Hybrid cognitive authority and algorithmic subjectivity: rethinking knowledge management in AI-driven communication
Abstract
Purpose: This paper aims to explore the transformative impact of generative artificial intelligence (AI) and human-computer interaction (HCI) on knowledge management in business, focusing on how AI-driven communication reshapes organizational practices. It examines the role of HCI in designing user-centric AI tools and introduces Hybrid Cognitive Authority (the co-construction of knowledge between human and AI agents) and Algorithmic Subjectivity (AI-generated communication simulating intent without cognition) to evaluate their effects on decision-making, knowledge flows and ethical governance in commercial settings. Design/methodology/approach: A mixed-methods approach integrates interdisciplinary genealogical analysis, qualitative case studies and critical discourse analysis. The study traces the evolution of commercial communication from mid-20th-century pragmatics to AI-mediated paradigms, synthesizing insights from cognitive science, information systems and digital epistemology. Five case studies of AI and HCI applications in business (e.g. customer service, recruitment) and discourse analysis of AI-generated artifacts provide empirical evidence for assessing knowledge management outcomes. Findings: Generative AI, supported by HCI, enhances knowledge management by improving efficiency and scalability, but raises challenges related to transparency, algorithmic bias and accountability. Empirical cases demonstrate how hybrid human-AI systems optimize knowledge processes while highlighting ethical risks, such as biased outputs. The proposed framework of Hybrid Cognitive Authority and Algorithmic Subjectivity necessitates governance models that balance AI automation with human oversight to maintain trust and interpretive agency. Originality/value: Unlike prior studies that view AI as a passive tool, this research positions AI as an active knowledge co-constructor, advancing knowledge management scholarship through the novel concepts of Hybrid Cognitive Authority and Algorithmic Subjectivity. It bridges theory and practice by offering actionable strategies for businesses to leverage AI and HCI responsibly, contributing to economic efficiency, ethical governance and societal trust in AI-driven communication.
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By translating governance domains into interface-level markers, such as corpus provenance indicators, model limitation notices, and human validation signals, platforms can recalibrate user reliance and resist the drift toward algorithmic subjectivity, where machine-generated outputs are tacitly treated as authoritative.
“By translating governance domains into interface-level markers, such as corpus provenance indicators, model limitation notices, and human validation signals, platforms can recalibrate user reliance and resist the drift toward algorithmic subjectivity, where machine-generated outputs are tacitly treated as authoritative [38].”
From Who speaks when machines read scripture: boundary-making and interpretive authority in AI-mediated religious knowledge (2026) · cites this paper as [38]
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- Authors
- Sun, Y., & Xu, C.
- Affiliations
- Beijing Institute of Petrochemical Technology (CN)
- Xi’an Jiaotong-Liverpool University (CN)
- Corresponding author
- Xu, Cheng
- ORCID
- Venue
- Journal of Knowledge Management
- Publisher
- Emerald
- Published
- 2025-10-28
- Volume
- 30
- Issue
- 8
- Pages
- 2741-2766
- ISSN
- 1367-3270 (ISSN-L)
- 1758-7484
- OpenAlex
- W4415504496
- Semantic Scholar
- 8b6ac826acfb1db245378ccfce19c7e619782b32
- Cited by
- 23
- References
- 38
- Citations by year
- 2026: 22 · 2025: 1
- FWCI
- 17.80
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Knowledge Management (publishedVersion)
- Funders
- Beijing Municipal Social Science Foundation (23JJC035)
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Knowledge Management and Technology
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
- Keywords
- generative AI, human-computer interaction, knowledge management, algorithmic bias, AI governance, human oversight, knowledge flows, business communication, customer service automation, recruitment automation, trust in AI
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