient. Psychological Science 17: 311–18. [Google Scholar] [CrossRef]
  57. Epstein, S. 1985. The Implications of Cognitive-experiential Self-theory for Research in Social Psychology and Personality. Journal for the Theory of Social Behaviour 15: 283–310. [Google Scholar] [CrossRef]
  58. Evans, M. T. 2003. The Sacred: Differentiating, Clarifying and Extending Concepts. Review of Religious Research 45: 32–47. [Google Scholar] [CrossRef]
  59. Findlay, M., and W. Wong. 2021. Trust and Regulation: An Analysis of Emotion. Available online: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3857447 (accessed on 12 August 2023).
  60. Flannery, K. A., and R. Walles. 2003. How does schema theory apply to real versus virtual memories? Cyberpsychology & Behavior: The Impact of the Internet, Multimedia and Virtual Reality on Behavior and Society 6: 151–59. [Google Scholar]
  61. Frith, C. D. 2008. Social cognition. Biological Sciences 363: 2033–39. [Google Scholar] [CrossRef]
  62. Fu, R., Y. Huang, and P. V. Singh. 2020. AI and Algorithmic Bias: Source, Detection, Mitigation and Implications. July 26. Available online: https://ssrn.com/abstract=3681517 (accessed on 12 August 2023).
  63. Furst, J. 2021. God and Robots: Will AI Transform Religion?—BBC News. Youtube. October 23. Available online: https://youtu.be/JE85PTDXARM?feature=shared (accessed on 12 August 2023).
  64. Gabriel, I. 2020. Artificial Intelligence, Values, and Alignment. Minds and Machines 30: 411–37. [Google Scholar] [CrossRef]
  65. Gagliardi, L. 2023. The role of cognitive biases in conspiracybeliefs: A literature review. Journal of Economic Surveys, 1–34. [Google Scholar]
  66. Galesic, M., H. Olsson, J. Dalege, T. V. Does, and D. L. Stein. 2021. Integrating social and cognitive aspects of belief dynamics: Towards a unifying framework. Journal of The Royal Society Interface 18: 20200857. [Google Scholar] [CrossRef]
  67. Gattal, A., C. Djeddi, F. Abbas, I. Siddiqi, and B. Bouderah. 2023. A new method for writer identification based on historical documents. Journal of Intelligent Systems 32: 2–12. [Google Scholar] [CrossRef]
  68. Geraci, R. M. 2008. Apocalyptic AI: Religion and the Promise of Artificial Intelligence. Journal of the American Academy of Religion 76: 138–66. [Google Scholar] [CrossRef]
  69. Gerlich, M. 2023. Perceptions and Acceptance of Artificial Intelligence: A Multi-Dimensional Study. Social Sciences 12: 502. [Google Scholar] [CrossRef]
  70. Gibney, E. 2022. Open-Source Language AI Challenges Big Tech’s Models. Nature. June 22. Available online: https://www.nature.com/articles/d41586-022-01705-z (accessed on 12 August 2023).
  71. Gill, A. J., S. H. Krapels, T. Blanke, J. Grant, M. Hedges, and S. Tanner. 2017. Insight workflow: Systematically combining human and computational methods to explore textual data. Journal of the Association for Information Science and Technology 68: 1671–86. [Google Scholar] [CrossRef]
  72. Głaz, S. 2021. Psychological Analysis of Religious Experience: The Construction of the Intensity of Religious Experience Scale (IRES). Journal of Religion and Health 60: 576–95. [Google Scholar] [CrossRef]
  73. Goyal, A., V. Gupta, and M. Kumar. 2018. Recent Named Entity Recognition and Classification techniques: A systematic review. Computer Science Review 29: 21–43. [Google Scholar] [CrossRef]
  74. Grafman, J., I. Cristofori, W. Zhong, and J. Bulbulia. 2020. The Neural Basis of Religious Cognition. Current Directions in Psychological Science 29: 126–33. [Google Scholar] [CrossRef]
  75. Grassini, S. 2023. Shaping the Future of Education: Exploring the Potential and Consequences of AI and ChatGPT in Educational Settings. Education Sciences 13: 692. [Google Scholar] [CrossRef]
  76. Graves, M. 2021. Emergent Models for Moral AI Spirituality. Special Issue on Artificial Intelligence, Spirituality and Analogue Thinking 7: 7–15. [Google Scholar]
  77. Graves, M. 2023. What Does it Mean to Consider AI a Person? Theology and Science 21: 348–53. [Google Scholar] [CrossRef]
  78. Gretchen, H. 2022. Righteous AI: The Christian Voice in the Ethical AI Conversation. digital.lib.washington—University of Washington. Available online: http://hdl.handle.net/1773/48925 (accessed on 12 August 2023).
