Justin E. Lane’s cognitive science of religion, presented in Understanding Religion Through Artificial Intelligence: Bonding and Belief, is an interdisciplinary endeavor combining artificial intelligence (AI) with cognitive science, and evolutionary and cognitive psychology with anthropology and religious studies. Instead of religious traditions, he concentrates on religious systems. He reconceptualizes religion as a “cybernetic assemblage” and refers to his approach as “cultural cybernetics.” Its methodological rigor lies in its ability to devise a continuum between traditional qualitative fieldwork methods and modern AI by modeling different types of religiosities. Advanced machine learning uses algorithms to create artificial neural networks that are inspired by neurophysiology. These networks are used to predict religious behavior by examining the link between the system input and expected (probabilistic) output. Lane suggests the use of Multi-Agent AI (MAAI) to create psychologically realistic algorithms whose mechanism replicates human cognitive processes, which could prove significant for addressing complex social concerns and encourage researchers to utilize the evolution and dynamism of adaptive and complex social systems. Lane’s succinct use of cultural cybernetics, based on human cognition and an information-centric approach, provides a novel method in anthropology. It analyzes semi-structured field data and online data sources to construct semantic network representations and quantify within-group consensus to build “computational approximations of an individual’s schema” (221).
Every chapter delivers novel ways of explaining old subjects of inquiry. Lane offers an interesting rendition of rituals by going beyond the taken-for-granted formal representation of rituals to understand their effect on social cohesion. It suggests that group beliefs are codified by frequent low arousal rituals that extend the group’s schema to more individuals who increasingly socially identify with the group. The rare emotionally intense ritual experiences tie individuals to the group’s essential beliefs in ways that encourage them to engage in altruistic self-sacrifice for the group. Simultaneously, Lane refutes homogenizing tendencies by positing that diverse evolutionary pressures have resulted in multiple formations of doctrinal rituals. IIS’s (Information Identity System) collaboration with the DMR (Divergent Modes of Religiosity) theory offers theoretically and empirically grounded explanations of religious and cultural changes.
Along with fusion theory, social identity theory, and the devoted actor theory, IIS offers ways to understand and predict the contextual specificities of social issues like religious extremism and how its link with intense personal experiences leads to conceptual ties. It uses the “output correspondence” approach to validate computer simulations. Using simulation techniques and computational modeling, Lane examines the relationship between fused beliefs and tedium effect, extended fusion and conceptual ties, fused individuals and devoted actors, and conceptual links and sacred values.
Lane lucidly explores the application of modern information processing at the intersection of bonding and belief to not only study the effect of religion on the everyday lives of humans but also to trace its effect throughout history. Furthermore, IIS’s collaboration with the DMR theory allows for a multi-causal analysis that explores the impending relevance of emotionally intense rituals in doctrinal religions. It also incorporates both the imagistic and doctrinal models of religion to explain the transition of societies from one form of social organization to the other. While predictions allow for the multi-level control of religious and cultural systems, they also raise severe ethical considerations concerning data protection and the misuse of modern computation for vested interests that often curtail civil liberties. Simultaneously, Lane debunks the impending fear of an AI apocalypse.
Lane’s endeavor to use computational modeling to analyze a group’s social cohesion is a path-breaking contribution to the cognitive science of religion. This type of modeling reconceptualizes and integrates earlier theories of cognition, religion, group alignment, and social cohesion to make it more empirically applicable and policy relevant. It also reinvigorates the scientific study of religion and postulates the importance of naturalistic assumptions and falsification. However, he cautions readers against the reductionist tendencies of such an approach and suggests the need for incorporating multi-variable causal analysis, especially by using the multi-agent AI system for making, quantifiable, empirical, and testable predictions about the religious behavior and thought of both individuals and groups.
Throughout the book, especially in the final chapter, Lane provides directions for future research using semantic networks and computational techniques to study doctrinal religions, social schisms, and historically specific socio-biological changes. This book has significant inter-disciplinary implications as it widens the scope of the social sciences by strengthening its epistemological foundations, providing new ontological directions, and critically engaging scholars from diverse fields. Finally, it enriches the study of religion by reframing how the subject is approached scientifically and intrigues non-academic minds on how AI could facilitate our understanding of human religiosity.
Anand Ranjan is a doctoral fellow at the School of Divinity, University of Edinburgh.
Anand Ranjan
Date Of Review:
October 26, 2022