Filter Babel: The Challenge of Synthetic Media to Authenticity and Common Ground in AI-Mediated Communication
TLDR
This paper explores "Filter Babel," a future where personalized AI-generated media challenges common ground and identity in human communication.
Key contributions
- Introduces "Filter Babel," a concept where all media and interactions are privately AI-generated for individuals.
- Explores how this personalized reality could erode common ground and the integrity of human communication.
- Discusses the tension between private experience for identity and the necessity of a shared reality.
- Identifies key challenges and opportunities for future research in AI-mediated communication.
Why it matters
This paper highlights a critical future challenge: how hyper-personalized AI-generated content could isolate individuals and undermine shared understanding. It prompts crucial discussion on maintaining common ground and identity in an increasingly AI-mediated world, guiding future research.
Original 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.
📬 Weekly AI Paper Digest
Get the top 10 AI/ML arXiv papers from the week — summarized, scored, and delivered to your inbox every Monday.