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In this fascinating conversation, Dr. Beth Singler and Gilad Berenstein dive into the complex topic of digital religions. They discussed the many ways established religions are adopting technology and artificial intelligence and adapting their practice for the AI age, as well as the emergence of new religions for whom technology and artificial intelligence are at the core of their belief system. They conclude with a beautiful conversation about AI hope in the future, where artificial intelligence elevates all of our spiritual practices.
Meet our speakers:
Host: Gilad Berenstein is currently working in venture capital in Seattle after founding and leading a successful travel personalization startup and serving as an Entrepreneur-in-Residence at the Allen Institute for Artificial Intelligence (AI2). Gilad holds masters and undergraduate degrees from the Foster School of Business at the University of Washington.
Guest: Prof. Dr Beth Singler is the Assistant Professor in Digital Religion(s) at the University of Zurich (UZH). She is the Co-Director of the University Research Priority Programme (URPP) in Digital Religion(s), a member of the board of Directors of the Digital Society Initiative, and Co-Lead of the MEEET-Lab. Beth explores the social, ethical, philosophical and religious implications of advances in Artificial Intelligence and robotics. She has been described as the “smartest and sanest observer of digital religion” (Church Times 2025). In 2024 she published two books on Religion and AI: her newest monograph, Religion and AI: An Introduction, which won a 2025 ISSR Book Prize and The Cambridge Companion to Religion and AI, co-edited with Fraser Watts.
New Books:
Religion and AI: An Introduction
The Cambridge Companion to Religion and AI
Views and opinions expressed by podcast guests are their own and do not necessarily reflect the view of AI and Faith or any of its leadership.
Production: Penny Yuen
Host: Gilad Berenstein
Guest: Dr. Beth Singler
Editing: Isabelle Braconnot
Music from #Uppbeat License code: 1ZHLF7FMCNHU39
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