  79. Guendelman, S., S. Medeiros, and H. Rampes. 2017. Mindfulness and Emotion Regulation: Insights from Neurobiological, Psychological, and Clinical Studies. Frontiers in Psychology 8: 220. [Google Scholar] [CrossRef]
  80. Gunawan, F. 2022. The ideology of translators in Quranic translation: Lessons learned from Indonesia. Cogent Arts & Humanities 9: 2088438. [Google Scholar]
  81. Harris, S., J. T. Kaplan, A. Curiel, S. Y. Bookheimer, M. Iacoboni, and M. S. Cohen. 2009. The Neural Correlates of Religious and Nonreligious Belief. PLoS ONE 4: e7272. [Google Scholar] [CrossRef]
  82. Harrison, V. S. 2007. Metaphor, Religious Language, and Religious Experience. Sophia 46: 127–45. [Google Scholar] [CrossRef]
  83. Hassan, S. U., J. Ahamed, and K. Ahmad. 2022. Analytics of machine learning-based algorithms for text classification. Sustainable Operations and Computers 3: 238–48. [Google Scholar] [CrossRef]
  84. Hassani, H., C. Beneki, S. Unger, M. T. Mazinani, and M. R. Yeganegi. 2020. Text Mining in Big Data Analytics. Big Data and Cognitive Computing 4: 1. [Google Scholar] [CrossRef]
  85. Héliot, Y., I. H. Gleibs, A. Coyle, D. M. Rousseau, and C. Rojon. 2019. Religious identity in the workplace: A systematic review, research agenda, and practical implications. Human Resource Managment 59: 153–73. [Google Scholar] [CrossRef]
  86. Henderson, A. K., K. M. Walsemann, and J. A. Ailshire. 2022. Religious Involvement and Cognitive Functioning at the Intersection of Race–Ethnicity and Gender Among Midlife and Older Adults. Journals of Gerontology. Series B, Psychological Sciences and Social Sciences 77: 237–48. [Google Scholar] [CrossRef]
  87. Hermans, C. A. 2015. Towards a Theory of Spiritual and Religious Experiences: A Building Block Approach of the Unexpected Possible. Archive for the Psychology of Religion 37: 141–67. [Google Scholar] [CrossRef]
  88. Hewitt, M. 2012. Affective and Cognitive Dimensions of Religious Experience: Toward a Conceptual/Theoretical Integrative Perspective. Studies in Religion/Sciences Religieuses 41: 33–45. [Google Scholar] [CrossRef]
  89. Hitch, D. 2023. Artificial Intelligence Augmented Qualitative Analysis: The Way of the Future? Qualitative Health Research, 1–12. [Google Scholar] [CrossRef]
  90. Hobson, N. M., J. Schroeder, J. L. Risen, D. Xygalatas, and M. Inzlicht. 2018. The Psychology of Rituals: An Integrative Review and Process-Based Framework. Personality and Social Psychology Review 22: 260–84. [Google Scholar] [CrossRef]
  91. Huang, C., Z. Zhang, B. Mao, and X. Yao. 2023. An Overview of Artificial Intelligence Ethics. IEEE Transactions on Artificial Intelligence 4: 799–819. [Google Scholar] [CrossRef]
  92. Humerick, M. 2018. Taking AI Personally: How the E.U. Must Learn to Balance the Interests of Personal Data Privacy & Artificial Intelligence. Santa Clara High Technology Law journal 34: 393–418. [Google Scholar]
  93. Jackson, J. C., J. Watts, J.-M. List, C. Puryear, R. Drabble, and K. A. Lindquist. 2022. From Text to Thought: How Analyzing Language Can Advance Psychological Science. Perspectives on Psychological Science 17: 805–26. [Google Scholar] [CrossRef]
  94. Jackson, J. C., K. C. Yam, P. M. Tang, C. G. Sibley, and A. Waytz. 2023. Exposure to automation explains religious declines. Proceedings of the National Academy of Sciences of the United States of America 120: e2304748120. [Google Scholar] [CrossRef]
  95. Jarrahi, M. H. 2018. Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making. Business Horizons 61: 577–86. [Google Scholar] [CrossRef]
  96. Johns, M. D. 2021. Ethics issues in the study of religion and new media. In Digital Religion: Understanding Religious Practice in Digital Media. Edited by H. A. Campbell and R. Tsuria. Oxfordshire: Routledge, pp. 250–65. [Google Scholar]
  97. Johnston, E. F. 2022. Introduction: Interpretive Approaches in the Study of Religion. In Interpreting Religion: Making Sense of Religious Lives Interpreting Religion: Making Sense of Religious Lives. Edited by E. Johnston and V. Singh. Bristol: Policy Press, pp. 1–18. [Google Scholar]
  98. Josselson, R. 2004. The hermeneutics of faith and the hermeneutics of suspicion. Narrative Inquiry 14: 1–28. [Google Scholar] [CrossRef]
  99. Jungherr, A. 2023. Artificial Intelligence and Democracy: A Conceptual Framework. Social Media + Society 9: 2–10. [Google Scholar] [CrossRef]
  100. Kaddour, J., J. Harris, M. Mozes, H. Bradley, R. Raileanu, and R. McHardy. 2023. Challenges and Applications of Large Language Models. Computation and Language 1: 1–72. [Google Scholar]
  101. Kang, Y., Z. Cai, C.-W. Tan, Q. Huang, and H. Liu. 2020. Natural language processing (NLP) in management research: A literature review. Journal of Management Analytics 7: 139–72. [Google Scholar] [CrossRef]
  102. Kapogiannis, D., A. K. Barbey, M. Su, G. Zamboni, F. Krueger, and J. Grafman. 2009. Cognitive and neural foundations of religious belief. Pans 106: 4876–81. [Google Scholar] [CrossRef]
  103. Karataş, M., and K. M. Cutright. 2023. Thinking about God increases acceptance of artificial intelligence in decision-making. Proceedings of the National Academy of Sciences of the United States of America 120: e2218961120. [Google Scholar] [CrossRef]
  104. Kéri, S. 2023. Autism and Religion. Children 10: 2–16. [Google Scholar] [CrossRef]
  105. Khurana, D., A. Koli, K. Khatter, and S. Singh. 2023. Natural language processing: State of the art, current trends and challenges. Multimedia Tools and Applications 82: 3713–44. [Google Scholar] [CrossRef]
  106. Kim, J., H. Lee, and Y. H. Cho. 2022. Learning design to support student-AI collaboration: Perspectives of leading teachers for AI in education. Education and Information Technologies 27: 6069–104. [Google Scholar] [CrossRef]
  107. Kime, K. G., and J. R. Snarey. 2018. A Jamesian Response to Reductionism in the Neuropsychology of Religious Experience. Archive for the Psychology of Religion 40: 307–25. [Google Scholar] [CrossRef]
  108. Koehler, A. A., S. D. Cochran, V. M. Mays, K.-W. Chang, and J. G. Foster. 2020. Integrating topic modeling and word embedding to characterize violent deaths. Proceedings of the National Academy of Sciences of the United States of America 119: e2108801119. [Google Scholar] [CrossRef] [PubMed]
  109. Koehrsen, J. 2021. A field perspective on sustainability transitions: The case of religious organizations. Environmental Innovation and Societal Transitions 40: 408–20. [Google Scholar] [CrossRef]
  110. Korteling, J. E., A.-M. Brouwer, and A. Toet. 2018. A Neural Network Framework for Cognitive Bias. Frontiers in Psychology 9: 1561. [Google Scholar] [CrossRef] [PubMed]
  111. Koubaa, A., A. Ammar, B. Benjdira, A. Al-Hadid, B. Kawaf, S. A. Al-Yahri, Abdelrahman Babiker, Koutaiba Assaf, and M. B. Ras. 2020. Activity Monitoring of Islamic Prayer (Salat) Postures using Deep Learning. Paper presented at 2020 6th Conference on Data Science and Machine Learning Applications (CDMA), Riyadh, Saudi Arabia, March 4–5; Piscataway: IEEE, pp. 106–11. [Google Scholar]
  112. Krause, N. M. 2007. Social Involvement in Religious Institutions and God-Mediated Control Beliefs: A Longitudinal Investigation. Journal for the Scientific Study of Religion 46: 519–37. [Google Scholar] [CrossRef] [PubMed]
  113. Krishna, A., and F. Strack. 2017. Reflection and Impulse as Determinants of Human Behavior. Knowledge and Action 9: 145–67. [Google Scholar]
  114. Krokcorresponding, D. 2015. The Role of Meaning in Life Within the Relations of Religious Coping and Psychological Well-Being. Journal of Religion and Health 54: 2292–308. [Google Scholar]
  115. Laitinen, A., and O. Sahlgren. 2021. AI Systems and Respect for Human Autonomy. Frontiers in Artificial Intelligence 4: 151. [Google Scholar] [CrossRef]
  116. Lane, J. E. 2021. Understanding Religion Through Artificial Intelligence: Bonding and Belief. London, UK: Bloomsbury Publishing. [Google Scholar]
  117. Lane, J. E., and F. L. Shults. 2021. The Computational Science of Religion. Journal for the Cognitive Science of Religion 6: 191–208. [Google Scholar] [CrossRef]
  118. Larsson, S. 2019. The Socio-Legal Relevance of Artificial Intelligence. Droit et Société 103: 573–93. [Google Scholar] [CrossRef]
  119. Lazzarino, R. 2023. Earbuds, smartphones, and music. Spiritual care and existential changes in COVID-19 times. Social Theory & Health 21: 247–66. [Google Scholar]
  120. Leeuwen, N. V., and M. V. Elk. 2019. Seeking the supernatural: The Interactive Religious Experience Model. Religion, Brain & Behavior 9: 221–51. [Google Scholar]
  121. Leite, Â, B. Nobre, and P. Dias. 2023. Religious identity, religious practice, and religious beliefs across countries and world regions. Archive for the Psychology of Religion 45: 107–132. [Google Scholar] [CrossRef]
  122. Leo, D., Z. Izadikhah, E. C. Fein, and S. A. Forooshani. 2021. The Effect of Trauma on Religious Beliefs: A Structured Literature Review and Meta-Analysis. Trauma, Violence, & Abuse 22: 161–75. [Google Scholar]
  123. Lewandowsky, S., U. K. Ecker, C. M. Seifert, N. Schwarz, and J. Cook. 2012. Misinformation and Its Correction: Continued Influence and Successful Debiasing. Psychological Science in the Public Interest 13: 106–31. [Google Scholar] [CrossRef] [PubMed]
