AI in Digital and Applied Humanities

Abstract

This conceptual paper examines how artificial intelligence (AI) reconfigures the conditions under which humanistic interpretation is performed in digital and applied humanities. Rather than presenting the study as primary phenomenological research, the revised article adopts a conceptual phenomenological approach informed by van Manen’s phenomenology of practice and by critical scholarship on algorithmic mediation. A purposive, interdisciplinary literature corpus is interpreted through four analytic dimensions: epistemology, ontology, ethics, and temporality. The central research question asks: How does AI-mediated inquiry alter the temporal, epistemic, relational, and ethical conditions of humanistic scholarship, and what forms of scholarly reflexivity are required in response? The analysis develops four linked concepts, temporal dissonance, the algorithmic unconscious, technological reflexivity, and relational ambiguity, to explain how machine-speed inference, opaque data histories, human–AI co-production, and asymmetrical agency reshape scholarly judgment. The paper also considers counterarguments concerning deskilling, loss of interpretive authority, labor displacement, cultural homogenization, and unequal access. It connects these concerns to information ethics, human-centered AI principles, UNESCO’s global ethics framework, and the European Union’s risk-based AI governance. The resulting framework argues neither for uncritical adoption nor categorical rejection of AI. Instead, it proposes a reflexive model in which AI can support discovery and collaboration while human scholars retain responsibility for interpretation, contextual judgment, source criticism, and ethical accountability.