The popularization of artificial intelligence has been and continues to be the fastest diffusion of technology in human history. The development and rapid spread of this technology was and is not inevitable but rather a consequence of needs that pervade human society. This project explores how our changing relationship with truth and an overwhelming flood of daily information have created a modern crisis of trust, leaving a cultural vacuum that a social technology like AI is stepping in to fill. This research looks towards global secularization as a possible entry into a taxonomy of those needs, arguing that secularization has led to the fracturing of truth and the massive production of information that necessitated a social technology like artificial intelligence. Indeed, secularization precipitates the many dislocations of modernity and post-modernity that can inform our study of the 'AI era': the industrial, scientific, financial, psychological, and media revolutions.

There are two pivotal elements of this analysis. First, AI is perceived as an omniscient truth generator, offering a remedy for the gap left by the displacement of sacred texts and their modern offspring. Second, the future of AI is imagined as apocalyptic, built upon a redemptive narrative that affects development, regulation, and popularization of AI. While scholars, commentators, and developers have increasingly noted the many intersections between religion and AI, few have expanded their scope to the religio-epistemological and ontological needs that produce and popularize this technology.

Making use of the architecture and UX of AI models, language used by AI developers and founders, popular perceptions of AI as expressed through conventional and social media, and contemporary technological and social theory, this research sets out to articulate one possible reason why AI is developed and why it is so “popular.” Moreover, this research is linked to two fundamental questions about AI and society: First, what are the truth claims of AI, and are they aligned with public perceptions, developer goals, and material reality? Second, how can we differentiate between religious metaphors—apocalyptic narratives used as rhetorical fodder for resource allocation—and actual, material risk?

By identifying a series of ontological conditions for AI propagation, this research directly contributes to CNTR’s mission to champion technological responsibility and to examine our technological imagination. Instead of looking at standard code or policy fixes, this work confronts the deeper cultural reasons why we lean on AI.     In the end, unpacking the narratives that shape how we understand this technology—asking why they are so compelling—will allow us to better predict and transform the AI future. 

• How do the technical designs of AI models, like their ability to simulate human-like conversations and empathy, trick us into believing they are infallible, and how does that match up with reality?
• How can we separate the sci-fi storytelling used by tech founders (like dramatic warnings of a robot apocalypse or promises of a utopian future) from the actual, everyday dangers of unchecked AI growth?
• How can understanding our deep human need for certainty, authority, and answers help us better predict where artificial intelligence is heading next?