AI4LAM Fantastic Futures 2026: Trust in the Loop
This participatory workshop invites attendees to work through the AI Maturity Index for Academic Libraries together and to use their results as a catalyst for structured conversation about AI assessment, planning, prioritization, readiness, and governance gaps. The workshop’s value is not the tool itself; it’s the dialogue the tool generates among library staff with different roles, vantage points, and institutional contexts. The AI Maturity Index for Academic Libraries assesses eight dimensions of library practice—Collections, Discovery, Facilities, Instruction, Metadata, Preservation, Research, and Governance—across five maturity levels. The Index understands that AI maturity is not determined by the amount of AI technology a library uses; instead, it measures how effectively AI serves its users’ needs. Attendees leave with a provisional maturity profile for their institution, facilitation strategies they can replicate with their own staff, and peer connections to colleagues navigating similar challenges.
Church & AI Conference / GoNeDiGiTal: Digital Theology to Date and Beyond
My goal in this paper is to explore the crafting of artificial agents that serve the ends of the church. I argue that an existing technique in AI safety training called ‘constitutional AI’ can be fruitfully adapted to create AI agents that promote the glory of God and the flourishing of human beings. After unpacking how constitutional AI works at a technical level—from reinforcement learning with human feedback to reinforcement learning from AI feedback—I trace the evolution of Anthropic’s constitution for Claude from 2023 to 2026 and propose that the church’s long history of confession and catechesis offers a better metaphor than constitutionalism: ‘catechetical AI.’ I then take up questions of free expression, sovereignty, and pluralism, contrasting the subsidiarity of Catholic social teaching in Pope Leo XIV’s Magnifica Humanitas with a Neo-Calvinist model of sphere sovereignty. Bending constitutional AI toward the ends of the church leads inevitably toward a greater pluralism than standard AI safety protocols anticipate—and that, I contend, is a good thing for the future of human–AI collaboration. I forecast the emergence of a new breed of theological engineer who catechizes models as ‘creedal machines’ to serve alongside congregants in the different spheres of human activity.
International Conference for the Fantastic in the Arts 47: (Meta)Cognition
This paper (co-authored with Haerin Shin and Douglas Fisher) examines Haruki Murakami’s fiction as a sustained meditation on metacognitive practice that fundamentally opposes the accelerated cognition characteristic of generative artificial intelligence. Murakami rarely writes about computation and evinces distaste for technological advances, yet his fiction offers insight into a fundamental question facing us as AI rapidly advances: how to maintain human ways of knowing in an increasingly automated and algorithmically structured world. Drawing primarily on Hard-Boiled Wonderland and the End of the World, The Wind-Up Bird Chronicle, Dance Dance Dance, Kafka on the Shore, and Killing Commendatore, as well as the nonfiction of Underground, we argue that Murakami’s narrative architectures deliberately cultivate what Daniel Kahneman terms ‘System 2’ thinking—slow, deliberate, consciously effortful cognition. His liminal ‘other worlds’ enforce a durational consciousness that resists algorithmic compression, while his antagonists—hollow figures of algorithmic intelligence like Noboru Wataya and Menshiki—raise the question of whether strategic optimization and pattern recognition, however sophisticated, ever constitute genuine understanding without a moral center or experiential ground. Murakami’s novels model consciousness as essentially inefficient, necessarily embodied, and irreducibly temporal, demonstrating how literature itself might serve as a technology for preserving slow cognition against the tyranny of instantaneous processing.
Artificial Intelligence and Religion Unit, Annual Meeting of the American Academy of Religion
This paper describes an experiment to generate stub articles about women religious leaders using a purpose-built artificial intelligence system as a means to address gender imbalances on Wikipedia. The Women in Religion User Group is an officially recognized Wikimedia Movement Affiliate that “seeks to create, update, and improve Wikipedia articles pertaining to the lives of cis and transgender women scholars, activists, and practitioners in the world’s religious, spiritual, and wisdom traditions.” (Women in Religion 2025) In the early stages of the project, we explored the use of retrieval augmented generation (RAG) to improve the veracity of the stubs that the LLM generated. In the current phase of the project, we are fine-tuning an open-source large language model to improve its ability to create Wikipedia stubs. After reviewing these techniques, we discuss their effectiveness while also raising ethical questions about releasing our project in open source.
