Knowledge on trial: AI, trust and the future of decision-making

Purpose The purpose of the paper is to highlight that while they may be in a hurry to feed the growing giant of AI, they must also thoughtfully consider the consequences. The black-box nature of AI raises concerns about transparency and trust and as long as they do not fully understand how AI reaches its conclusions, questions about the reliability of AI-driven decision-making will continue. Design/methodology/approach A qualitative secondary research approach, using content analysis of evidence collected from newspapers, research papers and recent books to critically compare AI-driven and traditional approaches to knowledge and decision-making. Findings The findings reveal that AI-driven decisions cannot be trusted blindly, as they may reinforce existing vulnerabilities and discrimination in society. Therefore, AI must be used mindfully, with continuous human oversight, transparency and accountability, to reduce rather than exacerbate disorder and inequality in the information society, while building public trust instead of creating fear. Originality/value The paper is original, offering a critical perspective on AI-driven decision-making, trust and the need for mindful human oversight in the information society.

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Publication Details

Journal
Library Hi Tech News
Published
2026-10-07
DOI
https://doi.org/10.1108/lhtn-09-2026-0199
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
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article

Knowledge on trial: AI, trust and the future of decision-making

Saleeq Ahmad Dar, Hilal Ahmad Dar
Library Hi Tech News
Ethics and Social Impacts of AI
article

Knowledge on trial: AI, trust and the future of decision-making

Saleeq Ahmad Dar, Hilal Ahmad Dar
article en

Abstract

Purpose The purpose of the paper is to highlight that while they may be in a hurry to feed the growing giant of AI, they must also thoughtfully consider the consequences. The black-box nature of AI raises concerns about transparency and trust and as long as they do not fully understand how AI reaches its conclusions, questions about the reliability of AI-driven decision-making will continue. Design/methodology/approach A qualitative secondary research approach, using content analysis of evidence collected from newspapers, research papers and recent books to critically compare AI-driven and traditional approaches to knowledge and decision-making. Findings The findings reveal that AI-driven decisions cannot be trusted blindly, as they may reinforce existing vulnerabilities and discrimination in society. Therefore, AI must be used mindfully, with continuous human oversight, transparency and accountability, to reduce rather than exacerbate disorder and inequality in the information society, while building public trust instead of creating fear. Originality/value The paper is original, offering a critical perspective on AI-driven decision-making, trust and the need for mindful human oversight in the information society.

Library Hi Tech News
Lovely Professional University (IN), Islamic University of Science and Technology (IN)
Openalex Percentile: Top 7%
Ethics and Social Impacts of AI
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Knowledge on trial: AI, trust and the future of decision-making — Saleeq Ahmad Dar, Hilal Ahmad Dar · Library Hi Tech News (2026) | TGRS Research Map | TGRS