Robots are increasingly used in a variety of work environments, but surprisingly little attention has been paid to how robots change work. In this comparative case study, we explore how robotization changed the work design of order pickers and order packers in eight logistic warehouses. We found that all warehouses robotized tasks based on technological functionality to increase efficiency, which sometimes created jobs consisting of ‘left-over tasks’. Only two warehouses used a bottom-up approach, where employees were involved in the implementation and quality of work was considered important. Although the other warehouses did not, sometimes their work design still benefitted from robotization. The positive effects we identified are reduced physical and cognitive demands and opportunities for upskilling. Warehouses that lack attention to the quality of work may risk ending up with the negative effects for employees, such as simplification and intensification of work, and reduced autonomy. We propose that understanding the consequences of robots on work design supports HR professionals to help managing this transition by both giving relevant input on a strategic level about the importance of work design and advocating for employees and their involvement.
Artificial intelligence-driven technology increasingly shapes work practices and, accordingly, employees’ opportunities for meaningful work (MW). In our paper, we identify five dimensions of MW: pursuing a purpose, social relationships, exercising skills and self-development, autonomy, self-esteem and recognition. Because MW is an important good, lacking opportunities for MW is a serious disadvantage. Therefore, we need to know to what extent employers have a duty to provide this good to their employees. We hold that employers have a duty of beneficence to design for opportunities for MW when implementing AI-technology in the workplace. We argue that this duty of beneficence is supported by the three major ethical theories, namely, Kantian ethics, consequentialism, and virtue ethics. We defend this duty against two objections, including the view that it is incompatible with the shareholder theory of the firm. We then employ the five dimensions of MW as our analytical lens to investigate how AI-based technological innovation in logistic warehouses has an impact, both positively and negatively, on MW, and illustrate that design for MW is feasible. We further support this practical feasibility with the help of insights from organizational psychology. We end by discussing how AI-based technology has an impact both on meaningful work (often seen as an aspirational goal) and decent work (generally seen as a matter of justice). Accordingly, ethical reflection on meaningful and decent work should become more integrated to do justice to how AI-technology inevitably shapes both simultaneously.
The American company Amazon has made headlines several times for monitoring its workers in warehouses across Europe and beyond.1 What is new is that a national data protection authority has recently issued a substantial fine of €32 million to the e-commerce giant for breaching several provisions of the General Data Protection Regulation (gdpr) with its surveillance practices. On 27 December 2023, the Commission nationale de l’informatique et des libertés (cnil)—the French Data Protection Authority—determined that Amazon France Logistique infringed on, among others, Articles 6(1)(f) (principle of lawfulness) and 5(1)(c) (data minimization) gdpr by processing some of workers’ data collected by handheld scanner in the distribution centers of Lauwin-Planque and Montélimar.2 Scanners enable employees to perform direct tasks such as picking and scanning items while continuously collecting data on quality of work, productivity, and periods of inactivity.3 According to the company, this data processing is necessary for various purposes, including quality and safety in warehouse management, employee coaching and performance evaluation, and work planning.4 The cnil’s decision centers on data protection law, but its implications reach far beyond into workers’ fundamental right to health and safety at work. As noted in legal literature and policy documents, digital surveillance practices can have a significant impact on workers’ mental health and overall well-being.5 This commentary examines the cnil’s decision through the lens of European occupational health and safety (EU ohs). Its scope is limited to how the French authority has interpreted the data protection principle of lawfulness taking into account the impact of some of Amazon’s monitoring practices on workers’ fundamental right to health and safety.
MULTIFILE
The demand for mobile agents in industrial environments to perform various tasks is growing tremendously in recent years. However, changing environments, security considerations and robustness against failure are major persistent challenges autonomous agents have to face when operating alongside other mobile agents. Currently, such problems remain largely unsolved. Collaborative multi-platform Cyber- Physical-Systems (CPSs) in which different agents flexibly contribute with their relative equipment and capabilities forming a symbiotic network solving multiple objectives simultaneously are highly desirable. Our proposed SMART-AGENTS platform will enable flexibility and modularity providing multi-objective solutions, demonstrated in two industrial domains: logistics (cycle-counting in warehouses) and agriculture (pest and disease identification in greenhouses). Aerial vehicles are limited in their computational power due to weight limitations but offer large mobility to provide access to otherwise unreachable places and an “eagle eye” to inform about terrain, obstacles by taking pictures and videos. Specialized autonomous agents carrying optical sensors will enable disease classification and product recognition improving green- and warehouse productivity. Newly developed micro-electromechanical systems (MEMS) sensor arrays will create 3D flow-based images of surroundings even in dark and hazy conditions contributing to the multi-sensor system, including cameras, wireless signatures and magnetic field information shared among the symbiotic fleet. Integration of mobile systems, such as smart phones, which are not explicitly controlled, will provide valuable information about human as well as equipment movement in the environment by generating data from relative positioning sensors, such as wireless and magnetic signatures. Newly developed algorithms will enable robust autonomous navigation and control of the fleet in dynamic environments incorporating the multi-sensor data generated by the variety of mobile actors. The proposed SMART-AGENTS platform will use real-time 5G communication and edge computing providing new organizational structures to cope with scalability and integration of multiple devices/agents. It will enable a symbiosis of the complementary CPSs using a combination of equipment yielding efficiency and versatility of operation.
