Qualitative conceptual analysis demonstrates how dialogue and motivational needs shape human-AI interaction, indicating new directions for designing relational technologies.
This study examines how human-AI relationships can be reinterpreted through a dialogue-centred perspective within the framework of Human-Computer Interaction (HCI). Building on Bødker’s three waves of HCI, we trace the evolving role of the human from a cognitive “factor” to an intentional “actor,” and ultimately to a relational agent embedded in socio-technical contexts. While early approaches focused on usability and error reduction, later paradigms acknowledged emotions, goals, and lived experiences. In the third wave, interaction is recognised as emergent, situated, and relational, shaped through ongoing negotiation between humans and non-human agents.We propose that dialogue offers a productive lens to understand and design these relationships. Dialogue here refers not only to language but also to how meaning, form, behaviour, and responsiveness are cocreated during interaction. To analyse how such dialogic relations develop, the study adopts a motivation-based analytical approach, drawing on Maslow’s hierarchy of needs as a framework for understanding how unmet needs activate engagement and shape user expectations. Through a qualitative analysis of selected human – AI interaction examples, we explore which needs are addressed and what relational outcomes emerge. By combining theoretical insight with motivational analysis, this work aims to inform future design practices that support more meaningful human-AI relations. Methodologically, the study employs a qualitative, theory-driven analysis of selected human–AI interaction cases examined through Maslow’s hierarchy of needs to identify how different motivational layers shape dialogic relationships.
No takes yet. Share an insight, caveat, or question.
Altıparmakoğulları et al. (2026) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: