The End of the Search Engine Era and the Rise of Generative AI: A Paradigm Shift in Information Retrieval

For over two decades, search engines have played a critical role in the internet ecosystem, facilitating access to vast amounts of information. Google, Bing, and other search engines have become household names, ingrained in the way people navigate the web and retrieve data. However, recent advancements in artificial intelligence (AI), particularly in generative AI models like OpenAI's GPT-4, have ushered in a new era of information retrieval. These models offer a fundamentally different approach by generating context-aware, human-like responses to complex queries, effectively challenging the search engine's dominance. This paper explores the transition from traditional search engine-based information retrieval to generative AI models, discussing the limitations of search engines, the strengths of generative AI, the societal and economic implications of this shift, and the ethical considerations that accompany the growing reliance on AI for information dissemination. The research draws on historical trends, technological advancements, and contemporary user behavior to present a comprehensive analysis of how generative AI is reshaping the digital landscape.

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Publication Details

Published
2024-11-13
DOI
https://doi.org/10.1109/miucc62295.2024.10783559
Citations
10
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
5.29
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article

The End of the Search Engine Era and the Rise of Generative AI: A Paradigm Shift in Information Retrieval

Tamer Elboghdadly, Eslam Amer
10 citations
Big Data and Business Intelligence
5.29
article

The End of the Search Engine Era and the Rise of Generative AI: A Paradigm Shift in Information Retrieval

Tamer Elboghdadly, Eslam Amer
article en
10 citations

Abstract

For over two decades, search engines have played a critical role in the internet ecosystem, facilitating access to vast amounts of information. Google, Bing, and other search engines have become household names, ingrained in the way people navigate the web and retrieve data. However, recent advancements in artificial intelligence (AI), particularly in generative AI models like OpenAI's GPT-4, have ushered in a new era of information retrieval. These models offer a fundamentally different approach by generating context-aware, human-like responses to complex queries, effectively challenging the search engine's dominance. This paper explores the transition from traditional search engine-based information retrieval to generative AI models, discussing the limitations of search engines, the strengths of generative AI, the societal and economic implications of this shift, and the ethical considerations that accompany the growing reliance on AI for information dissemination. The research draws on historical trends, technological advancements, and contemporary user behavior to present a comprehensive analysis of how generative AI is reshaping the digital landscape.

University of Portsmouth (GB)
Openalex Percentile: Top 4%
Big Data and Business Intelligence
5.29
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