IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v18y2021i13p6705-d579589.html
   My bibliography  Save this article

REDECA: A Novel Framework to Review Artificial Intelligence and Its Applications in Occupational Safety and Health

Author

Listed:
  • Maryam Pishgar

    (Mechanical and Industrial Engineering, University of Illinois at Chicago, Chicago, IL 60609, USA)

  • Salah Fuad Issa

    (Agricultural and Biological Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA)

  • Margaret Sietsema

    (Environmental and Occupational Health Sciences, University of Illinois at Chicago, Chicago, IL 60612, USA)

  • Preethi Pratap

    (Environmental and Occupational Health Sciences, University of Illinois at Chicago, Chicago, IL 60612, USA)

  • Houshang Darabi

    (Mechanical and Industrial Engineering, University of Illinois at Chicago, Chicago, IL 60609, USA)

Abstract

Introduction: The field of artificial intelligence (AI) is rapidly expanding, with many applications seen routinely in health care, industry, and education, and increasingly in workplaces. Although there is growing evidence of applications of AI in workplaces across all industries to simplify and/or automate tasks there is a limited understanding of the role that AI contributes in addressing occupational safety and health (OSH) concerns. Methods: This paper introduces a new framework called Risk Evolution, Detection, Evaluation, and Control of Accidents (REDECA) that highlights the role that AI plays in the anticipation and control of exposure risks in a worker’s immediate environment. Two hundred and sixty AI papers across five sectors (oil and gas, mining, transportation, construction, and agriculture) were reviewed using the REDECA framework to highlight current applications and gaps in OSH and AI fields. Results: The REDECA framework highlighted the unique attributes and research focus of each of the five industrial sectors. The majority of evidence of AI in OSH research within the oil/gas and transportation sectors focused on the development of sensors to detect hazardous situations. In construction the focus was on the use of sensors to detect incidents. The research in the agriculture sector focused on sensors and actuators that removed workers from hazardous conditions. Application of the REDECA framework highlighted AI/OSH strengths and opportunities in various industries and potential areas for collaboration. Conclusions: As AI applications across industries continue to increase, further exploration of the benefits and challenges of AI applications in OSH is needed to optimally protect worker health, safety and well-being.