  124. Li, X., H. Xiong, X. Li, X. Wu, X. Zhang, J. Liu, Jiang Bian, and D. Dou. 2022. Interpretable deep learning: Interpretation, interpretability, trustworthiness, and beyond. Knowledge and Information Systems 64: 3197–234. [Google Scholar] [CrossRef]
  125. Lizardo, O. 2023. An Analytical Approach to Culture. Philosophy of the Social Sciences 53: 281–302. [Google Scholar] [CrossRef]
  126. Long, T. E., and J. K. Hadden. 1983. Religious Conversion and the Concept of Socialization: Integrating the Brainwashing and Drift Models. Journal for the Scientific Study of Religion 22: 1–14. [Google Scholar] [CrossRef]
  127. Lukyanenko, R., W. Maass, and V. C. Storey. 2022. Trust in artificial intelligence: From a Foundational Trust Framework to emerging research opportunities. Electronic Markets 32: 1993–2020. [Google Scholar] [CrossRef]
  128. Macagno, F., and L. Salvato. 2023. Argumentation and the interpretation of religious texts. Journal of Argumentation in Context 12: 2–18. [Google Scholar] [CrossRef]
  129. Maedche, A., C. Legner, A. Benlian, B. Berger, H. Gimpel, T. Hess, Oliver Hinz, Stefan Morana, and M. Söllner. 2019. AI-Based Digital Assistants. Business & Information Systems Engineering 61: 535–44. [Google Scholar]
  130. Mah, P. M., I. Skalna, and J. Muzam. 2022. Natural Language Processing and Artificial Intelligence for Enterprise Management in the Era of Industry 4.0. Applied Sciences 12: 9207. [Google Scholar] [CrossRef]
  131. Mann, J. L. 2019. Augmented Reality, Virtual Reality, and Religion: Recent Developments and Their Significance. In Believing in Bits: Digital Media and the Supernatural Believing in Bits: Digital Media and the Supernatural. New York: Oxford Academic, pp. 195–212. [Google Scholar]
  132. McClelland, J. L. 2009. The Place of Modeling in Cognitive Science. Topics in Cognitive Science 1: 11–38. [Google Scholar] [CrossRef] [PubMed]
  133. McLoughlin, I., and N. Indurkhya. 2023. AI, Human–Robot Interaction, and Natural Language Processing. In The Cambridge Handbook of Language in Context. Edited by J. Romero-Trillo. Cambridge: Cambridge University Press. [Google Scholar]
  134. Meintel, D. 2021. Religious Authenticity and Commitment. Studies in Religion/Sciences Religieuses 50: 8–26. [Google Scholar] [CrossRef]
  135. Miltiadis, P., D. Maria, S. Eleni, and S. Dimitrios. 2017. Religiosity: Development of religious cognitive schemas and religious faith. International Journal of Research Studies in Psychology 6: 73–83. [Google Scholar]
  136. Moriuchi, E., V. M. Landers, D. Colton, and N. Hair. 2021. Engagement with chatbots versus augmented reality interactive technology in e-commerce. Journal of Strategic Marketing 29: 375–89. [Google Scholar] [CrossRef]
  137. Mulukom, V. V., and M. Lang. 2021. Religious Experiences Are Interpreted through Priors from Cultural Frameworks Supported by Imaginative Capacity Rather Than Special Cognition. Journal for the Cognitive Science of Religion 7: 39–53. [Google Scholar] [CrossRef]
  138. Nandwani, P., and R. Verma. 2021. A review on sentiment analysis and emotion detection from text. Social Network Analysis And Mining 11: 1–19. [Google Scholar] [CrossRef]
  139. Nath, S., U. Das, and D. Ghosh. 2023. A Religious Sentiment Detector Based on Machine Learning to Provide Meaningful Analysis of Religious Texts. In Computational Intelligence in Communications and Business Analytics. Edited by K. Dasgupta, S. Mukhopadhyay, J. K. Mandal and P. Dutta. Berlin and Heidelberg: Springer, pp. 165–84. [Google Scholar]
  140. Nielbo, K. L., D. M. Braxton, and A. Upal. 2012. Computing Religion: A New Tool in the Multilevel Analysis of Religion. Method & Theory in the Study of Religion 24: 267–90. [Google Scholar]
  141. Nieminen, P., J. Loikkanen, E. Ryökäs, and A.-M. Mustonen. 2020. Nature of Evidence in Religion and Natural Science. Theology and Science 18: 448–74. [Google Scholar] [CrossRef]
  142. Nishant, R., D. Schneckenberg, and M. Ravishankar. 2023. The formal rationality of artificial intelligence-based algorithms and the problem of bias. Journal of Information Technology, 1–22. [Google Scholar] [CrossRef]
  143. Novelli, C. 2023. Accountability in artificial intelligence: What it is and how it works. AI & Society, 1–12. [Google Scholar]
  144. Nowell, L. S., J. M. Norris, D. E. White, and N. J. Moules. 2017. Thematic Analysis: Striving to Meet the Trustworthiness Criteria. International Journal of Qualitative Methods 16: 1609406917733847. [Google Scholar] [CrossRef]
