IDEAS home Printed from https://ideas.repec.org/a/ddj/fseeai/y2024i3p275-285.html
   My bibliography  Save this article

Navigating the Challenges and Ethics of AI in Shaping the Future of Work for Sustainable Industry 4.0

Author

Listed:
  • Mioara Chirita

    (Dunarea de Jos University of Galati, Romania)

  • Daniela-Ancuta Sarpe

    (Dunarea de Jos University of Galati, Romania)

Abstract

The rapid advancement of artificial intelligence (AI) is fundamentally transforming industrial sectors, driving the evolution of labor markets, and significantly reshaping economic structures. Within the paradigm of Industry 4.0, which is defined by the integration of AI, automation, and data analytics, substantial gains in operational efficiency, productivity, and innovation have been realized. However, the widespread deployment of AI technologies in workforce management raises pressing challenges, particularly in the realms of ethics, employment dynamics, and socio-economic impacts. This paper critically examines the ethical issues arising from AI adoption in Industry 4.0, with a focus on its implications for sustainable economic growth. The research delves into the pivotal role of AI in optimizing processes across manufacturing, logistics, and service industries, while also addressing critical concerns such as workforce displacement, data privacy, and algorithmic biases. The shift towards increased automation, though contributing to enhanced efficiency and competitiveness, necessitates a comprehensive reevaluation of labor market structures and the re-skilling of human capital. This paper underscores the importance of developing robust ethical frameworks that ensure AI deployment serves societal well-being, upholding human dignity and fostering equitable labor market opportunities. Beyond the technological challenges, the paper also explores the potential of AI to promote sustainable practices within Industry 4.0. It investigates how AI can be leveraged to reduce environmental impacts, optimize resource utilization, and drive innovation in sustainable technologies. Ethical dimensions such as transparency, accountability, and the mitigation of the digital divide are critically examined, ensuring that AI advancements are aligned with the broader goals of sustainable development. This study aims to provide a comprehensive analysis of the intersection between AI, labor markets, and ethical considerations within the context of Industry 4.0, offering valuable insights for policymakers, business leaders, and technologists to navigate the challenges of shaping a sustainable and inclusive future of work.

Suggested Citation

  • Mioara Chirita & Daniela-Ancuta Sarpe, 2024. "Navigating the Challenges and Ethics of AI in Shaping the Future of Work for Sustainable Industry 4.0," Economics and Applied Informatics, "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration, issue 3, pages 275-285.
    • Handle: RePEc:ddj:fseeai:y:2024:i:3:p:275-285
    DOI: https://doi.org/10.35219/eai15840409453
    as

