Control Search Rankings, Control the World: What is a Good Search Engine?

2025-02-05

AI Summary

This paper addresses the core question: “What constitutes an ethically legitimate search engine?”—focusing on its normative commitments and accountability boundaries as a global information gatekeeper. Methodologically, it introduces the novel “Four-Role Ethical Model” (Customer Servant, Librarian, Journalist, Teacher), integrating information retrieval theory, media ethics, and science and technology studies. Through historical comparative analysis, a COVID-19 case study, and normative ethical modeling, the study systematically examines mechanisms of value embedding across search technology evolution. The contribution is a pragmatic, interdisciplinary ethical assessment framework that informs search engine design, regulatory policy development, and governance of AI-era information gatekeepers. By bridging abstract principles with institutional accountability, the work advances search ethics from aspirational guidelines toward enforceable, institutionally grounded responsibility—marking a significant shift toward systemic, operationalizable ethical governance in information infrastructure.

Technology Category

• Philosophy and Ethics of AI: Accountability, Interpretability & Explainability
• Natural Language Processing: Ethics — Bias, Fairness, Transparency & Privacy
• Search and Optimization: Other Foundations of Search & Optimization

Application Category

• Responsible Web: Fairness, accountability, transparency and ethics of web technologies
• User Modeling, Personalization and Recommendation: Accountability, Transparency, and Ethics for personalization
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics

Abstract

This paper examines the ethical question, 'What is a good search engine?' Since search engines are gatekeepers of global online information, it is vital they do their job ethically well. While the Internet is now several decades old, the topic remains under-explored from interdisciplinary perspectives. This paper presents a novel role-based approach involving four ethical models of types of search engine behavior: Customer Servant, Librarian, Journalist, and Teacher. It explores these ethical models with reference to the research field of information retrieval, and by means of a case study involving the COVID-19 global pandemic. It also reflects on the four ethical models in terms of the history of search engine development, from earlier crude efforts in the 1990s, to the very recent prospect of Large Language Model-based conversational information seeking systems taking on the roles of established web search engines like Google. Finally, the paper outlines considerations that inform present and future regulation and accountability for search engines as they continue to evolve. The paper should interest information retrieval researchers and others interested in the ethics of search engines.

Problem

• Ethical models for search engines
• Interdisciplinary ethical examination
• Regulation and accountability evolution

Innovation

• Role-based ethical models
• COVID-19 case study
• Large Language Model integration