Too often, companies believe that the main challenge amid the era of artificial intelligence (AI) is responding to employees’ fears of being replaced, but our recent study found there might be something more concerning than the idea of workers being replaced by machines.
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Focusing on how retail workers experience working alongside automated technology, we found that they see the machine as the preferred, ideal worker for customers.
By devaluing their assets, such as the ability to connect with people, they came to experience what we coined a ‘techno-induced feeling of being less able’ (TIFLA).
The consequence of this ranged from performance-related issues to lowered morale and resentment.
Countering the TIFLA feeling is essential to encourage higher degrees of collaboration between humans and technology. Especially with the advent of AI, companies would need to keep workers motivated and help them build and maintain trust in technology.
What we believe is missing to date, is an approach managers can use to guide them when implementing new technologies.
To support businesses in the retail and service sector to addressing the potential negative psycho-social effects associated with technological transformations, we propose an approach deemed CoDE (concerted diagnosis and engagement with customers).
This CoDE aims to stimulate workers' participation by boosting human self-worth through a celebration of social capabilities, and their potential to contribute to an enhanced customer experience.
We break down this CoDE in three easy steps:
Collect feedback
We recommend that HR managers introduce a workers' self-assessment on how they experience working alongside new technologies.
This assessment will focus on their experience associated with the core tasks in the usual role description (before introduction of new technology).
The assessment would ensure that HR has relevant data to compare before and after the introduction of new tech.
Indeed, our study highlighted that workers are not particularly reluctant to new approaches. They may, however, experience deep self-doubt when a valued aspect of their professional role is eliminated.
Such a diagnosis would help ensure that the tech transition does not miss factors that matter to employees.
Collaborate in the choice of tech
If possible, allowing workers to choose aspects related to how the technology is implemented will allow them to feel involved in this decision while appreciating the powerful message it conveys: that they are and remain part of the future of work.
This alleviates workers' sense of enduring the technology, rather than working with it, as a factor for rejecting technology.
Celebrate human qualities
We suggest HR managers create a pool of 'humanising assets' – aspects of work valued by both workers and customers. These aspects would become the basis of tasks that create high-quality interactions with customers and enhance the clients' overall experience. They will also contribute to social recognition objectives for employees.
So, if it makes sense to ask workers to acquire new technological skills, becoming a techie won't be enough. We believe that the critical challenge for HR to truly succeed in building a sustainable world of work may be helping workers discover their 'humane powers'.
Kamila Moulaï is Marie Sklodowska Curie Postdoc Fellow and pstdoc at Rotterdam School of Management.
Newton Howard is professor of computational neurology and neurosurgery at the University of Oxford and the founder and director of the Oxford Computational Neuroscience Lab
This piece features findings from the research paper “All too human or the emergence of a techno-induced feeling of being less-able: identity work, ableism and new service” published in The International Journal of Human Resource Management, 1-32 (2022). The research was authored by Moulaï, K., Islam, G., Manning, S., & Terlinden, L.
It also builds on findings (for the practical recommendations) from my following research paper on AI. Reference : Moulaï, K. and Islam, G. (2022) "Artificial Intelligence and performance beyond the organizational matrix". RESP-AI. in: CRIMT International Proceedings.
