Ethnographic approach reveals social dynamics affecting technology adoption in small-scale farming, indicating challenges within local society.
Purpose Research on trust in artificial intelligence (AI) focusses on particularized trust regarding specific technical designs in highly industrialized countries. The work presented here approaches trust in AI on a more general level using social systems theory. It investigates how system trust in a society affects the introduction of new AI devices. Design/methodology/approach To answer the research question, the study uses small-scale farming in Northern Africa as a revelatory case. The case is approached ethnographically through repetitive encounters with farmers in Morocco. Based on the documentation of these encounters, a narrative analysis is performed that allows a thick description of the subject matter. Findings The study identifies a dissonance between trust dynamics in local society and global application designs for digital technology. System trust evolves around AI devices, without addressing the underlying technology itself as a subject of institutional development. Instead, it is considered a kind of second nature to which society is exposed. Research limitations/implications The ethnographic approach gives insight into lived experience in one specific case through the lens of participant observers. It highlights the existence of existential challenges regarding trust in AI, which are likely to surface differently in different contexts, requiring further work to be conceptualized and understood in more detail. Originality/value The findings close an important gap in research on trust in AI. They unveil social dynamics in this domain that have so far been overlooked, but are likely to play an important role in innovation diffusion and technology adoption in developing countries, but also other scenarios of industrial transformation.
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Attoungbre et al. (2025) studied this question.
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