As artificial intelligence (AI) continues to influence the future of work, several different industries are exploring the use of artificial intelligence worker management (AIWM) to automate or semi-automate tasks such as shift scheduling and work allocation, as well as to monitor activity and evaluate performance.

The European Agency for Safety and Health at Work (EU-OSHA) recently published a report on the potential workplace impacts of artificial intelligence worker management on workplace health and safety.

What is artificial intelligence worker management?

Artificial intelligence worker management uses digital systems and algorithms to collect real-time data from workers and the workplace. These systems use AI-based models to make automated or semi-automated decisions about factors such as task allocation or workload. Automated decisions are made without human involvement. Semi-automated decisions are where the AI system provides the operator or manager with real-time information to help them make informed decisions.

Where and how is it being used?

In larger European companies where work involves mostly manual and repetitive routine tasks, the report provides examples of artificial intelligence worker management systems being used to improve demand prediction, shift scheduling, and task assignment based on workers’ capabilities. At one Italian auto part manufacturer, the AI-based system helped skilled operators adapt to changing constraints using real-time data and automated task assignments, with the goal of enhancing productivity, reducing stress, and improving work-life balance. In another example, AI chatbots analyze communication patterns to detect and prevent mental health issues and provide personalized support.

What are the risks to health and safety?

Introducing artificial intelligence worker management to mainly increase productivity, and without consulting workers on its purpose and use, can have profound physical and psychological impacts. Using AI to monitor and direct work can lead to work intensification. Workers may experience higher pressure to perform, avoid breaks, and be told to work more and faster, which increases the risk of incidents and musculoskeletal disorders. This accelerated pace of work can also lead to stress, fatigue and burnout, affecting a wide range of workplaces from banking and call centres to warehouses. Workers may also experience feelings of surveillance and a lack of control when digital systems determine their work tasks, pace and schedule.

Where performance results are visible to peers, artificial intelligence worker management can create an environment of unhealthy competition and feelings of social isolation. The collection of confidential or sensitive data can also raise privacy concerns among workers and lead to feelings of distrust. In some cases, excessive automation can reduce the need for workers’ and managers’ cognitive or creative abilities, which can lead to stress and reduced job satisfaction.

How can it improve health and safety?

To date, the evidence of artificial intelligence worker management improving health and safety is limited, but there are several potential benefits. The collected data can influence the design of more effective health and safety training programs in the future. Matching tasks to workers’ skills can make the division of work more efficient, increasing job satisfaction. By monitoring workplace conditions, digital systems can warn of risks to workers such as excessive workload, fatigue and burnout. They can also optimize work routines to improve workers’ safety, well-being and productivity. Since the impact of artificial intelligence worker management on workplaces is not yet fully understood, employers need to continuously evaluate these technologies to further improve strategies to promote and protect the health and safety of workers.

How can potential hazards be prevented?

Trust is a determining factor for managing the potential health and safety risks of implementing AI workplace management systems. Foster trust by considering the impacts on workers at every step, including whether to use the technology at all. Involve workers in decisions, be transparent about data collection and use, perform risk assessments, and provide information and training. When workers know employers and managers are invested in their ability to work well, not just hard, they are more comfortable raising concerns about potential performance pressure and burnout.

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