From Babel to Nehemiah: A Theological Reading of Magnifica Humanitas and the Governance of Artificial Intelligence
DOI:
https://doi.org/10.55324/ijoms.v5i10.1295Keywords:
Magnifica Humanitas, Catholic Social Doctrine, artificial intelligence governance, Babel and Nehemiah, Trinitarian communionAbstract
This study reads the encyclical within its own theological context and questions what vision of systemic governance is implied in its argument. This reading is organized through the Systems Shift heuristic a seven-element framework drawn from socio-technical transition theory, leverage point analysis, lock-in studies, Responsible AI research, and AI governance literature but this framework serves to support the encyclical's argument, not to organize it. The study's central argument is that Magnifica Humanitas opposes two competing civilizational scripts. Babel names a social order dominated by concentrated technical power, the idolatry of profit, homogenization, and the functional reduction of human beings to data and performance. Nehemiah names the opposite order: patient reconstruction, distributed responsibility, prayerful wisdom, and the protection of the vulnerable. Leo XIV himself framed the AI ??era through these biblical images, and this paper shows that this framing carries the full weight of the encyclical’s theological anthropology: the measure of the technological order is the Incarnation the Word made flesh who reveals the human person as irreducibly embodied, relational, free, and called to communion. Five new theological dimensions are developed and integrated: (1) Trinitarian communion as the theological foundation of the Nehemiah paradigm; (2) structural sin as the proper theological name for the Babel configuration; (3) pneumatology as the basis of shared understanding; (4) incarnational biology as a deepening of Christological anthropology against AI reductionism; and (5) Marian eschatology the grammar of the Magnificat as the encyclical’s concluding horizon for the human city.
References
Aloisi, A., & De Stefano, V. (2022). Essential jobs, remote work and digital surveillance: Addressing the COVID-19 pandemic panopticon. International Labour Review, 161(2), 289–314. https://doi.org/10.1111/ilr.12219
Birkstedt, T., Minkkinen, M., Tandon, A., & Mäntymäki, M. (2023). AI governance: Themes, knowledge gaps and future agendas. Internet Research, 33(7), 133–167. https://doi.org/10.1108/INTR-01-2022-0042
Carabantes, M. (2020). Black-box artificial intelligence: An epistemological and critical analysis. AI & Society, 35(2), 309–317. https://doi.org/10.1007/s00146-019-00888-w
Choung, H., David, P., & Ross, A. (2023). Trust in AI and its role in the acceptance of AI technologies. International Journal of Human–Computer Studies, 174, 103007. https://doi.org/10.1016/j.ijhcs.2023.103007
Corrêa, N. K., Galvão, C., Santos, J. W., Del Pino, C., Pinto, E. P., Barbosa, C., Massmann, D., Mambrini, R., Galvão, L., Terem, E., & de Oliveira, N. (2023). Worldwide AI ethics: A review of 200 guidelines and recommendations for AI governance. Patterns, 4(10), 100857. https://doi.org/10.1016/j.patter.2023.100857
Coveri, A., Cozza, C., Guarascio, D., & Zanfei, A. (2024). Platform power: Monopolisation and financialisation in the era of big tech. Structural Change and Economic Dynamics, 70, 394–407. https://doi.org/10.1016/j.strueco.2024.03.016
Dencik, L., Hintz, A., Redden, J., & Tre?re?, E. (2019). Exploring data justice: Conceptions, applications and directions. Information, Communication & Society, 22(7), 873–881. https://doi.org/10.1080/1369118X.2019.1606268
Geels, F. W. (2019). Socio-technical transitions to sustainability: A review of criticisms and elaborations of the Multi-Level Perspective. Current Opinion in Environmental Sustainability, 39, 187–201. https://doi.org/10.1016/j.cosust.2019.06.009
Geels, F. W. (2020). Micro-foundations of the multi-level perspective on socio-technical transitions: Developing a multi-dimensional model of agency through crossovers between social constructivism, evolutionary economics and neo-institutional theory. Technological Forecasting and Social Change, 152, 119894. https://doi.org/10.1016/j.techfore.2019.119894
Jobin, A., Ienca, M., & Vayena, E. (2019). The global landscape of AI ethics guidelines. Nature Machine Intelligence, 1(9), 389–399. https://doi.org/10.1038/s42256-019-0088-2
Kusche, I. (2024). Possible harms of artificial intelligence and the EU AI Act: Fundamental rights and risk. Journal of Risk Research, 27(9), 1143–1159. https://doi.org/10.1080/13669877.2024.2350720
Lacsa, J. E., & Arroyo, R. C. (2024). Integrating Catholic social teaching with AI ethics to address inequity in AI healthcare. Journal of Religion and Health, 63(5), 3435–3454. https://doi.org/10.1007/s10943-024-02140-2
Laine, J., Minkkinen, M., & Mäntymäki, M. (2024). Ethics-based AI auditing: A systematic literature review on conceptualizations of ethical principles and knowledge contributions to stakeholders. Information & Management, 61(5), 103963. https://doi.org/10.1016/j.im.2024.103963
Mäntymäki, M., Minkkinen, M., Birkstedt, T., & Viljanen, M. (2022). Defining organizational AI governance. AI & Society, 37(4), 1452–1462. https://doi.org/10.1007/s00146-022-01477-5
Radu, R. (2021). Steering the governance of artificial intelligence: National strategies in perspective. Policy and Society, 40(2), 178–193. https://doi.org/10.1080/14494035.2021.1899866
Regilme, S. S. (2024). Artificial intelligence colonialism: Environmental damage, labor exploitation, and human rights crises in the Global South. SAIS Review of International Affairs, 44(2), 75–92. https://doi.org/10.1353/sais.2024.a950958
Ryan, M., & Stahl, B. C. (2021). Artificial intelligence ethics guidelines for developers and users: Clarifying their content and normative implications. Journal of Information, Communication and Ethics in Society, 19(1), 61–86. https://doi.org/10.1108/JICES-12-2019-0138
Stahl, B. C., Antoniou, J., Bhalla, N., Brooks, L., Jansen, P., Lindqvist, B., Kirichenko, A., Marchal, S., Rodrigues, R., Santiago, N., Warso, Z., & Wright, D. (2023). A systematic review of artificial intelligence impact assessments. Artificial Intelligence Review, 56(11), 12799–12831. https://doi.org/10.1007/s10462-023-10420-8
Susser, D., Roessler, B., & Nissenbaum, H. (2019). Technology, autonomy, and manipulation. Internet Policy Review, 8(2). https://doi.org/10.14763/2019.2.1410
Zuboff, S. (2019). Surveillance capitalism and the challenge of collective action. New Labor Forum, 28(1), 10–29. https://doi.org/10.1177/1095796018819461
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