  145. Olsher, D. J. 2015. New Artificial Intelligence Tools for Deep Conflict Resolution and Humanitarian Response. Procedia Engineering 107: 282–92. [Google Scholar] [CrossRef]
  146. Orlandi, L. B., V. Febo, and S. Perdichizzi. 2022. The role of religiosity in product and technology acceptance: Evidence from COVID-19 vaccines. Technological Forecasting and Social Change 185: 2–10. [Google Scholar]
  147. Ozorak, E. W. 1989. Social and Cognitive Influences on the Development of Religious Beliefs and Commitment in Adolescence. Journal for the Scientific Study of Religion 28: 448–63. [Google Scholar] [CrossRef]
  148. Park, D., G. Lee, W. G. Kim, and T. T. Kim. 2019. Social Network Analysis as a Valuable Tool for Understanding Tourists’ Multi-Attraction Travel Behavioral Intention to Revisit and Recommend. Sustainability 11: 2497. [Google Scholar] [CrossRef]
  149. Partarakis, N., and X. Zabulis. 2024. A Review of Immersive Technologies, Knowledge Representation, and AI for Human-Centered Digital Experiences. Electronics 13: 269. [Google Scholar] [CrossRef]
  150. Peters, U. 2022. What Is the Function of Confirmation Bias? Erkenntnis 87: 1351–76. [Google Scholar] [CrossRef]
  151. Pietroni, E., and D. Ferdani. 2021. Virtual Restoration and Virtual Reconstruction in Cultural Heritage: Terminology, Methodologies, Visual Representation Techniques and Cognitive Models. Information 12: 167. [Google Scholar] [CrossRef]
  152. Pozzo, B. 2020. Fashion between Inspiration and Appropriation. Laws 9: 5. [Google Scholar] [CrossRef]
  153. Puzio, A. 2023. Robot, let us pray! Can and should robots have religious functions? An ethical exploration of religious robots. AI & Society, 1–17. [Google Scholar]
  154. Quaquebeke, N. V., and F. H. Gerpott. 2023. The Now, New, and Next of Digital Leadership: How Artificial Intelligence (AI) Will Take Over and Change Leadership as We Know It. Journal of Leadership & Organizational Studies 30: 265–75. [Google Scholar]
  155. Raghav, Y. Y., and S. Gulia. 2023. The Rise of Artificial Intelligence and Its Implications on Spirituality. In Investigating the Impact of AI on Ethics and Spirituality. Edited by S. Chakraborty. Hershey: IGI Global, pp. 14–15. [Google Scholar]
  156. Rähme, Boris. 2021. Artificial intelligence and religion: Between existing ai and grand narratives. Material Religion 17: 547–49. [Google Scholar] [CrossRef]
  157. Raquib, A., B. Channa, T. Zubair, and J. Qadir. 2022. Islamic virtue-based ethics for artificial intelligence. Discover Artificial Intelligence 2: 1–16. [Google Scholar] [CrossRef]
  158. Raue, M., and S. G. Scholl. 2018. The Use of Heuristics in Decision Making Under Risk and Uncertainty. Psychological Perspectives on Risk and Risk Analysis, 153–79. [Google Scholar]
  159. Redondo, T., and A. M. Sandoval. 2016. Text Analytics: The convergence of Big Data and Artificial Intelligence. International Journal of Interactive Multimedia and Artificial Intelligence 3: 57–64. [Google Scholar]
  160. Reed, R. 2021. A.I. in Religion, A.I. for Religion, A.I. and Religion: Towards a Theory of Religious Studies and Artificial Intelligence. Religions 12: 401. [Google Scholar] [CrossRef]
  161. Robinson, S. C. 2020. Trust, transparency, and openness: How inclusion of cultural values shapes Nordic national public policy strategies for artificial intelligence (AI). Technology in Society 63: 101421. [Google Scholar] [CrossRef]
  162. Rochat, P. 2023. The Evolution of Developmental Theories Since Piaget: A Metaview. Perspectives on Psychological Science, 1–10. [Google Scholar] [CrossRef] [PubMed]
  163. Rodrigues, R. 2020. Legal and human rights issues of AI: Gaps, challenges and vulnerabilities. Journal of Responsible Technology 4: 100005. [Google Scholar] [CrossRef]
  164. Rodríguez, N. D., A. D. Ser, M. Coeckelbergh, M. L. Prado, E. H. Viedma, and F. Herrera. 2023. Connecting the dots in trustworthy Artificial Intelligence: From AI principles, ethics, and key requirements to responsible AI systems and regulation. Information Fusion 99: 101896. [Google Scholar] [CrossRef]
  165. Rovenpor, D. R., and L. M. Isbell. 2018. Do emotional control beliefs lead people to approach positive or negative situations? Two competing effects of control beliefs on emotional situation selection. Emotion 18: 313–31. [Google Scholar] [CrossRef] [PubMed]
  166. Ryan, M., and B. C. Stahl. 2020. Artificial Intelligence Ethics Guidelines for Developers and Users: Clarifying Their Content and Normative Implications. Emerald. June 9. Available online: https://www.emerald.com/insight/content/doi/10.1108/JICES-12–2019-0138/full/html (accessed on 12 August 2023).
