Predictive functions of artificial intelligence for risk assessment in remote hybrid work

Abstract

Remote hybrid work risk assessment is an obligation for the employer according to Occupational Safety and Health (OSH) regulations. Risk management requires the cooperation of the worker, who is now responsible for recognizing and managing hazards, necessitating specific technical training. Generative Artificial Intelligence (AI) technologies can support the knowledge needs of both workers and employers as effective tools for prevention in occupational health and safety, respecting privacy regulations and avoiding remote control of workers. Researchers from INAIL, Universitas Mercatorum, and the University of Sannio are developing an AI-based assistant for assessing risk in remote and hybrid work, facing challenges in assistant training due to limited availability of data on incidents and illnesses related to remote work. The generative AI prototype will be able to evaluate the relationship between remote work activities and types of injuries, using domestic injury data to identify patterns and high-risk areas. By integrating Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs), the hybrid model will enable a dynamic and comprehensive analysis of hazards, contributing to a better understanding of risk factors in hybrid work contexts.