Simulating Religious Conflict and Peacebuilding through Multi-Agent Artificial Intelligence Modeling

The utilization of multi-agent artificial intelligence (MAAI) in modeling religious dynamics, social conflicts, and pathways to peace represents a significant advancement in computational social sciences and humanities. This presentation will outline the approach to MAAI that the author has used as the leader of several international, interdisciplinary research projects with a special focus on the integrative process and empirical insights that have emerged in their work with the United Nations Development Program in Palestine and Bosnia & Herzegovina, as well as Northern Ireland and South Sudan. Each of the models developed in these contexts has been constructed with the help of religious studies subject matter experts, incorporating religious factors and variables into the cognitive architectures and social network interactions of the simulated agents that populate the ‘artificial societies’ (or digital twins) of the regions they represent. Such models provide scholars and stakeholders with a digital laboratory in which they can run simulation experiments in order to discover the conditions under which – and the processes by which – intergroup religious conflict can be mitigated and peaceful cooperation can be promoted.

The complex interplay of religion, identity, and social cohesion has long posed challenges to peace and reconciliation efforts worldwide. Traditional approaches in disciplines such as religious studies provide theoretical insight into such challenges but are rarely able to shed light on the non-linear causal dynamics of the social systems they study. Traditional quantitative analytical methods often fall short in capturing the nuanced dynamics that lead to conflict or foster peace. However, recent advancements in artificial intelligence, specifically MAAI modeling, offer new insights into these complexities – when such models are constructed with diverse and hermeneutically sensitive subject matter experts.  

MAAI systems model social phenomena by simulating the interactions of individual agents within a digital environment. These agents, governed by algorithms that mimic human cognitive and affective processes, interact within specified parameters, allowing researchers to observe emergent behaviors and patterns. This approach is particularly suited to studying religion and social conflict, where individual beliefs and behaviors aggregate to form complex social dynamics. Such approaches can “grow” the macro-level phenomenon of interest from the micro-level behaviors and meso-level interactions of the networked simulated agents. Once validated against real-world data, these models provide insights into the causal relationships among these levels and can be used to test scientific hypotheses and stakeholder policies. Data can include surveys, interviews, subject matter expertise or data gathered from an online platform called ARES, which can analyze online textual data across 93 dimensions, including cultural, psychological, and moral concerns, to model social behaviors and predict outcomes with high accuracy.

After an introduction to this methodology, the bulk of this presentation will outline some of the insights gained from the use of MAAI in three regions that have been (or are) characterized by social conflict. In each of these regions, historical and social conflicts have deeply entrenched religious divisions. MAAI modeling offers a unique lens to examine these divisions, identify underlying triggers of conflict, and potential levers for peace. Our work in Northern Ireland was funded by a research grant in collaboration with the Woolf Center at the University of Cambridge. Our MAAI model of that region has been able to simulate past conflicts (40 years of ‘The Troubles’) with a high degree of accuracy and simulation experiments have shed light on the main drivers of conflict and cooperation in the recent past. Optimization experiments on this model, some of which will be reported in the 2024 UN Human Development Report, are also able to shed light on the parameters that are most likely to promote peace (or conflict) in the near future.

Our work in the other two regions has been funded by the United Nations Development Program. In Palestine, our research team has already developed a prototype, system-dynamics model of the socio-ecological system of the region and we are well on our way to developing a full MAAI model. Here is a link that briefly describes that work: https://www.wired.com/story/culturepulse-ai-israeli-palestinian-crisis/?utm_medium=social&utm_source=twitter&utm_brand=wired&utm_social-type=owned&mbid=social_twitter.  Our current work with the UNDP office in Bosnia & Herzegovina also involves both system-dynamics and MAAI models. Here we are collaborating with social scientists and stakeholders in the region to simulate the complex interplay between religious identity, territorial disputes, and political sovereignty, offering insights into the cyclical nature of conflict and potential interventions that could foster coexistence.

The analytic and predictive capability of MAAI, as demonstrated by the ARES platform, holds significant promise for policymakers and peacebuilders as well as social scientists. By identifying not just the manifestations of conflict but also its root causes, MAAI enables targeted interventions that can address the psychological, social, and cultural dimensions contributing to tension and violence. Furthermore, the ability of MAAI to model the impact of information spread through social media on community sentiment and beliefs offers a powerful tool for combating misinformation and hate speech, which are often precursors to violence. The integration of MAAI in studying religion, social conflict, and peace efforts marks a transformative shift in the social sciences. The approach described here exemplifies the potential of this technology to contribute to a deeper understanding of complex social phenomena and to inform more effective strategies for conflict resolution and peacebuilding. In regions like Palestine, Bosnia, and Northern Ireland, where historical wounds run deep, MAAI offers a beacon of hope for uncovering new pathways to reconciliation and lasting peace.