  167. Salvadore, S. V. 2023. Exploring the Ethical Dimensions of Using ChatGPT in Language Learning and Beyond. Languages 8: 191. [Google Scholar] [CrossRef]
  168. Sameera, A., and A. Khadijah. 2023. Young, Black, Muslim American: An intersectional lens to understanding emerging adult religious experiences. Psychology of Religion and Spirituality 15: 319–29. [Google Scholar]
  169. Santos, L. B., O. Nizam, A. Israel, C. L. de Nunes, and S. I. Frango. 2023. Use of artificial intelligence in biblical citation recommendations in the New Testament. Revista Científica Multidisciplinar Núcleo do Conhecimen 2: 123–43. [Google Scholar]
  170. Scavarelli, A., A. Arya, and R. J. Teather. 2021. Virtual reality and augmented reality in social learning spaces: A literature review. Virtual Reality 25: 57–277. [Google Scholar] [CrossRef]
  171. Schippers, M. C. 2019. Life Crafting as a Way to Find Purpose and Meaning in Life. Frontiers in Psychology 10: 2778. [Google Scholar] [CrossRef] [PubMed]
  172. Seitz, R. J., and H.-F. Angel. 2020. Belief formation—A driving force for brain evolution. Brain and Cognition 140: 105548. [Google Scholar] [CrossRef] [PubMed]
  173. Sezgin, E. 2023. Artificial intelligence in healthcare: Complementing, not replacing, doctors and healthcare providers. Digit Health 9: 20552076231186520. [Google Scholar] [CrossRef]
  174. Shadiev, R., T.-T. Wu, A. Sun, and Y.-M. Huang. 2018. Applications of speech-to-text recognition and computer-aided translation for facilitating cross-cultural learning through a learning activity: Issues and their solutions. Educational Technology Research and Development 66: 191–214. [Google Scholar] [CrossRef]
  175. Shults, L. F. 2019. Computer Modeling in Philosophy of Religion. Open Philosophy 2: 108–25. [Google Scholar] [CrossRef]
  176. Shults, L. F., and W. J. Wildman. 2020. Human Simulation and Sustainability: Ontological, Epistemological, and Ethical Reflections. Sustainability 12: 10039. [Google Scholar] [CrossRef]
  177. Siapka, A. 2018. The Ethical and Legal Challenges of Artificial Intelligence: The EU Response to Biased and Discriminatory AI. December 11. Available online: https://ssrn.com/abstract=3408773 (accessed on 12 August 2023).
  178. Singler, B. 2020. The AI Creation Meme: A Case Study of the New Visibility of Religion in Artificial Intelligence Discourse. Religions 11: 253. [Google Scholar] [CrossRef]
  179. Sosis, R. 2020. Four advantages of a systemic approach to the study of religion. Archive for the Psychology of Religion 42: 142–57. [Google Scholar] [CrossRef]
  180. Spennemann, D. H. 2023. ChatGPT and the Generation of Digitally Born “Knowledge”: How Does a Generative AI Language Model Interpret Cultural Heritage Values? Knowledge 3: 480–512. [Google Scholar] [CrossRef]
  181. Spilka, B., P. Shaver, and L. A. Kirkpatrick. 1985. A General Attribution Theory for the Psychology of Religion. Journal for the Scientific Study of Religion 24: 1–20. [Google Scholar] [CrossRef]
  182. Stahl, B. C. 2022. Organisational responses to the ethical issues of artificial intelligence. AI & Society 37: 23–37. [Google Scholar]
  183. Stahl, B. C., D. Schroeder, and R. Rowena. 2023. Ethics of Artificial Intelligence Case Studies and Options for Addressing Ethical Challenges. In SpringerBriefs in Research and Innovation Governance. Edited by D. Schroeder and K. Iatridis. Lancashire: Springer, p. 121. [Google Scholar]
  184. Stahl, B. C., R. Rodrigues, N. Santiago, and K. Macnish. 2022. A European Agency for Artificial Intelligence: Protecting fundamental rights and ethical values. Computer Law & Security Review 45: 105661. [Google Scholar]
  185. Stahl, H. A. 2022. Relationships, Religion and Robotics: The Soul and the Ethical Implications of AI. The University of Sydney. Available online: https://hdl.handle.net/2123/28850 (accessed on 12 August 2023).
