Paper Title
ADAPTING TO TECHNOLOGICAL UNPLOYMENT: STRATEGIES FOR JOB DISPLACEMENT CAUSED BY AI
Article Identifiers
Authors
Lamin D. Kinteh
Keywords
Artificial intelligence, Job displacement, Workforce resilience, Adaptive strategies, Reskilling, Upskilling, Policy interventions, Entrepreneurship, Societal adaptation, Technological disruption, Empowerment.
Abstract
The rapid integration of artificial intelligence (AI) technologies into various industries poses significant challenges to the labor market, potentially leading to widespread job displacement. This research paper endeavors to explore comprehensive strategies aimed at accommodating the inevitable shift caused by AI-driven automation. Drawing upon a synthesis of scholarly literature, empirical studies, and expert insights, this paper examines the multifaceted implications of AI-induced job displacement and proposes adaptive measures to mitigate adverse effects while fostering empowerment and resilience within the workforce. The paper first elucidates the underlying dynamics of AI-induced job displacement, delineating the mechanisms through which automation disrupts traditional employment structures. It delves into the nuanced factors contributing to job displacement, ranging from technological advancements to economic imperatives and organizational dynamics. By understanding the root causes and patterns of displacement, stakeholders can better devise targeted interventions to address the ensuing challenges. Subsequently, the paper scrutinizes the multifaceted implications of AI-induced displacement on the workforce, encompassing socioeconomic repercussions, psychological impacts, and structural transformations within the labor market. It underscores the imperative of proactive adaptation and highlights the urgency of implementing tailored strategies to mitigate the adverse effects on affected individuals and communities. The core of the paper revolves around the proposition and exploration of adaptive strategies to accommodate AI-induced job displacement comprehensively. This includes a multifaceted approach encompassing reskilling and upskilling initiatives tailored to emerging skill demands, policy interventions aimed at facilitating smooth transitions and providing adequate support mechanisms for displaced workers, and fostering entrepreneurship and innovation as pathways to new economic opportunities. Moreover, the paper advocates for the reevaluation of societal perceptions surrounding work and value, emphasizing the need for inclusive and equitable frameworks that recognize diverse forms of contribution and redefine success beyond traditional employment paradigms. By examining successful case studies and best practices from various sectors and jurisdictions, the paper distills actionable insights and lessons learned, providing practical guidance for policymakers, employers, educators, and individuals navigating the complex landscape of AI-induced job displacement. Ultimately, the paper underscores the importance of proactive adaptation, collaborative action, and human-centric approaches in harnessing the transformative potential of AI while safeguarding the well-being and resilience of the workforce in an era of technological disruption.
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How To Cite (APA)
Lamin D. Kinteh (May-2024). ADAPTING TO TECHNOLOGICAL UNPLOYMENT: STRATEGIES FOR JOB DISPLACEMENT CAUSED BY AI. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(5), a934-a943. https://ijnrd.org/papers/IJNRD2405099.pdf
Issue
Volume 9 Issue 5, May-2024
Pages : a934-a943
Other Publication Details
Paper Reg. ID: IJNRD_220522
Published Paper Id: IJNRD2405099
Downloads: 000121995
Research Area: Computer Science & TechnologyÂ
Country: Raipur, Chhattisgarh, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2405099.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2405099
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Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)
ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016
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This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition
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