From realism and socio-cognitivism to AI constructs: enhancing domain analysis through artificial intelligence?

Abstract

Introduction. This study explores the integration of artificial intelligence (AI) within the framework of domain analysis (DA), traditionally grounded in socio-cognitive and realist perspectives. The aim is to assess AI's potential to enhance DA's focus on contextual and disciplinary knowledge, while examining possible epistemological challenges.

Method. Building on established concepts from Hjørland’s socio-cognitive DA framework, this paper employs a theoretical review to examine AI's capacity to augment DA by improving classification, retrieval and interdisciplinary mapping within knowledge organisation.

Analysis. The study critically analyses how AI may either enhance or disrupt DA’s philosophical foundations by potentially reducing domain specificity. Particular attention is given to AI's tendency toward generalisation, which could dilute DA's contextual sensitivity.

Results. The findings suggest that while AI has transformative potentials for DA, there is a risk of oversimplifying epistemic structures. AI could reorient DA towards machine-centric interpretations, limiting DA’s capacity to accommodate complex, domain-specific nuances.

Conclusions. The paper concludes that AI can benefit DA if carefully integrated, respecting its epistemological depth. Future research should focus on developing AI approaches that enhance DA without undermining its socio-cognitive foundations.