HUMAN-CENTRED EXPLAINABLE AI IN EMERGING MARKETS: TRUST AND CONFIDENCE AMONG NON-TECHNICAL USERS IN PAKISTAN

Abstract

Building user confidence through explainable artificial intelligence (XAI) in non-technical sectors, specifically in the country of Pakistan, is the focus of this research. It seeks to assess the implications of AI system explainability and the influence of trust and understanding on professional acceptance in mainstream use. The qualitative research design involved semi-structured interviews as a means of gathering data from the four sectors of education and healthcare, finance, and public administration, and XAI in these sectors in Pakistan. Participants involved in the research were twelve in number. Thematic analysis was conducted on the perceptions and experiences to evaluate the increasing trust and confidence in the XAI tools.

User confidence depends on the extent to which the clarity, relevance, and transparency of AI explanations are evaluative. When explanations were intuitive and articulated in human-centered ways, trust and participation were high. Confidence and participation, on the other hand, were limited if the explanations were convoluted and impenetrable. These included trust and transparency, human-centered design, cognitive ease, specific domains, and ethical constraints. Different from the other studies, this study explains that the psychological and contextual aspects are equally important in user trust and must be incorporated into explainability beyond the technical aspects of XAI tools. This study underscores the importance of resilient, culturally appropriate systems in which XAI tools focus on a balance between explainability and automation. Such design practices will improve trust and transparency of human–AI interactions in the emerging markets of Pakistan.