Suggested Citation

  • Maryam Pishgar & Salah Fuad Issa & Margaret Sietsema & Preethi Pratap & Houshang Darabi, 2021. "REDECA: A Novel Framework to Review Artificial Intelligence and Its Applications in Occupational Safety and Health," IJERPH, MDPI, vol. 18(13), pages 1-42, June.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:13:p:6705-:d:579589
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/18/13/6705/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/18/13/6705/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. J�rgen Melzner & Sijie Zhang & Jochen Teizer & Hans-Joachim Bargst�dt, 2013. "A case study on automated safety compliance checking to assist fall protection design and planning in building information models," Construction Management and Economics, Taylor & Francis Journals, vol. 31(6), pages 661-674, June.
    2. Anurag Yedla & Fatemeh Davoudi Kakhki & Ali Jannesari, 2020. "Predictive Modeling for Occupational Safety Outcomes and Days Away from Work Analysis in Mining Operations," IJERPH, MDPI, vol. 17(19), pages 1-17, September.
    3. Anna Dubois & Lars-Erik Gadde, 2002. "The construction industry as a loosely coupled system: implications for productivity and innovation," Construction Management and Economics, Taylor & Francis Journals, vol. 20(7), pages 621-631.
    4. Christos A. Damalas & Ilias G. Eleftherohorinos, 2011. "Pesticide Exposure, Safety Issues, and Risk Assessment Indicators," IJERPH, MDPI, vol. 8(5), pages 1-18, May.
    5. Mokhinabonu Mardonova & Yosoon Choi, 2018. "Review of Wearable Device Technology and Its Applications to the Mining Industry," Energies, MDPI, vol. 11(3), pages 1-14, March.
    6. Guha, Abhijit & Grewal, Dhruv & Kopalle, Praveen K. & Haenlein, Michael & Schneider, Matthew J. & Jung, Hyunseok & Moustafa, Rida & Hegde, Dinesh R. & Hawkins, Gary, 2021. "How artificial intelligence will affect the future of retailing," Journal of Retailing, Elsevier, vol. 97(1), pages 28-41.
    7. Thomas Davenport & Abhijit Guha & Dhruv Grewal & Timna Bressgott, 2020. "How artificial intelligence will change the future of marketing," Journal of the Academy of Marketing Science, Springer, vol. 48(1), pages 24-42, January.
    8. Iain M. Cockburn & Rebecca Henderson & Scott Stern, 2018. "The Impact of Artificial Intelligence on Innovation," NBER Working Papers 24449, National Bureau of Economic Research, Inc.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mauricio A. Ramírez-Moreno & Patricio Carrillo-Tijerina & Milton Osiel Candela-Leal & Myriam Alanis-Espinosa & Juan Carlos Tudón-Martínez & Armando Roman-Flores & Ricardo A. Ramírez-Mendoza & Jorge de, 2021. "Evaluation of a Fast Test Based on Biometric Signals to Assess Mental Fatigue at the Workplace—A Pilot Study," IJERPH, MDPI, vol. 18(22), pages 1-20, November.
    2. Elizabeth Fisher & Michael A. Flynn & Preethi Pratap & Jay A. Vietas, 2023. "Occupational Safety and Health Equity Impacts of Artificial Intelligence: A Scoping Review," IJERPH, MDPI, vol. 20(13), pages 1-28, June.
    3. Sara L. Tamers & Jessica M. K. Streit & Casey Chosewood, 2022. "Promising Occupational Safety, Health, and Well-Being Approaches to Explore the Future of Work in the USA: An Editorial," IJERPH, MDPI, vol. 19(3), pages 1-7, February.
    4. Joana Duarte & Fernanda Rodrigues & Jacqueline Castelo Branco, 2022. "Sensing Technology Applications in the Mining Industry—A Systematic Review," IJERPH, MDPI, vol. 19(4), pages 1-16, February.
    5. Matt Comi & Florence Becot & Casper Bendixsen, 2023. "Automation, Climate Change, and the Future of Farm Work: Cross-Disciplinary Lessons for Studying Dynamic Changes in Agricultural Health and Safety," IJERPH, MDPI, vol. 20(6), pages 1-15, March.

