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Search Engines Post-ChatGPT: How Generative Artificial Intelligence Could Make Search Less Reliable

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arxiv 2402.11707 v1 pith:H3KAEVMY submitted 2024-02-18 cs.IR cs.AIcs.CY

classification cs.IRcs.AIcs.CY
keywords searchenginesgenaiartificialcontentdiscussgenerativeinformation
verification ladder T0 review T1 audit T2 compute T3 formal
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In this commentary, we discuss the evolving nature of search engines, as they begin to generate, index, and distribute content created by generative artificial intelligence (GenAI). Our discussion highlights challenges in the early stages of GenAI integration, particularly around factual inconsistencies and biases. We discuss how output from GenAI carries an unwarranted sense of credibility, while decreasing transparency and sourcing ability. Furthermore, search engines are already answering queries with error-laden, generated content, further blurring the provenance of information and impacting the integrity of the information ecosystem. We argue how all these factors could reduce the reliability of search engines. Finally, we summarize some of the active research directions and open questions.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. News Source Citing Patterns in AI Search Systems

    cs.IR 2025-07 conditional novelty 6.0 of 10

    AI search engines concentrate news citations among a few mostly left-leaning, high-quality outlets, and users do not appear to base preferences on cited source leaning or quality.

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