  186. Steyvers, M., and A. Kumar. 2023. Three Challenges for AI-Assisted Decision-Making. Perspectives on Psychological Science, 1–13. [Google Scholar] [CrossRef]
  187. Sugiura, M., R. J. Seitz, and H.-F. Angel. 2015. Models and Neural Bases of the Believing Process. Journal of Behavioral and Brain Science 5: 12–23. [Google Scholar] [CrossRef]
  188. Susanto, M. A., S. Y. Sudikan, A. Ahmadi, and N. Afdholy. 2023. Unveiling the Narrative Strategies of World Religious Literature: An In-Depth Exploration. International Journal of Multicultural and Multireligious Understanding 10: 213–21. [Google Scholar] [CrossRef]
  189. Taggart, T., N. Gottfredson, W. Powell, S. Ennett, L. M. Chatters, L. C. Edward, and E. Eng. 2018. The Role of Religious Socialization and Religiosity in African American and Caribbean Black Adolescents’ Sexual Initiation. Journal of Religion and Health 57: 1889–904. [Google Scholar] [CrossRef]
  190. Taherdoost, H., and M. Madanchian. 2023. Artificial Intelligence and Sentiment Analysis: A Review in Competitive Research. Computers 12: 37. [Google Scholar] [CrossRef]
  191. Tan, C. 2020. Digital Confucius? Exploring the implications of artificial intelligence in spiritual education. Connection Science 32: 280–91. [Google Scholar] [CrossRef]
  192. Taves, A., and E. Asprem. 2017. Experience as event: Event cognition and the study of (religious) experiences. Religion, Brain & Behavior 7: 43–62. [Google Scholar]
  193. Thiruchselvam, R., Y. Gopi, L. Kilekwang, J. Harper, and J. J. Gross. 2017. In God we trust? Neural measures reveal lower social conformity among non-religious individuals. Social Cognitive and Affective Neuroscience 12: 956–64. [Google Scholar] [CrossRef]
  194. Tolly, J. 2023. Cognitive Science of Religion, Reliability, and Perceiving God. Theology and Science 21: 520–43. [Google Scholar] [CrossRef]
  195. Torregrosa, J., G. B. Orgaz, E. M. Cámara, J. D. Ser, and D. Camacho. 2023. A survey on extremism analysis using natural language processing: Definitions, literature review, trends and challenges. Journal of Ambient Intelligence and Humanized Computing 14: 9869–905. [Google Scholar] [CrossRef]
  196. Trotta, A. 2023. The future of ethics in AI: Challenges and opportunities. AI & Society 38: 439–41. [Google Scholar]
  197. Truby, J. 2020. Governing Artificial Intelligence to benefit the UN Sustainable Development Goals. Sustainable Development 28: 946–59. [Google Scholar] [CrossRef]
  198. Turini, S. 2023. Binary Testament: An Interdisciplinary Analysis of the A.I. Bible—Unveiling the Quantum Tapestry of Digital Divinity. Qeios. December 21. Available online: https://www.qeios.com/read/TREZ58 (accessed on 12 August 2023).
  199. Umbrello, S. 2023. The Intersection of Bernard Lonergan’s Critical Realism, the Common Good, and Artificial Intelligence in Modern Religious Practices. Religions 14: 1536. [Google Scholar] [CrossRef]
  200. Uysal, A. K., and S. Gunal. 2014. The impact of preprocessing on text classification. Information Processing & Management 50: 104–12. [Google Scholar]
  201. Van, C. P. 2017. Rethinking self-transcendent positive emotions and religion: Insights from psychological and biblical research. Psychology of Religion and Spirituality 9: 254–63. [Google Scholar]
  202. Vang, Z. M., F. Hou, and K. Elder. 2019. Perceived Religious Discrimination, Religiosity, and Life Satisfaction. Journal of Happiness Studies 20: 1913–32. [Google Scholar] [CrossRef]
  203. Varona, D., and J. L. Suárez. 2022. Discrimination, Bias, Fairness, and Trustworthy AI. Applied Sciences 12: 5826. [Google Scholar] [CrossRef]
  204. Varsha, P. S. 2023. How can we manage biases in artificial intelligence systems—A systematic literature review. International Journal of Information Management Data Insights 3: 100165. [Google Scholar]
  205. Verma, M. 2017. Lexical Analysis of Religious Texts using Text Mining and Machine Learning Tools. International Journal of Computer Applications 168: 2017. [Google Scholar] [CrossRef]
  206. Vestrucci, A., S. Lumbreras, and L. Oviedo. 2021. Can AI Help Us to Understand Belief? Sources, Advances, Limits, and Future Directions. International Journal of Interactive Multimedia and Artificial Intelligence, Special Issue on Artificial Intelligence, Spirituality and Analogue Thinking 7: 24–33. [Google Scholar] [CrossRef]