    Download full text from publisher

    File URL: http://eia.feaa.ugal.ro/images/eia/2024_3/Chirita_Sarpe.pdf
    Download Restriction: no
    File URL: https://libkey.io/https://doi.org/10.35219/eai15840409453?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Ioannis Bellos & Mark Ferguson & L. Beril Toktay, 2017. "The Car Sharing Economy: Interaction of Business Model Choice and Product Line Design," Manufacturing & Service Operations Management, INFORMS, vol. 19(2), pages 185-201, May.
    2. Ricardo Vinuesa & Hossein Azizpour & Iolanda Leite & Madeline Balaam & Virginia Dignum & Sami Domisch & Anna Felländer & Simone Daniela Langhans & Max Tegmark & Francesco Fuso Nerini, 2020. "The role of artificial intelligence in achieving the Sustainable Development Goals," Nature Communications, Nature, vol. 11(1), pages 1-10, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jiang, Kai & Xin, Baogui & Santibanez Gonzalez, Ernesto D.R., 2025. "Can industrial intelligence promote net-zero development? An analysis of resource dependence," The North American Journal of Economics and Finance, Elsevier, vol. 78(C).
    2. Maryna Henrysson & Ranjula Bali Swain & Ashok Swain & Francesco Fuso Nerini, 2024. "Sustainable Development Goals and wellbeing for resilient societies: shocks and recovery," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-13, December.
    3. Henrik Skaug Sætra, 2021. "AI in Context and the Sustainable Development Goals: Factoring in the Unsustainability of the Sociotechnical System," Sustainability, MDPI, vol. 13(4), pages 1-19, February.
    4. Xi Liu & Yugang He & Renhong Wu, 2024. "Revolutionizing Environmental Sustainability: The Role of Renewable Energy Consumption and Environmental Technologies in OECD Countries," Energies, MDPI, vol. 17(2), pages 1-21, January.
    5. Wells, Peter & Wang, Xiaobei & Wang, Liqiao & Liu, Haokun & Orsato, Renato, 2020. "More friends than foes? The impact of automobility-as-a-service on the incumbent automotive industry," Technological Forecasting and Social Change, Elsevier, vol. 154(C).
    6. Aurélie Halsband, 2022. "Sustainable AI and Intergenerational Justice," Sustainability, MDPI, vol. 14(7), pages 1-11, March.
    7. Wilson, Christopher & van der Velden, Maja, 2022. "Sustainable AI: An integrated model to guide public sector decision-making," Technology in Society, Elsevier, vol. 68(C).
    8. Stéphanie Camaréna, 2021. "Engaging with Artificial Intelligence (AI) with a Bottom-Up Approach for the Purpose of Sustainability: Victorian Farmers Market Association, Melbourne Australia," Sustainability, MDPI, vol. 13(16), pages 1-28, August.
    9. Simon Ofori Ametepey & Clinton Aigbavboa & Wellington Didibhuku Thwala & Hutton Addy, 2024. "The Impact of AI in Sustainable Development Goal Implementation: A Delphi Study," Sustainability, MDPI, vol. 16(9), pages 1-76, May.
    10. Jinyi Li & Zhen Liu & Guizhong Han & Peter Demian & Mohamed Osmani, 2024. "The Relationship Between Artificial Intelligence (AI) and Building Information Modeling (BIM) Technologies for Sustainable Building in the Context of Smart Cities," Sustainability, MDPI, vol. 16(24), pages 1-38, December.
    11. Keeheon Lee, 2021. "A Systematic Review on Social Sustainability of Artificial Intelligence in Product Design," Sustainability, MDPI, vol. 13(5), pages 1-29, March.
    12. Gianluca MISURACA & Colin van Noordt, 2020. "AI Watch - Artificial Intelligence in public services: Overview of the use and impact of AI in public services in the EU," JRC Research Reports JRC120399, Joint Research Centre.
    13. Lee, Chien-Chiang & Zou, Jinyang & Chen, Pei-Fen, 2025. "The impact of artificial intelligence on the energy consumption of corporations: The role of human capital," Energy Economics, Elsevier, vol. 143(C).
    14. Raghu Raman & Ricardo Vinuesa & Prema Nedungadi, 2021. "Bibliometric Analysis of SARS, MERS, and COVID-19 Studies from India and Connection to Sustainable Development Goals," Sustainability, MDPI, vol. 13(14), pages 1-20, July.
    15. Ancín, María & Pindado, Emilio & Sánchez, Mercedes, 2022. "New trends in the global digital transformation process of the agri-food sector: An exploratory study based on Twitter," Agricultural Systems, Elsevier, vol. 203(C).
    16. Martins, Flavio Pinheiro & De-León Almaraz, Sofía & Botelho Junior, Amilton Barbosa & Azzaro-Pantel, Catherine & Parikh, Priti, 2024. "Hydrogen and the sustainable development goals: Synergies and trade-offs," Renewable and Sustainable Energy Reviews, Elsevier, vol. 204(C).
    17. Liu, Liang & Yang, Kun & Fujii, Hidemichi & Liu, Jun, 2021. "Artificial intelligence and energy intensity in China’s industrial sector: Effect and transmission channel," Economic Analysis and Policy, Elsevier, vol. 70(C), pages 276-293.
    18. Zhao, Qian & Wang, Lu & Stan, Sebastian-Emanuel & Mirza, Nawazish, 2024. "Can artificial intelligence help accelerate the transition to renewable energy?," Energy Economics, Elsevier, vol. 134(C).
    19. D’Amico, Gaspare & Arbolino, Roberta & Shi, Lei & Yigitcanlar, Tan & Ioppolo, Giuseppe, 2022. "Digitalisation driven urban metabolism circularity: A review and analysis of circular city initiatives," Land Use Policy, Elsevier, vol. 112(C).
    20. Hao, Wu & Martin, Layla, 2022. "Prohibiting cherry-picking: Regulating vehicle sharing services who determine fleet and service structure," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 161(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ddj:fseeai:y:2024:i:3:p:275-285. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Gianina Mihai (email available below). General contact details of provider: https://edirc.repec.org/data/fegalro.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.