Towards a typology of epistemic relationships in human–AI interaction
DOI:
https://doi.org/10.47989/ir31iConf64143Keywords:
Epistemic relationship, Human-AI interaction (HAI) and collaboration, AI metaphor, Semi-structured interviewAbstract
Introduction. This study investigates how academics negotiate epistemic relationships (ERs) with artificial intelligence (AI) in research and teaching. We conceptualize ERs as the positioning of humans and AI in relation to knowledge, asking: What epistemic relationships emerge in researchers’ interactions with AI, and how are they enacted across academic knowledge practices?
Method. Semi-structured interviews were conducted in two independently collected datasets with 31 academics across regions and disciplines.
Analysis. We developed a five-dimensional codebook including three epistemic attributes (assessment perspective, trust type, human epistemic status) and two analytic devices (activities and metaphors). We refined the coding through iterative analysis and identified recurring patterns across participants’ accounts in both datasets.
Results. Five recognizable ER types emerged: Epistemic Abstention, Instrumental Reliance, Contingent Delegation, Co-agency Collaboration, and Authority Displacement. These types reflect variations in how participants assess and trust AI, position themselves epistemically, and embed AI in academic activities.
Conclusion(s). Our study contributes to conversations on information literacies and the ethical use of AI. We highlight the contingent and practice-dependent nature of ERs, suggesting a shift beyond static metaphors of AI toward a more nuanced account that captures the epistemic dimensions of human–AI knowledge co-construction.
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