  207. Vinichenko, M. V., O. L. Chulanova, M. V. Vinogradova, and L. N. Amozova. 2020. The Impact of Artifical Intelligence on Society Views of Islamic Religious Leaders. European Journal of Science and Theology 16: 67–77. [Google Scholar]
  208. Vishwanatha, J. K., U. Sambamoorthi, U. Sambamoorthi, E. L. Thompson, K. Stinson, and T. A. Syed. 2023. Community perspectives on AI/ML and health equity: AIM-AHEAD nationwide stakeholder listening sessions. PLOS Digital Health 2: e0000288. [Google Scholar] [CrossRef]
  209. Wagner, G., R. Lukyanenko, and G. Paré. 2022. Artificial intelligence and the conduct of literature reviews. Journal of Information Technology 37: 209–26. [Google Scholar] [CrossRef]
  210. Wang, H., and X. Wang. 2023. Sentiment analysis of tweets and government translations: Assessing China’s post-COVID-19 landscape for signs of withering or booming. Global Media and China 8: 213–33. [Google Scholar] [CrossRef]
  211. Wang, J. 2021. Is artificial intelligence capable of understanding? An analysis based on philosophical hermeneutics. Cultures of Science 4: 135–46. [Google Scholar] [CrossRef]
  212. Watts, F. N. 2004. Psychological and Religious Perspectives on Emotion. Journal of Religion & Science 32: 243–60. [Google Scholar]
  213. Willard, A. K., and A. Norenzayan. 2013. Cognitive biases explain religious belief, paranormal belief, and belief in life’s purpose. Cognition 129: 379–91. [Google Scholar] [CrossRef] [PubMed]
  214. Williams, C., A. Denovan, K. Drinkwater, and N. Dagnall. 2022. Thinking Style and Paranormal Belief: The Role of Cognitive Biases. Imagination, Cognition and Personality 41: 274–98. [Google Scholar] [CrossRef]
  215. Xygalatas, D. 2014. Cognitive Science of Religion. Encyclopedia of Psychology and Religion, 343–47. [Google Scholar]
  216. Yen, C., C.-L. Lin, and M.-C. Chiang. 2023. Exploring the Frontiers of Neuroimaging: A Review of Recent Advances in Understanding Brain Functioning and Disorders. Life 13: 1472. [Google Scholar] [CrossRef]
  217. Yin, E., and A. Mahrous. 2022. COVID-19 global pandemic, workplace spirituality and the rise of spirituality-driven organisations in the post-digital era. Journal of Humanities and Applied Social Sciences 4: 79–93. [Google Scholar] [CrossRef]
  218. Ysseldyk, R., K. Matheson, and H. Anisman. 2010. Religiosity as Identity: Toward an Understanding of Religion From a Social Identity Perspective. Personality and Social Psychology Review 14: 60–71. [Google Scholar] [CrossRef]
  219. Yusof, N. N., A. Mohamed, and S. Abdul-Rahman. 2015. Reviewing Classification Approaches in Sentiment Analysis. International Conference on Soft Computing in Data Science 545: 43–53. [Google Scholar]
  220. Zaid, A., and H. Bennoudi. 2023. AI vs. Human Translators: Navigating the Complex World of Religious Texts and Cultural Sensitivity. International Journal of Linguistics, Literature and Translation 6: 173–82. [Google Scholar] [CrossRef]
  221. Zhao, X., Y. Ren, and K. S. Cheah. 2023. Leading Virtual Reality (VR) and Augmented Reality (AR) in Education: Bibliometric and Content Analysis from the Web of Science (2018–2022). SAGE Open 13: 21582440231190821. [Google Scholar] [CrossRef]
  222. Zhong, W., I. Cristofori, J. Bulbulia, F. Krueger, and J. Grafmana. 2017. Biological and cognitive underpinnings of religious fundamentalism. Neuropsychologia 100: 18–25. [Google Scholar] [CrossRef] [PubMed]
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Alkhouri, K.I. The Role of Artificial Intelligence in the Study of the Psychology of Religion. Religions 2024, 15, 290. https://doi.org/10.3390/rel15030290

AMA Style

Alkhouri KI. The Role of Artificial Intelligence in the Study of the Psychology of Religion. Religions. 2024; 15(3):290. https://doi.org/10.3390/rel15030290

Chicago/Turabian Style

Alkhouri, Khader I. 2024. "The Role of Artificial Intelligence in the Study of the Psychology of Religion" Religions 15, no. 3: 290. https://doi.org/10.3390/rel15030290

APA Style

Alkhouri, K. I. (2024). The Role of Artificial Intelligence in the Study of the Psychology of Religion. Religions, 15(3), 290. https://doi.org/10.3390/rel15030290

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop