Science and technology

In a groundbreaking initiative, the Finnish Institute of Occupational Health has unveiled the potential of artificial intelligence (AI) to revolutionize occupational safety. A four-year research project, titled "Improving Safety Management through Data Mining – AI Safety," conducted in collaboration with four Finnish industrial companies, explored how machine learning methods could enhance safety management and occupational safety protocols.

Traditional methods of reviewing vast amounts of occupational safety data have proven cumbersome for organizations. However, AI, particularly machine learning techniques like text mining, offers an efficient solution. These methods can quickly analyze extensive datasets, including implicit information related to the operating environment and context, enabling a comprehensive understanding of occupational safety trends.

"Artificial intelligence requires high-quality data to provide valuable insights. Systematic data collection, particularly related to deviations and human behavior, is essential. Contextual data is crucial for preparing forecasting models, helping organizations identify factors associated with safety issues," emphasized Maria Tiikkaja, Head of Research at the Finnish Institute of Occupational Health.

A pivotal aspect of the research was the development of a comprehensive guide aimed at organizations. This guide offers valuable methods for collecting safety data, enhancing data quality, and utilizing it effectively in machine learning-based safety management. Emphasizing the importance of data quality over quantity, the guide focuses on factors underlying safety issues, encouraging organizations to delve into personnel training and identify key elements.

"Instead of fixating on mandatory safety observation reporting quotas, organizations should concentrate on understanding the nuances of safety through comprehensive personnel training," advised Tiikkaja.

The guide advocates user-friendly data systems, accessible interfaces, and streamlined data recording processes. The ultimate goal is to create diverse, analyzed benchmark data amalgamated from various organizational functions. These analyses yield critical reports, empowering organizations to prepare comprehensive occupational safety overviews and facilitate continuous learning.

In the ideal scenario, organizations can leverage this analyzed occupational safety data to develop innovative strategies, ushering in a new era of occupational safety management and operations. With AI's transformative potential, the future of occupational safety is marked by proactive measures, data-driven decisions, and a safer workplace for all.