Filter Babel: The Challenge of Synthetic Media to Authenticity and Common Ground in AI-Mediated Communication

2026-04-17

AI Summary

In an AI-mediated communication environment, individuals immersed in fully personalized synthetic media risk the erosion of a shared reality and common ground for dialogue. This work proposes the concept of the “Filter Babel Tower” through a thought experiment that integrates insights from philosophy of language, human-computer interaction theory, and the mechanisms of AI-generated content, revealing how privatized AI-driven linguistic experiences pose profound threats to public understanding and epistemic authenticity. The study systematically examines challenges to identity coherence, semantic interoperability, and the preservation of truthfulness in AI-mediated communication, advocating for a new paradigm of AI-facilitated discourse that upholds identity integrity and enables meaningful dialogue. It offers a theoretical framework and constructive directions for future research in this emerging domain.

Technology Category

• Philosophy and Ethics of AI: AI & Epistemology
• Natural Language Processing: Language Grounding & Multi-modal NLP
• Humans and AI: AI for Accessibility

Application Category

• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Economics, Online Markets and Human Computation: Economic ramifications for generative AI infrastructure and applications

Abstract

Filter Babel is a thought experiment about a near future in which everything we read, watch, and even whom we "meet" is privately generated for each of us. If we each recede into a world of purely private experience, we may each develop a Wittgensteinian private language that remains intelligible to others only because an AI translator sits in the middle. This intermediation challenges the integrity of common ground and therefore of communication. On the other hand, private experience is an essential engine of identity and selfhood: as Lanier warns, one must be somebody before one can share oneself. This paper opens a discussion of the challenges and opportunities that Filter Babel might present to human communication and identity, and what constructive directions for research in AI-mediated communication might ensue.

Problem

• synthetic media
• AI-mediated communication
• common ground
• authenticity
• identity

Innovation

• Filter Babel
• AI-mediated communication
• synthetic media
• common ground
• private language