Abstract
Advanced digitalization and other advanced technologies have proven their value to effectively address our social needs and have played a crucial role in the creation and transformation of society itself. Our daily life operates in an increasingly high-tech environment and revolutionize health provision, but also working conditions. Artificial intelligence (AI) related technologies can provide support at workplaces to compensate for the daily occupational dangers, reducing their impact on long-term worker health status. The purpose of this study is to identify relevant factors to improve long-term workability of aged workers that can be addressed through the use of new AI-based solutions, such as IoT, virtual reality, and interactive virtual coaches. In addition to a state-of-the-art research review, a set of workshop focus groups with the participation of middle-aged workers from different countries and an online European survey were conducted. An overview of the main factors that influence positive and negative on workability have emerged. This paper shows that factors in different working areas and how technology can provide skills and methods to cope with functional decline are relevant to improve workers’ workability as they age. Further research is necessary to propose effective technological-based solutions to address the identified results and measure their impact on worker’s long-term health.
This work has received funding from the European’s Union Horizon 2020 research and innovation programme under Grant Agreement No. 826299.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Furman, J., Seamans, R.: AI and the economy. Innov. Policy Econ. 19(1), 161–191 (2019)
Lasi, H., Fettke, P., Kemper, H.-G., Feld, T., Hoffmann, M.: Industry 4.0. Bus. Inf. Syst. Eng. 6(4), 239–242 (2014). https://doi.org/10.1007/s12599-014-0334-4
Manuti, A., Monachino, D.: Managing knowledge at the time of artificial intelligence: an explorative study with knowledge workers. East Eur. J. Psycholinguist. 7(2) (2020). https://doi.org/10.29038/eejpl.2020.7.2.man
Buzzelli, G.: Class structure and technological replaceability of the European workforce (2021)
Guerin, R.J., Castillo, D., Hendricks, K.J., Howard, J., Piacentino, J., Okun, A.H.: Preparing the future workforce for safe and healthy employment (2020)
Zarte, M., Pechmann, A., Nunes, I.: Principles for human-centered system design in Industry 4.0 – a systematic literature review. In: Nunes, I.L. (ed.) AHFE 2020. AISC, vol. 1207, pp. 140–147. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-51369-6_19
Giakoumis, D., Votis, K., Altsitsiadis, E., Segkouli, S., Paliokas, I., Tzovaras, D.: Smart, personalized and adaptive ICT solutions for active, healthy and productive ageing with enhanced workability. In: Proceedings of the 12th ACM International Conference on PErvasive Technologies Related to Assistive Environments, pp. 442–447, June 2019
Calzavara, M., Battini, D., Bogataj, D., Sgarbossa, F., Zennaro, I.: Ageing workforce management in manufacturing systems: state of the art and future research agenda. Int. J. Prod. Res. 58(3), 729–747 (2020)
Frandsen, T.F., Nielsen, M.F.B., Lindhardt, C.L., Eriksen, M.B.: Using the full PICO model as a search tool for systematic reviews resulted in lower recall for some PICO elements. J. Clin. Epidemiol. 127, 69–75 (2020)
Cabrita, M., op den Akker, H., Tabak, M., Hermens, H.J., Vollenbroek-Hutten, M.M.R.: Persuasive technology to support active and healthy ageing: an exploration of past, present, and future. J. Biomed. Inform. 84, 17–30 (2018). https://doi.org/10.1016/j.jbi.2018.06.010
Berg-Beckhoff, G., Nielsen, G., Ladekjær Larsen, E.: Use of information communication technology and stress, burnout, and mental health in older, middle-aged, and younger workers – results from a systematic review. Int. J. Occup. Environ. Health 23(2), 160–171 (2017). https://doi.org/10.1080/10773525.2018.1436015
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Abril-Jimenez, P., Cabrera-Umpierrez, M.F., Gonzalez, S., Carreton, R., Claassen, G., Arredondo Waldmeyer, M.T. (2022). Design of Human-Centered Adaptive Support Tools to Improve Workability in Older Workers. A Field of Research of Human-Centered AI. In: Antona, M., Stephanidis, C. (eds) Universal Access in Human-Computer Interaction. Novel Design Approaches and Technologies. HCII 2022. Lecture Notes in Computer Science, vol 13308. Springer, Cham. https://doi.org/10.1007/978-3-031-05028-2_11
Download citation
DOI: https://doi.org/10.1007/978-3-031-05028-2_11
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-05027-5
Online ISBN: 978-3-031-05028-2
eBook Packages: Computer ScienceComputer Science (R0)