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Accepted for/Published in: JMIR AI

Date Submitted: Jun 17, 2025
Date Accepted: Apr 2, 2026

The final, peer-reviewed published version of this preprint can be found here:

Human-AI Interaction in Low- and Middle-Income Countries: Qualitative Study of How Local Human Factors Influence AI Development and Deployment

Baka E, Krischer N, De Silva U, Tan YR, Yap P, Wong BLH

Human-AI Interaction in Low- and Middle-Income Countries: Qualitative Study of How Local Human Factors Influence AI Development and Deployment

JMIR AI 2026;5:e78649

DOI: 10.2196/78649

PMID: 42235072

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

Human-AI Interaction in Low- and Middle-Income Countries: How Local Human Factors Influence AI Development and Deployment

  • Evangelia Baka; 
  • Niklas Krischer; 
  • Udani De Silva; 
  • Yi-Roe Tan; 
  • Peiling Yap; 
  • Brian Li Han Wong

ABSTRACT

Artificial intelligence (AI) is rapidly transforming healthcare and health research, offering new opportunities for improving efficiency, accessibility, and equity. However, the ethical, societal, and regulatory challenges of AI development and deployment are particularly pronounced in low- and middle-income countries (LMICs). While existing literature often emphasises high-level ethical principles or technical frameworks, there is a notable gap in empirical, qualitative research that centers on human involvement and sociocultural dynamics throughout the AI lifecycle in LMIC contexts. This study addresses this gap by exploring the role of human involvement across the AI lifecycle, examining how cultural, societal, and governance factors influence AI perceptions and expectations in LMICs. Through 21 qualitative interviews with AI researchers and innovators across MENA, Africa, Latin America, and Asia, we identified five key themes: (1) the necessity of human oversight and the readiness required to support it, (2) the need for AI ethics training, (3) the importance of developing AI systems tailored to local realities, (4) the role of human-centered AI governance, and (5) the value of securing multidisciplinary teams. Findings highlight critical gaps in AI literacy, ethical governance, and interdisciplinary collaboration, emphasising that AI solutions must be co-designed with local communities to be culturally and contextually relevant. This study underscores the urgent need for participatory AI development in LMICs and calls for investment in AI education, ethical oversight, and inclusive governance frameworks to ensure that AI serves as a tool for social equity rather than exclusion.


 Citation

Please cite as:

Baka E, Krischer N, De Silva U, Tan YR, Yap P, Wong BLH

Human-AI Interaction in Low- and Middle-Income Countries: Qualitative Study of How Local Human Factors Influence AI Development and Deployment

JMIR AI 2026;5:e78649

DOI: 10.2196/78649

PMID: 42235072

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