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<p>Despite rapid advancements in machine learning (ML) technologies, their application toward promoting inclusive employment for persons with disabilities (PwDs) remains fragmented, with limited understanding of global research trends, practical forecasting tools, and ethical frameworks guiding responsible AI deployment in this domain. This study addresses these critical gaps by conducting the first comprehensive bibliometric analysis of ML research related to disability and inclusive employment from 2014 to 2023, uncovering global patterns of productivity, collaboration, and thematic development. It further develops a robust ML-based forecasting model to accurately predict employment trends among individuals with hearing disabilities in India, a largely underrepresented population in current research. Additionally, the study proposes two novel conceptual frameworks—the AI for Inclusive Employment Ecosystem and the Ethics–Inclusion–Impact (EII) Framework—to provide actionable, participatory, and ethically grounded guidance for deploying AI systems that support inclusive workplaces. By integrating bibliometric insights, empirical modeling, and conceptual innovation, this work fills a significant scholarly void, advancing knowledge and practice toward equitable, human-centered AI-driven employment solutions aligned with Sustainable Development Goals and Industry 5.0 principles.</p>

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AI-enabled inclusive employment in industry 5.0 bibliometric trends and forecasting for persons with hearing disability

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年5月24日

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  • Amardeep Yadav,
  • Sanchana P. Thomas,
  • A. P. Pavithra,
  • T. R. Krishnaprasad,
  • Manoj Pokkiyarath

摘要

Despite rapid advancements in machine learning (ML) technologies, their application toward promoting inclusive employment for persons with disabilities (PwDs) remains fragmented, with limited understanding of global research trends, practical forecasting tools, and ethical frameworks guiding responsible AI deployment in this domain. This study addresses these critical gaps by conducting the first comprehensive bibliometric analysis of ML research related to disability and inclusive employment from 2014 to 2023, uncovering global patterns of productivity, collaboration, and thematic development. It further develops a robust ML-based forecasting model to accurately predict employment trends among individuals with hearing disabilities in India, a largely underrepresented population in current research. Additionally, the study proposes two novel conceptual frameworks—the AI for Inclusive Employment Ecosystem and the Ethics–Inclusion–Impact (EII) Framework—to provide actionable, participatory, and ethically grounded guidance for deploying AI systems that support inclusive workplaces. By integrating bibliometric insights, empirical modeling, and conceptual innovation, this work fills a significant scholarly void, advancing knowledge and practice toward equitable, human-centered AI-driven employment solutions aligned with Sustainable Development Goals and Industry 5.0 principles.