WikiConference North America 2025
This workshop, facilitated by members of the Women in Religion User Group, explores the ethical, technical, and practical potential of using artificial intelligence to assist editors of underrepresented topics on English-language Wikipedia. We begin by reviewing the Wikimedia Foundation’s April 2025 strategy brief, “Artificial Intelligence for Editors.” Drawing on the experience of our user group, we will discuss ways of “supporting editors with AI” when editing articles about underrepresented areas. We will reflect on our efforts during the past two years to accelerate the production of stubs about notable women in religion using techniques such as retrieval augmented generation, synthetic data creation, and LLM fine-tuning. During our discussion, we will offer a series of pulse surveys to gauge participant sentiment about the employment of these techniques on and off Wiki. As an outcome of this workshop, we will publish our collective thoughts at our user group’s Meta page with the hope of charting a path for using AI responsibly to address knowledge gaps on Wikipedia.
Critical Legal AI Literacies Speaker Series, Yale Law School
Theologies of the Digital III: Biases and Debiasing Theology, Garrett Evangelical Theological Seminary
How do we teach a computer the meaning of words? Word embeddings, a breakthrough of natural language processing, render the semantics of words computationally tractable by representing them as vectors in a high-dimensional space—exemplifying, though they emerged from statistics and computer science, two key ideas in the philosophy of language: Frege’s principle that words have meaning only in the context of a sentence and Wittgenstein’s dictum that the meaning of a word is its use in the language. But embeddings also absorb latent forms of bias from the corpora on which they are trained. In this presentation, I introduce word embeddings from a theological perspective, examine techniques for identifying and rectifying gender bias in word embeddings, and ask what tools developed to measure demographic biases might reveal about biases related to religious identity. In an accompanying hands-on session, we explore latent biases in a large corpus of contemporary news.
Wikimedia+Libraries International Convention 2025
The term ‘deepfake’ was first coined in 2017 to describe the use of deep neural networks to generate synthetic voices, images, and videos. In its early years, the technology was primarily used to create pornography, memes, and political propaganda. As the technology has matured, deepfakes have also become a tool of financial fraud, with corporations reporting millions in losses annually.
However, ‘deepfakes’ also have positive uses. The cultural heritage sector, for example, has created compelling interactive exhibits that use synthetic media and artificial intelligence to bring artists and artworks to life, so to speak. In 2019, the Dalí Museum in St. Petersburg, Florida exhibited a deepfake version of Salvador Dalí titled “Dalí Lives” that interacted with visitors. In 2024, the same museum recreated Dalí’s “lobster phone” to allow visitors to call the artist and engage with his digital simulacra in conversation about his artwork. Scholars debate the ethics of creating such installations, which promote public engagement but perhaps at the cost of diluting artistic and historical authenticity.
In this talk, I explore a related side-effect of using AI-generated synthetic media in cultural heritage, namely, how deepfakes affect cultural memory. Researchers are now investigating how deepfakes change our perceptions of personal and cultural history. As more and more institutions make their collections freely available online, and these images in turn become training data for improving deep neural networks capable of making better and more compelling synthetic images, what responsibility do cultural heritage institutions have to serve as stewards of authentic (digital) memory?
Guest Lecture for MAC626: Artificial Intelligence & Media, Korea University
WikiConference North America 2024
The Women in Religion WikiProject was founded in 2018, with three significant goals: to increase the content about women in religion on Wikipedia; to train others interested in learning how to edit and contribute to Wikipedia and Wikidata; and to create reliable, secondary sources about women in religion. To that end, we have been involved in several impactful projects; most recently, the publication of three monographs of biographies about notable women in religion (with a fourth currently in the planning stage) and experimentations with AI to assist editors in using that technology to increase content about underrepresented people and topics on Wikipedia. We also have monthly zoom planning sessions and editathons. This panel will report on our projects and the significant contributions we’ve made to Wikipedia and to Wikidata.