Human Simulation and Sustainability: Ontological, Epistemological, and Ethical Reflections

Abstract

This article begins with a brief outline of recent advances in the application of computer modeling to sustainability research, identifying important gaps in coverage and associated limits in methodological capability, particularly in regard to taking account of the tangled human factors that are often impediments to a sustainable future. It then describes some of the ways in which a new transdisciplinary approach within “human simulation” can contribute to the further development of sustainability modeling, more effectively addressing such human factors through its emphasis on stakeholder, policy professional, and subject matter expert participation, and its focus on constructing more realistic cognitive architectures and artificial societies. Finally, the article offers philosophical reflections on some of the ontological, epistemological, and ethical issues raised at the intersection of sustainability research and social simulation, considered in light of the importance of human factors, including values and worldviews, in the modeling process. Based on this philosophical analysis, we encourage more explicit conversations about the value of naturalism and secularism in finding and facilitating effective and ethical strategies for sustainable development.

Progress in simulating human geography: Assemblage theory and the practice of multi-agent artificial intelligence modeling

“…How? Participatory and collaborative methods in the simulation of human-geographic assemblages help to surface ethical presuppositions driving the construction of models and the design of simulation experiments (Shults and Wildman, 2020b). The co-production of MAAI models in transdisciplinary teams of social scientists, computer modelers, and policy stakeholders provides conceptual scaffolding and experimental tools that make it easier for everyone involved to see and critique one another's ethical assumptions and to explore the political implications of alternative proposals.…”

Paying the Piper: History, Humanities, and the Scientific Study of Religion

“…Ambasciano also neglects the positive effects of our modeling approach, the results of which he fails to cite. MAAI models developed through our international collaborative efforts with humanities and social science scholars have aimed at discovering solutions to real-world challenges such as mitigating xenophobic anxiety and intergroup conflict , finding more progressive and culturally sensitive ways to solve immigration crises in Europe related to Refugee camps in Lesbos (Padilla, et al, 2018;Paloutzian, et al, 2021), analyzing the effectiveness of anti-childsex-trafficking policies (Alizada & Wildman, 2019), simulating processes that enhance minority integration in urban areas (Puga-Gonzalez, et al, 2019), addressing problems related to ethnocentrism (Lemos, et al, 2019), responding to global challenges related to the United Nations Sustainable Development Goals (Shults & Wildman, 2020b), reducing radicalization and violent extremism Ottman, et al 2022), uncovering ways to help change the Dutch immigration system to be more culturally compatible with Syrian Refugees (Boshuijzen-van Burken, et al, 2020), offering support for universities and other organizations struggling to set policies to slow the spread of COVID-19 (Wildman, et al, 2020), providing insight for therapeutic interventions for PTSD nightmares (McNamara, et al, 2021), illuminating the dynamics that promote prosocial attitudes and behaviors (Galen, et al, 2021), and preventing the spread of misinformation and anxiety in the wake of a pandemic (Antosz, et al, 2022). We welcome whatever assistance Ambasciano or other historians of religion, regardless of their previous participation in CSR 2.0, have to offer to help us address these critical social issues using the kinds of tools that policy makers are interested in engaging.…”

Simulation, Science, and Stakeholders: Challenges and Opportunities for Modelling Solutions to Societal Problems

“…In this section, I outline the general procedure for navigating what has elsewhere been called the "insight space" provided by the human simulation approach to computational models aimed at social simulation [7]. Te navigation of this space moves (often backward as well as forward) through fve distinct but interrelated phases: analysing a problem situation, creating a problem space, selecting a specifc problem, designing a solution space, and critique and iteration.…”

“…Te good news is that there are computational modelling and simulation (CMS) tools, especially agentbased modelling (ABM), that are designed specifcally for understanding and explaining such complex adaptive systems [1,2]. Although the use of these tools to address real-world societal problems is increasing rapidly [3][4][5][6], the bad news is that progress is held up by challenges related to the psychological and sociological realism of "artifcial societies" and by challenges related to engaging stakeholders in participatory modelling [7]. As we will see, these challenges are closely linked and taking full advantage of opportunities for the practical application of CMS methodologies to the task of solving societal challenges will require a more careful and rigorous linking of stakeholder participation strategies to the scientifc process of developing and deploying adequately realistic computational models.…”