    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. Leah Warfield Smith & Randall Lee Rose & Alex R. Zablah & Heath McCullough & Mohammad “Mike” Saljoughian, 2023. "Examining post-purchase consumer responses to product automation," Journal of the Academy of Marketing Science, Springer, vol. 51(3), pages 530-550, May.
    2. Abhijit Guha & Dhruv Grewal, 2022. "How robots will affect the future of retailing," AMS Review, Springer;Academy of Marketing Science, vol. 12(3), pages 245-252, December.
    3. Pantano, Eleonora & Viassone, Milena & Boardman, Rosy & Dennis, Charles, 2022. "Inclusive or exclusive? Investigating how retail technology can reduce old consumers’ barriers to shopping," Journal of Retailing and Consumer Services, Elsevier, vol. 68(C).
    4. Jabeur, Sami Ben & Ballouk, Houssein & Mefteh-Wali, Salma & Omri, Anis, 2022. "Forecasting the macrolevel determinants of entrepreneurial opportunities using artificial intelligence models," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    5. Shankar, Venkatesh & Kalyanam, Kirthi & Setia, Pankaj & Golmohammadi, Alireza & Tirunillai, Seshadri & Douglass, Tom & Hennessey, John & Bull, J.S. & Waddoups, Rand, 2021. "How Technology is Changing Retail," Journal of Retailing, Elsevier, vol. 97(1), pages 13-27.
    6. Sagarika Mishra & Michael T. Ewing & Holly B. Cooper, 2022. "Artificial intelligence focus and firm performance," Journal of the Academy of Marketing Science, Springer, vol. 50(6), pages 1176-1197, November.
    7. Navid Bahmani & Amit Bhatnagar & Dinesh Gauri, 2022. "Hey, Alexa! What attributes of Skills affect firm value?," Journal of the Academy of Marketing Science, Springer, vol. 50(6), pages 1219-1235, November.
    8. Stephanie M. Noble & Martin Mende, 2023. "The future of artificial intelligence and robotics in the retail and service sector: Sketching the field of consumer-robot-experiences," Journal of the Academy of Marketing Science, Springer, vol. 51(4), pages 747-756, July.
    9. Marilyn Giroux & Jungkeun Kim & Jacob C. Lee & Jongwon Park, 2022. "Artificial Intelligence and Declined Guilt: Retailing Morality Comparison Between Human and AI," Journal of Business Ethics, Springer, vol. 178(4), pages 1027-1041, July.
    10. Grewal, Dhruv & Guha, Abhijit & Satornino, Cinthia B. & Schweiger, Elisa B., 2021. "Artificial intelligence: The light and the darkness," Journal of Business Research, Elsevier, vol. 136(C), pages 229-236.
    11. Erik Hermann, 2022. "Leveraging Artificial Intelligence in Marketing for Social Good—An Ethical Perspective," Journal of Business Ethics, Springer, vol. 179(1), pages 43-61, August.
    12. Yuping Liu-Thompkins & Shintaro Okazaki & Hairong Li, 2022. "Artificial empathy in marketing interactions: Bridging the human-AI gap in affective and social customer experience," Journal of the Academy of Marketing Science, Springer, vol. 50(6), pages 1198-1218, November.
    13. Satornino, Cinthia B. & Grewal, Dhruv & Guha, Abhijit & Schweiger, Elisa B. & Goodstein, Ronald C., 2023. "The perks and perils of artificial intelligence use in lateral exchange markets," Journal of Business Research, Elsevier, vol. 158(C).
    14. van Giffen, Benjamin & Herhausen, Dennis & Fahse, Tobias, 2022. "Overcoming the pitfalls and perils of algorithms: A classification of machine learning biases and mitigation methods," Journal of Business Research, Elsevier, vol. 144(C), pages 93-106.
    15. Huang, Ming-Hui & Rust, Roland T., 2022. "A Framework for Collaborative Artificial Intelligence in Marketing," Journal of Retailing, Elsevier, vol. 98(2), pages 209-223.
    16. Francesca Bonetti & Matteo Montecchi & Kirk Plangger & Hope Jensen Schau, 2023. "Practice co-evolution: Collaboratively embedding artificial intelligence in retail practices," Journal of the Academy of Marketing Science, Springer, vol. 51(4), pages 867-888, July.
    17. Darima Fotheringham & Michael A. Wiles, 2023. "The effect of implementing chatbot customer service on stock returns: an event study analysis," Journal of the Academy of Marketing Science, Springer, vol. 51(4), pages 802-822, July.
    18. Christian Rammer & Gastón P Fernández & Dirk Czarnitzki, 2021. "Artificial Intelligence and Industrial Innovation: Evidence from Firm-Level Data," Working Papers of Department of Economics, Leuven 674605, KU Leuven, Faculty of Economics and Business (FEB), Department of Economics, Leuven.
    19. Yong‐Shik Lee, 2020. "New general theory of economic development: Innovative growth and distribution," Review of Development Economics, Wiley Blackwell, vol. 24(2), pages 402-423, May.
    20. Mingyue Li & Jingjing Wang & Kai Chen & Lianbei Wu, 2020. "Willingness and Behaviors of Farmers’ Green Disposal of Pesticide Packaging Waste in Henan, China: A Perceived Value Formation Mechanism Perspective," IJERPH, MDPI, vol. 17(11), pages 1-18, May.

    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:gam:jijerp:v:18:y:2021:i:13:p:6705-:d:579589. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.