Answer Bubbles: Information Exposure in AI-Mediated Search
Michelle Huang, Agam Goyal, Koustuv Saha, Eshwar Chandrasekharan

TL;DR
This study analyzes how AI-mediated search systems influence source diversity, language, and fidelity, revealing biases and the emergence of 'answer bubbles' that shape user perceptions of information.
Contribution
It provides a comprehensive comparison of four search systems, uncovering biases in source selection and the impact of AI summaries on information diversity and trust.
Findings
Generative systems show source-selection biases favoring certain sources.
Search integration reduces epistemic markers, decreasing hedging.
AI summaries overrepresent Wikipedia and long sources, underrepresent social media and negative sources.
Abstract
Generative search systems are increasingly replacing link-based retrieval with AI-generated summaries, yet little is known about how these systems differ in sources, language, and fidelity to cited material. We examine responses to 11,000 real search queries across four systems -- vanilla GPT, Search GPT, Google AI Overviews, and traditional Google Search -- at three levels: source diversity, linguistic characterization of the generated summary, and source-summary fidelity. We find that generative search systems exhibit significant \textit{source-selection} biases in their citations, favoring certain sources over others. Incorporating search also selectively attenuates epistemic markers, reducing hedging by up to 60\% while preserving confidence language in the AI-generated summaries. At the same time, AI summaries further compound the citation biases: Wikipedia and longer sources are…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsInformation Retrieval and Search Behavior · Wikis in Education and Collaboration · Misinformation and Its Impacts
