Applications in Workplace Health and Safety

Automation

Many manufacturing workplaces have begun to embed AI into their robots as a way to remove workers from hazardous situations while also improving the quality of work. The robots are not prone to fatigue and can perform highly repetitive tasks quicker and with more accuracy. Robots embedded with AI can facilitate work for those who are injured or disabled by accommodating the limitations of the worker, also referred to as “cobots”.

While these “cobots” can help workers, many are developed with self-learning algorithms, which can lead to less predictable actions for the workers collaborating with them, increasing the risk of collision or other accidents.

Advancements in AI has also led to the automation of cognitive tasks, such as automated driving, legal casework, and medical diagnoses. What this creates is a heavier reliance of robots and AI to perform complex tasks, leaving more sedentary and repetitive work for workers. With the reduction in cognitive load, this can lead to boredom and isolation/lack of interaction with peers, negatively affecting teamwork, eventually leading to an increase in the psychosocial risk factors.

Monitoring and Managing

Digital use of AI to monitor and manage workers has also grown in recent years. This allows for continuous and widespread monitoring through the collection of large amounts of real-time data. Using mobile devices, wearable, or embedded monitoring devices, AI systems can track information on location, vital signs, and signs of stress and fatigue.

This information can provide employers with new metrics on performance, improve productivity, reduce monitoring costs, and improve HR management. However, it is these forms of monitoring that can lead to more legal, regulatory, and ethical questions, including how it affects employee mental health.

Improving Worker Safety

Using AI-based monitoring can enable employers to improve the effectiveness and efficiency of a Health and Safety program through monitoring, reducing exposure risk, provide early warning signs of stress, health problems, and fatigue.

By integrating AI-based programs catered specifically to support evidence-based prevention, workplaces can identify and prevent health and safety issues where interventions are required at an organizational level.

Ethical and Sensitivity Concerns

With any type of workplace data collection, several ethical, information, and security strategies should be addressed before implementation to prevent the data from malicious or harmful use. Ensuring adequate provisions for legal and anonymity of the data can enable labour organizations to build effective evidence-based prevention and policies. This need for data must be balanced against the rights of workers to privacy. Transparency in collecting and using such data, and workers and their representatives should be collaborated with through the same access to information.

Final Notes

While the advancement of AI and technology integrated into workplaces has grown vastly in the last decade, workplaces looking to integrate more of these technologies should carefully consider the ethical and legal aspects, maintain clear communication with the staff, and continuously review and improve the process to ensure effective and safe integration.

References:

https://osha.europa.eu/en/publications/impact-artificial-intelligence-occupational-safety-and-health/view