Résumés
Summary
With the development of artificial intelligence (AI) and its applications, such as learning algorithms, it seems likely that work and organization will be profoundly reshaped. While this subject has been debated in broad terms (Arntz et al., 2016; Brynjolfsson & McAfee, 2014; Faraj et al., 2018), little has been written specifically from the perspective of employees (Phan et al., 2017). Little is known about the impact of AI on their work experiences and how they may respond. In a qualitative study of 27 bank employees, we investigated how learning algorithms shaped working conditions, how they affected autonomy and the meaning of work and how these constructs changed over time. The employees responded to the changes through job crafting behaviours (Wrzesniewski & Dutton, 2001). By considering the effects of the learning algorithms on the employees’ work experiences from their perspective, we offer a novel application of job crafting theory to AI technology. The employees responded to AI by changing task and relationship boundaries, and cognitively reframed their jobs. Their job crafting behaviours can be interpreted broadly as attempts to rebalance their levels of autonomy (which were initially reduced by the introduction of AI), to move toward closer personal relationships with customers and to reposition their meaning of work. In general, employees’ job crafting also had implications for employees’ managers, customers, and their work context in terms of the meaning of the AI tools and how they were used. Employees’ concerted response across the three job crafting dimensions underlines the importance of synergy across job crafting dimensions if they are to be successful in altering employees’ experience of work and enhancing the human value of their services.
Abstract
In this qualitative study of 27 bank employees, we investigated how learning algorithms affected their working conditions, their autonomy and the meaning of their work. We show that employees responded to the AI-induced changes through job crafting behaviours (Wrzesniewski & Dutton, 2001). Employees reshaped their task and relationship boundaries, and cognitively reframed their jobs, to maintain their autonomy, their desired social relationships and the meaning of their work. By considering the effects of learning algorithms on the employees’ work experience from their perspective, we provide a novel application of job crafting theory. Employees’ concerted response across the three job crafting dimensions underlines the importance of synergy across job crafting dimensions if they are to be successful in altering employees’ experience of work and enhancing the human value of their services.
Keywords:
- artificial intelligence,
- algorithms,
- job crafting,
- job redesign,
- banking
Résumé
Le développement de l'intelligence artificielle (IA) et de ses techniques telles que les algorithmes d'apprentissage peuvent profondément façonner le travail et l’organisation. Bien cela ait été débattu (Arntz et al., 2016 ; Brynjolfsson & McAfee, 2014 ; Faraj et al., 2018), il y a eu peu de recherches spécifiques du point de vue des employés (Phan et al., 2017). On sait peu de choses sur l’impact de l’IA sur les expériences de travail des employés et la façon dont ils peuvent réagir.
Dans une étude qualitative menée auprès de 27 employés de banque, nous avons étudié comment les algorithmes d'apprentissage façonnaient les conditions de travail, affectaient l'autonomie et le sens du travail, et l’évolution au fil du temps. Les résultats mettent en évidence que les employés réagissent à ces changements par des comportements de job crafting (Wrzesniewski et Dutton, 2001). En considérant les effets des algorithmes d'apprentissage sur l'expérience de travail des employés, nous proposons une nouvelle application de la théorie du job crafting aux technologies de l'IA.
La théorie du job crafting est utile pour montrer comment les employés réagissent à l'IA en modifiant les tâches, les limites relationnelles, et en repensant cognitivement leurs postes. Leurs comportements peuvent être interprétés comme une tentative de rééquilibrer les niveaux d'autonomie (initialement réduits par l'IA), de créer des relations personnelles plus étroites avec les clients et de repositionner leur sens du travail. Les comportements de job crafting des employés avaient également des implications pour leurs managers, leurs clients et le contexte en termes de signification des outils d'IA et de la manière dont ils étaient utilisés. La réponse des employés à travers les trois dimensions de job crafting souligne l'importance de la synergie entre ces dimensions s'ils veulent modifier leur expérience de travail et à renforcer la valeur humaine de leurs services.
Mots clés:
- intelligence artificielle,
- algorithmes,
- job crafting,
- job redesign,
- banque
Parties annexes
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