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This paper presents findings from an initial deployment of a readiness-centered Artificial Intelligence (AI) driven chatbot designed to support digital skilling amongst older adults in low-readiness settings. Building on Human-Centered Artificial Intelligence (HCAI) principles, the study introduces a readiness-centered reframing that adapts HCAI to account for users’ technological, cognitive and socio-cultural preparedness and tests this using a tool that integrated multilingual support, voice-based interactions and age-sensitive design. A cross-sectional study was conducted in urban and rural Kenyan counties, involving 388 participants using observational methods and semi-structured interviews to document user interactions. Thematic analysis revealed key barriers to adoption, including emotional discomfort, language-related confusion, usability breakdowns and cultural perceptions. These findings demonstrate that, while ethical design is necessary, it is not sufficient especially when foundational precursors like digital readiness, cognitive diversity and socio-cultural beliefs are not met. This study contributes by identifying critical gaps within the current HCAI framework and proposes a readiness-centered reframing that reorients design of AI systems around users’ actual capacities, cultural norms, and infrastructural realities. It introduces digital readiness assessment, cognitive scaffolding, and cultural usability as essential design pillars for AI systems that are not only ethical, but truly inclusive, usable and effective in low-readiness contexts.

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Readiness-Centered AI in Practice: Findings from a Pilot Chatbot for Digital Skilling of Older Adults in Low-Readiness Contexts

  • 会议论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年

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  • Anne Muchiri,
  • Joshua Rumo A. Ndiege,
  • Giannis Haralabopoulos,
  • Paula M. W. Musuva,
  • Paul Spiesberger

摘要

This paper presents findings from an initial deployment of a readiness-centered Artificial Intelligence (AI) driven chatbot designed to support digital skilling amongst older adults in low-readiness settings. Building on Human-Centered Artificial Intelligence (HCAI) principles, the study introduces a readiness-centered reframing that adapts HCAI to account for users’ technological, cognitive and socio-cultural preparedness and tests this using a tool that integrated multilingual support, voice-based interactions and age-sensitive design. A cross-sectional study was conducted in urban and rural Kenyan counties, involving 388 participants using observational methods and semi-structured interviews to document user interactions. Thematic analysis revealed key barriers to adoption, including emotional discomfort, language-related confusion, usability breakdowns and cultural perceptions. These findings demonstrate that, while ethical design is necessary, it is not sufficient especially when foundational precursors like digital readiness, cognitive diversity and socio-cultural beliefs are not met. This study contributes by identifying critical gaps within the current HCAI framework and proposes a readiness-centered reframing that reorients design of AI systems around users’ actual capacities, cultural norms, and infrastructural realities. It introduces digital readiness assessment, cognitive scaffolding, and cultural usability as essential design pillars for AI systems that are not only ethical, but truly inclusive, usable and effective in low-readiness contexts.